refactor(onboarding): drop old page

* feat(dashboards-v2): list panel kind (logs/traces) with row detail

* feat(dashboards-v2): list columns editor with datasource column switch

* feat(dashboards-v2): move list columns editor below the query builder

Replace the config-pane Columns section with a dnd-kit reorderable editor
rendered beneath the query builder (V1 parity); sanitize selectFields to the
field-key DTO so saved columns drop non-contract keys (isIndexed).

* style(dashboards-v2): format list panel header with oxfmt

* refactor(dashboards-v2): drop the unsupported-panel fallback

Every panel kind now has a renderer, so the "not yet supported in V2"
body is dead. Remove UnsupportedPanelBody and render the panel body
behind a plain `panelDefinition &&` guard. Also clean up the panel-kind
typing in Panel.tsx: `spec.plugin.kind` is non-optional and already a
PanelKind, so the `as unknown as` cast and `?.` chains go away.

* refactor(dashboards-v2): tighten the getPanelDefinition cast

Drop the dead `if (!kind)` guard (a partial registry already returns
undefined for absent keys) and reduce the `as unknown as` double-cast to
a single `as` — comparability clears it, so the unknown laundering was
unnecessary.

* refactor(dashboards-v2): narrow renderer props to the panel kind

PanelRendererProps<K> now carries a `panel` narrowed to kind K (via a
PluginOfKind helper that picks the variant from the generated plugin
union), so each renderer reads `panel.spec.plugin.spec` as its exact spec
DTO. Removes the per-renderer `as <Kind>SpecDTO` cast (and the now-dead
`?? {}` fallbacks) across all seven renderers; the single unavoidable
widening stays in getPanelDefinition.

* feat(dashboards-v2): create new panels from the editor

Add a draft-first create flow: picking a panel type opens the editor at
`/panel/new?panelKind=…&layoutIndex=…` on an in-memory default panel, and
nothing is persisted until save — cancelling leaves the dashboard
untouched (V1 parity). On save a new panel is minted (uuid) and added to
the target section via `createPanelOps` (resolves the section, or creates
one when the dashboard has none).

All "Add panel" triggers (section header, empty section, empty dashboard,
toolbar) route through a single useCreatePanel hook + the V2 type picker;
the leftover V1 global modal and useAddPanelToSection are removed.

New panels seed sensible defaults from the kind's supported signals: the
query datasource (e.g. List → logs, not the unsupported metrics default)
and, for List, the signal's default columns — so the Columns control
isn't empty on first open. New panels always re-serialize their query for
the kind on save, so the persisted query is valid even if untouched.

echo "--- working tree after commits (should be only dev hack) ---"; git status --short

* fix(dashboards-v2): place a new panel in the last row's free space

createPanelOps placed every new panel at x:0 on a fresh row, so a half-full
last row left its right half empty. Find the first free slot in the section's
last row (right of its panels) and only wrap to a new row when it can't fit.

* fix(uplot): center a single-item chart legend

isSingleRow read the container width from a ref inside useMemo, so it computed
once at mount (ref still null → width 0 → false) and only recovered if the
component happened to re-render. The uPlot legend re-renders on plot sync so it
recovered by luck; the Pie legend doesn't, leaving a single item clipped in a
narrow grid track. Measure the container with useResizeObserver instead.

* feat(dashboards-v2): unified panel empty, no-data and no-query states

Add a shared PanelMessage component (icon + title + description + optional
action) backing every non-chart panel state. PanelBody now shows a 'Nothing to
visualize yet' state for panels with no runnable query and a polished error
state with Retry. NoData becomes a 'No data in this time range' affordance with
an optional Retry, wired through a new optional refetch on the renderer props.

* fix(dashboards-v2): derive the preview "Plotted with" tag from the panel query

The editor preview hardcoded EQueryType.QUERY_BUILDER, so PromQL/ClickHouse
panels were mislabelled and list panels still showed the tag. Add a V2 PlotTag
(mirroring V1: hidden for list panels and before a query exists) fed by a new
getPanelQueryType util that reads the panel's V5 envelopes.

* feat(dashboards-v2): panel header title with description tooltip

Replace PanelHeader's ReactNode title with explicit name + description props,
rendering the description as an info-icon tooltip in the header instead of a
wrapper around the title. Panel passes them directly (no headerTitle memo).

* refactor(dashboards-v2): let consumers own the refetch loader signal

usePanelQuery returns the raw react-query isLoading; the dashboard panel and the
editor preview now compute isLoading || isFetching themselves, so each surface
decides whether a background refetch shows the full loader.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* fix(dashboards-v2): default a threshold's label to an empty string on save

* feat(dashboards-v2): show the panel header in the editor preview

Reuse PanelHeader in PreviewPane so the editor preview shows the panel
title, description tooltip, refetch spinner, and error/warning indicators,
with the body rendered flush beneath it like the dashboard grid panel.

Add a hideActions flag to PanelHeader to suppress the actions menu in the
editor: View/Edit/Clone/Delete don't apply there, and omitting panelActions
alone isn't enough since View/Edit/Download survive their own gates. Wire the
table/list header search through the preview as the grid does, and thread the
raw isFetching for the header's refetch spinner.

* feat(dashboards-v2): seed new panels with per-kind config defaults

A new panel was seeded with an empty plugin spec, so the config pane's
dropdowns and segmented controls (time scope, legend position, line style /
interpolation, fill mode) opened with nothing selected.

Derive a default plugin spec from each kind's declared sections via a new pure
buildDefaultPluginSpec helper and seed it in createDefaultPanel. Each default
equals the matching renderer fallback, so only the config-pane display changes,
not the rendered output. Controls whose empty state already reads as the chart
default (unit/decimals "auto", switches, numeric "Auto" inputs) are left unset.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* fix(dashboards-v2): preserve list columns across datasource round-trips

The List panel stores a single selectFields list, so switching the query
signal replaced the columns with the new datasource's defaults — going
logs -> traces -> logs discarded a customized logs selection.

Remember each signal's columns and restore them when switching back;
defaults still seed a signal the first time it's seen.

* docs(dashboards-v2): trim verbose comments to minimal-why style

Condense multi-paragraph block comments and drop comments that restate
the code across the new-panel editor surface, keeping only the non-obvious
"why" and concise JSDoc on functions and type fields. Comment-only — no
code, types, or test assertions changed.

* fix(dashboards-v2): show resource attributes like service.name in trace list panels

The List renderer only flattened nested resource/attribute maps for logs, so a
selected resource field such as service.name (nested under resources_string)
rendered N/A for traces even though the same data shows in V1. Flatten traces too.

* feat(dashboards-v2): open new List panels on a runnable logs query (V1 parity)

A new List panel opened blank: its seed query had an empty orderBy and lived only
in the builder, so the preview didn't run on open. Seed spec.queries at creation
with the V1 list logs query (orderBy timestamp desc) so the panel opens on logs,
pre-sorted, and the preview runs immediately; wire up useSeedNewListColumns so its
default columns (timestamp, body) are populated too. Switching to traces is handled
by the builder's list-view path.

* fix(dashboards-v2): drop all config-pane sections from the List panel

List columns are edited below the query builder, and Context Links isn't wanted in
the config pane, so the List panel now declares no config-pane sections.

* refactor(dashboards-v2): address PR review feedback

- getPanelDefinition: make PanelRegistry total over PanelKind so it never
  returns undefined (a missing kind is now a compile error)
- toQueryEnvelopes/hasRunnableQueries: accept `... | null` and drop the
  `?? []` at call sites
- consolidate panel loading to a single `isFetching` signal (Panel,
  PreviewPane, PanelEditor)
- rename defaultDataSource -> signal; use TelemetrytypesSignalDTO enum for
  the List default columns
- useCreatePanel now owns the panel-type picker state, deduping the three
  add-panel triggers; rename pluginKind -> panelKind
- LabelThresholdRow: extract onSave into a callback; ThresholdsSection test
  uses userEvent
- PreviewPane: drop the optional chaining on the required display field
- trim over-verbose comments

* refactor(dashboards-v2): type panel signals as TelemetrytypesSignalDTO

Replace the query-builder `DataSource` enum with `TelemetrytypesSignalDTO`
across the panel signal plumbing — the panel definitions' `supportedSignals`,
the List columns editor/suggestions/defaults, and the editor query-sync and
column-seeding hooks — and make the signal non-optional where a panel always
resolves one. Drops the now-dead `DataSource` imports.

* chore: pr review changes

* chore: pr review changes

---------

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

.github/workflows/jsci.yaml

@@ -56,17 +56,6 @@ jobs:
       PRIMUS_REF: main
       JS_SRC: frontend
       JS_PKG_MANAGER: pnpm
-  languages:
-    if: |
-      github.event_name == 'merge_group' ||
-      (github.event_name == 'pull_request' && ! github.event.pull_request.head.repo.fork && github.event.pull_request.user.login != 'dependabot[bot]' && ! contains(github.event.pull_request.labels.*.name, 'safe-to-test')) ||
-      (github.event_name == 'pull_request_target' && contains(github.event.pull_request.labels.*.name, 'safe-to-test'))
-    runs-on: ubuntu-latest
-    steps:
-      - name: self-checkout
-        uses: actions/checkout@v4
-      - name: run
-        run: bash frontend/scripts/validate-md-languages.sh
   openapi:
     if: |
       github.event_name == 'merge_group' ||

deploy/MIGRATION.md

@@ -1,48 +1,76 @@
-# Migrating from the install script to Foundry
+# Migrating from the install script and `deploy/` to Foundry
+
+The install script (`install.sh`) and the bundled Compose and Swarm files
+under `deploy/` are deprecated in favor of [Foundry][foundry], the supported
+way to install and manage SigNoz. This guide moves an existing Docker Compose
+or Docker Swarm deployment to Foundry and reattaches your existing volumes, so
+your data is preserved.
 
 > [!IMPORTANT]
-> The install script is now deprecated and will no longer receive updates.
+> This guide is only for **existing** `install.sh` / `deploy/` deployments.
+> Setting up SigNoz for the first time? Skip migration and install Foundry
+> directly: [SigNoz install docs][install-docs].
 
-This guide walks you through migrating an existing SigNoz deployment running via
-Docker Compose to [Foundry](https://signoz.io/docs/install/docker/).
+## How it works
 
-> [!NOTE]
-> Setting up SigNoz for the first time? You don't need this guide — follow the [SigNoz installation docs](https://signoz.io/docs/install/) instead.
+Foundry splits a deployment into two commands:
 
-## Overview
-To stay up to date on new installation platforms and patterns, please refer to [Foundry](https://github.com/SigNoz/foundry).
+- `foundryctl forge` generates the deployment manifests from a `casting.yaml`.
+  It never touches running containers, so it is safe to re-run while you
+  iterate.
+- `foundryctl cast` applies those manifests: it (re)creates the containers and
+  reuses the volumes you point it at.
 
-Two `foundryctl` commands are used throughout this guide:
-- **`forge`** — generates deployment manifests from your `casting.yaml`. It does not touch running containers, so it is safe to re-run while you iterate.
-- **`cast`** — applies the generated manifests: it creates and starts the containers (and pulls new images).
+You write one `casting.yaml`, point a few patches at your existing data
+volumes, then cast. The steps below are the same for Compose and Swarm; they
+differ only in the casting (step 3) and how you stop the old stack (step 5).
 
 ## Prerequisites
-- [ ] Install Foundry - `curl -fsSL https://signoz.io/foundry.sh | bash`
 
-## Migration Steps
-> [!WARNING]
-> **Before proceeding, back up both:**
-> - **Your docker volumes** — these hold your data.
-> - **Your existing `docker-compose.yaml` (and any config it references)** — keep a copy somewhere safe. The compose manifests are no longer distributed by SigNoz, so this backup is your only way to roll back to your previous setup.
+- An existing SigNoz deployment from `install.sh` or `deploy/` (Compose or
+  Swarm).
+- `foundryctl` (installed in step 1).
 
-1. Make a note of the volume names used by your existing deployment for the following components:
-- ClickHouse
-- SigNoz
-- ZooKeeper
+## Migrate
 
-> If you used the docker compose file we provided, the volumes will be `signoz-clickhouse`, `signoz-sqlite`, and `signoz-zookeeper-1`.
+### 1. Install Foundry
 
-2. Generate your `casting.yaml`. Based on internal testing, the following casting should generate the manifests that mimic the legacy docker compose setup (compare against your backed-up `docker-compose.yaml`). Once created, run `foundryctl forge -f casting.yaml`.
+```bash
+curl -fsSL https://signoz.io/foundry.sh | bash
+```
 
-Foundry has a [Docker Compose example](https://github.com/SigNoz/foundry/tree/main/docs/examples/docker/compose). Please use it as a reference.
+### 2. Keep your rollback path
 
-> [!WARNING]
-> If your deployment had more than 1 shard or replica, you will need to adjust your manifest volumes accordingly.
+This migration reattaches your existing volumes in place; it does not move or
+delete your data. The only destructive action is passing `--volumes` / `-v`
+when you stop the old stack (step 5), so avoid that flag.
 
 > [!IMPORTANT]
-> The `replica` and `shard` macros below are placeholders. Replace them with the values from your existing ClickHouse configuration (check the `macros` section of your current ClickHouse config, e.g. `config.xml`/`metrika.xml`), otherwise the generated manifests will not match your existing data.
+> Keep a copy of your existing `docker-compose.yaml` / stack file (and any
+> config it references). SigNoz no longer distributes these files, so this copy
+> is your only way to roll back.
+
+### 3. Write your `casting.yaml`
+
+Use the casting for your deployment. Both reproduce the legacy single-node
+setup (ClickHouse + ZooKeeper + SQLite) and reattach your existing volumes;
+they differ only in `spec.deployment.flavor` and the volume-reuse patch
+(Compose volumes have a `name` to replace; Swarm volumes are bare, so the whole
+entry is replaced). If your deployment ran more than one shard or replica,
+adjust the volume patches accordingly. The
+[Docker Compose example][compose-example] is a useful reference.
+
+> [!IMPORTANT]
+> The `replica` and `shard` macros are placeholders. Replace them with the
+> values from your existing ClickHouse config (the `macros` section of
+> `config.xml` / `metrika.xml`), or the generated manifests will not match your
+> existing data.
+
+<details>
+<summary><b>Docker Compose</b> casting.yaml</summary>
 
 ```yaml
+# casting.yaml
 apiVersion: v1alpha1
 kind: Installation
 metadata:
@@ -61,8 +89,8 @@ spec:
         data:
           config-0-0.yaml: |
             macros:
-              replica: "example01-01-1" # replace with your existing ClickHouse replica macro (see legacy configuration files for reference)
-              shard: "01"               # replace with your existing ClickHouse shard macro (see legacy configuration files for reference)
+              replica: "example01-01-1" # replace with your replica macro
+              shard: "01" # replace with your shard macro
   patches:
     - target: "deployment/compose.yaml"
       operations:
@@ -80,50 +108,163 @@ spec:
           value: root
 ```
 
-> [!NOTE]
-> The `user: root` patch on the ZooKeeper service is required so the container can read/write the data in your reused ZooKeeper volume, which was created with `root`-owned files by the legacy compose setup. Without it, ZooKeeper may fail to start with permission errors.
+</details>
 
-If you had custom configurations for features like SMTP or additional ingestion processors/receivers, you will need to include those in your casting file via [patches](https://github.com/SigNoz/foundry/blob/main/docs/concepts/patches.md), [custom configuration](https://github.com/SigNoz/foundry/blob/main/docs/concepts/moldings.md#custom-config-files) or [environment variables](https://github.com/SigNoz/foundry/blob/main/docs/reference/casting-file.md#molding-spec) based on your previous configuration.
+<details>
+<summary><b>Docker Swarm</b> casting.yaml</summary>
 
-3. Review your manifests, we suggest executing the following checks on your manifests before proceeding:
-- [ ] Validate the container images match what your deployment had, Foundry uses `latest` on generation by default.
-- [ ] If your signoz version was older than latest, please check the [upgrade path](https://signoz.io/docs/operate/upgrade/) first.
-- [ ] Check the produced manifests in `pours/deployment` match your older configurations. Extra consideration and review needs to be done on `compose.yaml` as this will be the main entry point for your new deployment.
-- [ ] The configuration files for clickhouse are now in YAML so validate your custom settings are present.
+```yaml
+# casting.yaml
+apiVersion: v1alpha1
+kind: Installation
+metadata:
+  name: signoz
+spec:
+  deployment:
+    flavor: swarm
+    mode: docker
+  metastore:
+    kind: sqlite
+  telemetrykeeper:
+    kind: zookeeper
+  telemetrystore:
+    spec:
+      config:
+        data:
+          config-0-0.yaml: |
+            macros:
+              replica: "example01-01-1" # replace with your replica macro
+              shard: "01" # replace with your shard macro
+  patches:
+    - target: "deployment/compose.yaml"
+      operations:
+        - op: replace
+          path: /volumes/signoz-telemetrykeeper-0-data
+          value:
+            name: signoz-zookeeper-1
+        - op: replace
+          path: /volumes/signoz-telemetrystore-0-0-data
+          value:
+            name: signoz-clickhouse
+        - op: replace
+          path: /volumes/signoz-metastore-sqlite-0-data
+          value:
+            name: signoz-sqlite
+        - op: add
+          path: /services/signoz-telemetrykeeper-zookeeper-0/user
+          value: root
+```
 
-4. Execute a `docker compose down`. **Do not** include parameters such as `--volumes` (or `-v`), as it will wipe the volumes we need to maintain and reuse to avoid data loss. 
+</details>
 
 > [!NOTE]
-> This will generate downtime so please plan accordingly.
+> The `user: root` patch on the ZooKeeper service lets the container read and
+> write the data in your reused ZooKeeper volume, whose files the legacy setup
+> created as `root`. Without it, ZooKeeper may fail to start with permission
+> errors.
 
-5. Validate the SigNoz containers are down with `docker ps -a`. Multiple containers cannot bind the same volume.
+If you had custom configuration (SMTP, extra ingestion receivers/processors,
+or custom ClickHouse settings), carry it over via [patches][patches],
+[custom config files][custom-config], or [environment variables][env-vars].
 
-6. Run `foundryctl cast -f casting.yaml`. This will recreate the containers based on the spec. This process will download new container images.
+### 4. Generate and review the manifests
+
+```bash
+foundryctl forge -f casting.yaml
+```
+
+Review `pours/deployment/` before deploying:
+
+- [ ] Container images match your current deployment. Foundry generates with
+  `latest` by default; if your SigNoz version was older than latest, check the
+  [upgrade path][upgrade-path] first.
+- [ ] The generated manifests match your previous configuration, especially
+  `compose.yaml` (the new entry point for your deployment).
+- [ ] The ClickHouse config is now YAML rather than XML; confirm your custom
+  settings carried over (see [ClickHouse configuration files][ch-config] for
+  the XML-to-YAML mapping).
+
+### 5. Stop the old deployment
+
+Use the command for your deployment. Do **not** pass `--volumes` / `-v`; that
+would delete the data you are migrating.
+
+```bash
+docker compose down        # Compose
+docker stack rm signoz     # Swarm
+```
 
 > [!NOTE]
-> When `cast` is run, the migration container will execute its migrations.
+> This causes downtime, so plan accordingly.
 
-## Verifying the Migration
-- SigNoz containers will be up and running.
-- Log in to the SigNoz UI and verify that data is present.
-    - Signoz will run on localhost:8080
-- Validate that your data ingestion is receiving data.
-    - Ingesters will receive data on localhost:4317(grpc) and localhost:4318(http)
-- Review the logs from both ClickHouse and ZooKeeper; no errors should be present.
+Confirm nothing is still bound to the volumes before continuing:
 
-## Rolling Back
-Because step 4 brought the legacy stack down *without* `-v`, your original volumes
-are untouched and still hold your data. To roll back:
+```bash
+docker ps -a
+```
 
-- Stop and remove the containers created by Foundry (`docker compose down`, again without `-v`).
-- Confirm the containers are gone with `docker ps -a` so nothing else is bound to the volumes.
-- Reapply your original docker compose file (`docker compose up -d`). It will reattach to the
-  existing volumes and restore your prior state.
+### 6. Deploy with Foundry
+
+```bash
+foundryctl cast -f casting.yaml
+```
+
+This recreates the containers against your existing volumes and pulls the
+images. The migration container runs the schema migrations as part of `cast`.
+
+**Prefer not to use `cast`?** The manifests in `pours/deployment/` are standard
+Docker artifacts you can apply yourself. Run the command from that directory so
+the relative config paths resolve:
+
+```bash
+cd pours/deployment
+docker compose up -d                        # Compose
+docker stack deploy -c compose.yaml signoz  # Swarm
+```
+
+## Verify
+
+- All SigNoz containers are running.
+- The UI is reachable on `http://localhost:8080`, and OTLP on `4317` (gRPC)
+  and `4318` (HTTP), so already-instrumented apps and saved bookmarks keep
+  working.
+- Your existing data is present in the UI, and new data is being ingested.
+- ClickHouse and ZooKeeper logs show no errors.
+
+## Roll back
+
+Step 5 left your volumes untouched, so your data is intact. To return to the
+previous setup:
+
+1. Bring down the Foundry deployment (`docker compose down` or
+   `docker stack rm signoz`, again without `-v`).
+2. Confirm the containers are gone with `docker ps -a`.
+3. Re-apply your backed-up stack: `docker compose up -d` (Compose) or
+   `docker stack deploy -c docker-compose.yaml signoz` (Swarm). It reattaches
+   the same volumes and restores your prior state.
 
 ## Troubleshooting
-- Please reach out to our community on [Slack](https://signoz.io/slack).
+
+If the migration runs into trouble, reach out on [Slack][slack] or open a
+[Foundry issue][foundry-issues].
 
 ## References
-- [SigNoz Docker installation docs](https://signoz.io/docs/install/docker/)
-- [SigNoz documentation](https://signoz.io/docs)
-- [Foundry](https://github.com/SigNoz/foundry)
+
+- [Foundry][foundry]
+- [Casting file reference][casting-ref]
+- [Custom config files][custom-config]
+- [Patches][patches]
+- [SigNoz documentation][signoz-docs]
+
+[foundry]: https://github.com/SigNoz/foundry
+[install-docs]: https://signoz.io/docs/install/
+[compose-example]: https://github.com/SigNoz/foundry/tree/main/docs/examples/docker/compose
+[patches]: https://github.com/SigNoz/foundry/blob/main/docs/concepts/patches.md
+[custom-config]: https://github.com/SigNoz/foundry/blob/main/docs/concepts/moldings.md#custom-config-files
+[env-vars]: https://github.com/SigNoz/foundry/blob/main/docs/reference/casting-file.md#molding-spec
+[casting-ref]: https://github.com/SigNoz/foundry/blob/main/docs/reference/casting-file.md
+[ch-config]: https://clickhouse.com/docs/operations/configuration-files
+[upgrade-path]: https://signoz.io/docs/operate/upgrade/
+[slack]: https://signoz.io/slack
+[foundry-issues]: https://github.com/SigNoz/foundry/issues
+[signoz-docs]: https://signoz.io/docs

docs/api/openapi.yml

@@ -4011,6 +4011,94 @@ components:
         enabled:
           type: boolean
       type: object
+    InframonitoringtypesAssociatedComponent:
+      properties:
+        name:
+          type: string
+        type:
+          $ref: '#/components/schemas/InframonitoringtypesCheckComponentType'
+      required:
+      - type
+      - name
+      type: object
+    InframonitoringtypesAttributesComponentEntry:
+      properties:
+        associatedComponent:
+          $ref: '#/components/schemas/InframonitoringtypesAssociatedComponent'
+        attributes:
+          items:
+            type: string
+          nullable: true
+          type: array
+      required:
+      - attributes
+      - associatedComponent
+      type: object
+    InframonitoringtypesCheckComponentType:
+      enum:
+      - receiver
+      - processor
+      type: string
+    InframonitoringtypesCheckType:
+      enum:
+      - hosts
+      - processes
+      - pods
+      - nodes
+      - deployments
+      - daemonsets
+      - statefulsets
+      - jobs
+      - namespaces
+      - clusters
+      - volumes
+      type: string
+    InframonitoringtypesChecks:
+      properties:
+        missingDefaultEnabledMetrics:
+          items:
+            $ref: '#/components/schemas/InframonitoringtypesMissingMetricsComponentEntry'
+          nullable: true
+          type: array
+        missingOptionalMetrics:
+          items:
+            $ref: '#/components/schemas/InframonitoringtypesMissingMetricsComponentEntry'
+          nullable: true
+          type: array
+        missingRequiredAttributes:
+          items:
+            $ref: '#/components/schemas/InframonitoringtypesMissingAttributesComponentEntry'
+          nullable: true
+          type: array
+        presentDefaultEnabledMetrics:
+          items:
+            $ref: '#/components/schemas/InframonitoringtypesMetricsComponentEntry'
+          nullable: true
+          type: array
+        presentOptionalMetrics:
+          items:
+            $ref: '#/components/schemas/InframonitoringtypesMetricsComponentEntry'
+          nullable: true
+          type: array
+        presentRequiredAttributes:
+          items:
+            $ref: '#/components/schemas/InframonitoringtypesAttributesComponentEntry'
+          nullable: true
+          type: array
+        ready:
+          type: boolean
+        type:
+          $ref: '#/components/schemas/InframonitoringtypesCheckType'
+      required:
+      - type
+      - ready
+      - presentDefaultEnabledMetrics
+      - presentOptionalMetrics
+      - presentRequiredAttributes
+      - missingDefaultEnabledMetrics
+      - missingOptionalMetrics
+      - missingRequiredAttributes
+      type: object
     InframonitoringtypesClusterRecord:
       properties:
         clusterCPU:
@@ -4054,8 +4142,6 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesClusterRecord'
           type: array
-        requiredMetricsCheck:
-          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4066,7 +4152,6 @@ components:
       - type
       - records
       - total
-      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     InframonitoringtypesDaemonSetRecord:
@@ -4123,8 +4208,6 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesDaemonSetRecord'
           type: array
-        requiredMetricsCheck:
-          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4135,7 +4218,6 @@ components:
       - type
       - records
       - total
-      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     InframonitoringtypesDeploymentRecord:
@@ -4192,8 +4274,6 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesDeploymentRecord'
           type: array
-        requiredMetricsCheck:
-          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4204,7 +4284,6 @@ components:
       - type
       - records
       - total
-      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     InframonitoringtypesHostFilter:
@@ -4270,8 +4349,6 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesHostRecord'
           type: array
-        requiredMetricsCheck:
-          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4282,7 +4359,6 @@ components:
       - type
       - records
       - total
-      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     InframonitoringtypesJobRecord:
@@ -4345,8 +4421,6 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesJobRecord'
           type: array
-        requiredMetricsCheck:
-          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4357,9 +4431,59 @@ components:
       - type
       - records
       - total
-      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
+    InframonitoringtypesMetricsComponentEntry:
+      properties:
+        associatedComponent:
+          $ref: '#/components/schemas/InframonitoringtypesAssociatedComponent'
+        metrics:
+          items:
+            type: string
+          nullable: true
+          type: array
+      required:
+      - metrics
+      - associatedComponent
+      type: object
+    InframonitoringtypesMissingAttributesComponentEntry:
+      properties:
+        associatedComponent:
+          $ref: '#/components/schemas/InframonitoringtypesAssociatedComponent'
+        attributes:
+          items:
+            type: string
+          nullable: true
+          type: array
+        documentationLink:
+          type: string
+        message:
+          type: string
+      required:
+      - attributes
+      - associatedComponent
+      - message
+      - documentationLink
+      type: object
+    InframonitoringtypesMissingMetricsComponentEntry:
+      properties:
+        associatedComponent:
+          $ref: '#/components/schemas/InframonitoringtypesAssociatedComponent'
+        documentationLink:
+          type: string
+        message:
+          type: string
+        metrics:
+          items:
+            type: string
+          nullable: true
+          type: array
+      required:
+      - metrics
+      - associatedComponent
+      - message
+      - documentationLink
+      type: object
     InframonitoringtypesNamespaceRecord:
       properties:
         meta:
@@ -4392,8 +4516,6 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesNamespaceRecord'
           type: array
-        requiredMetricsCheck:
-          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4404,7 +4526,6 @@ components:
       - type
       - records
       - total
-      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     InframonitoringtypesNodeCondition:
@@ -4469,8 +4590,6 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesNodeRecord'
           type: array
-        requiredMetricsCheck:
-          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4481,7 +4600,6 @@ components:
       - type
       - records
       - total
-      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     InframonitoringtypesPodCountsByPhase:
@@ -4567,8 +4685,6 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesPodRecord'
           type: array
-        requiredMetricsCheck:
-          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4579,7 +4695,6 @@ components:
       - type
       - records
       - total
-      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     InframonitoringtypesPostableClusters:
@@ -4842,16 +4957,6 @@ components:
       - end
       - limit
       type: object
-    InframonitoringtypesRequiredMetricsCheck:
-      properties:
-        missingMetrics:
-          items:
-            type: string
-          nullable: true
-          type: array
-      required:
-      - missingMetrics
-      type: object
     InframonitoringtypesResponseType:
       enum:
       - list
@@ -4911,8 +5016,6 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesStatefulSetRecord'
           type: array
-        requiredMetricsCheck:
-          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4923,7 +5026,6 @@ components:
       - type
       - records
       - total
-      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     InframonitoringtypesVolumeRecord:
@@ -4971,8 +5073,6 @@ components:
           items:
             $ref: '#/components/schemas/InframonitoringtypesVolumeRecord'
           type: array
-        requiredMetricsCheck:
-          $ref: '#/components/schemas/InframonitoringtypesRequiredMetricsCheck'
         total:
           type: integer
         type:
@@ -4983,7 +5083,6 @@ components:
       - type
       - records
       - total
-      - requiredMetricsCheck
       - endTimeBeforeRetention
       type: object
     LlmpricingruletypesGettablePricingRules:
@@ -14868,6 +14967,72 @@ paths:
       summary: Health check
       tags:
       - health
+  /api/v2/infra_monitoring/checks:
+    get:
+      deprecated: false
+      description: 'Checks whether the metrics and attributes required to power the
+        infra-monitoring section selected by the ''type'' query parameter (hosts,
+        processes, pods, nodes, deployments, daemonsets, statefulsets, jobs, namespaces,
+        clusters, volumes) are being received. For each collector receiver or processor
+        that contributes required metrics or attributes, lists what is present and
+        what is missing, with a prebuilt user-facing message and a docs link per missing
+        component. Default-enabled metrics are those expected as soon as the receiver
+        is configured; optional metrics require ''enabled: true'' in receiver config.
+        ''ready'' is true only when every missing list is empty.'
+      operationId: GetChecks
+      parameters:
+      - in: query
+        name: type
+        required: true
+        schema:
+          $ref: '#/components/schemas/InframonitoringtypesCheckType'
+      responses:
+        "200":
+          content:
+            application/json:
+              schema:
+                properties:
+                  data:
+                    $ref: '#/components/schemas/InframonitoringtypesChecks'
+                  status:
+                    type: string
+                required:
+                - status
+                - data
+                type: object
+          description: OK
+        "400":
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/RenderErrorResponse'
+          description: Bad Request
+        "401":
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/RenderErrorResponse'
+          description: Unauthorized
+        "403":
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/RenderErrorResponse'
+          description: Forbidden
+        "500":
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/RenderErrorResponse'
+          description: Internal Server Error
+      security:
+      - api_key:
+        - VIEWER
+      - tokenizer:
+        - VIEWER
+      summary: Run Infra Monitoring Setup Checks
+      tags:
+      - inframonitoring
   /api/v2/infra_monitoring/clusters:
     post:
       deprecated: false
@@ -14882,10 +15047,10 @@ paths:
         for custom groupBy keys; in both modes every row aggregates nodes and pods
         in the group. Supports filtering via a filter expression, custom groupBy,
         ordering by cpu / cpu_allocatable / memory / memory_allocatable, and pagination
-        via offset/limit. Also reports missing required metrics and whether the requested
-        time range falls before the data retention boundary. Numeric metric fields
-        (clusterCPU, clusterCPUAllocatable, clusterMemory, clusterMemoryAllocatable)
-        return -1 as a sentinel when no data is available for that field.'
+        via offset/limit. Also reports whether the requested time range falls before
+        the data retention boundary. Numeric metric fields (clusterCPU, clusterCPUAllocatable,
+        clusterMemory, clusterMemoryAllocatable) return -1 as a sentinel when no data
+        is available for that field.'
       operationId: ListClusters
       requestBody:
         content:
@@ -14958,11 +15123,11 @@ paths:
         row aggregates pods owned by daemonsets in the group. Supports filtering via
         a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit
         / memory / memory_request / memory_limit / desired_nodes / current_nodes,
-        and pagination via offset/limit. Also reports missing required metrics and
-        whether the requested time range falls before the data retention boundary.
-        Numeric metric fields (daemonSetCPU, daemonSetCPURequest, daemonSetCPULimit,
-        daemonSetMemory, daemonSetMemoryRequest, daemonSetMemoryLimit, desiredNodes,
-        currentNodes) return -1 as a sentinel when no data is available for that field.'
+        and pagination via offset/limit. Also reports whether the requested time range
+        falls before the data retention boundary. Numeric metric fields (daemonSetCPU,
+        daemonSetCPURequest, daemonSetCPULimit, daemonSetMemory, daemonSetMemoryRequest,
+        daemonSetMemoryLimit, desiredNodes, currentNodes) return -1 as a sentinel
+        when no data is available for that field.'
       operationId: ListDaemonSets
       requestBody:
         content:
@@ -15033,11 +15198,11 @@ paths:
         group. Supports filtering via a filter expression, custom groupBy, ordering
         by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit
         / desired_pods / available_pods, and pagination via offset/limit. Also reports
-        missing required metrics and whether the requested time range falls before
-        the data retention boundary. Numeric metric fields (deploymentCPU, deploymentCPURequest,
-        deploymentCPULimit, deploymentMemory, deploymentMemoryRequest, deploymentMemoryLimit,
-        desiredPods, availablePods) return -1 as a sentinel when no data is available
-        for that field.'
+        whether the requested time range falls before the data retention boundary.
+        Numeric metric fields (deploymentCPU, deploymentCPURequest, deploymentCPULimit,
+        deploymentMemory, deploymentMemoryRequest, deploymentMemoryLimit, desiredPods,
+        availablePods) return -1 as a sentinel when no data is available for that
+        field.'
       operationId: ListDeployments
       requestBody:
         content:
@@ -15102,10 +15267,9 @@ paths:
         custom groupBy to aggregate hosts by any attribute, ordering by any of the
         five metrics, and pagination via offset/limit. The response type is ''list''
         for the default host.name grouping or ''grouped_list'' for custom groupBy
-        keys. Also reports missing required metrics and whether the requested time
-        range falls before the data retention boundary. Numeric metric fields (cpu,
-        memory, wait, load15, diskUsage) return -1 as a sentinel when no data is available
-        for that field.'
+        keys. Also reports whether the requested time range falls before the data
+        retention boundary. Numeric metric fields (cpu, memory, wait, load15, diskUsage)
+        return -1 as a sentinel when no data is available for that field.'
       operationId: ListHosts
       requestBody:
         content:
@@ -15179,11 +15343,11 @@ paths:
         jobs in the group. Supports filtering via a filter expression, custom groupBy,
         ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit
         / desired_successful_pods / active_pods / failed_pods / successful_pods, and
-        pagination via offset/limit. Also reports missing required metrics and whether
-        the requested time range falls before the data retention boundary. Numeric
-        metric fields (jobCPU, jobCPURequest, jobCPULimit, jobMemory, jobMemoryRequest,
-        jobMemoryLimit, desiredSuccessfulPods, activePods, failedPods, successfulPods)
-        return -1 as a sentinel when no data is available for that field.'
+        pagination via offset/limit. Also reports whether the requested time range
+        falls before the data retention boundary. Numeric metric fields (jobCPU, jobCPURequest,
+        jobCPULimit, jobMemory, jobMemoryRequest, jobMemoryLimit, desiredSuccessfulPods,
+        activePods, failedPods, successfulPods) return -1 as a sentinel when no data
+        is available for that field.'
       operationId: ListJobs
       requestBody:
         content:
@@ -15248,10 +15412,10 @@ paths:
         type is ''list'' for the default k8s.namespace.name grouping or ''grouped_list''
         for custom groupBy keys; in both modes every row aggregates pods in the group.
         Supports filtering via a filter expression, custom groupBy, ordering by cpu
-        / memory, and pagination via offset/limit. Also reports missing required metrics
-        and whether the requested time range falls before the data retention boundary.
-        Numeric metric fields (namespaceCPU, namespaceMemory) return -1 as a sentinel
-        when no data is available for that field.'
+        / memory, and pagination via offset/limit. Also reports whether the requested
+        time range falls before the data retention boundary. Numeric metric fields
+        (namespaceCPU, namespaceMemory) return -1 as a sentinel when no data is available
+        for that field.'
       operationId: ListNamespaces
       requestBody:
         content:
@@ -15319,10 +15483,10 @@ paths:
         for custom groupBy keys (each row aggregates nodes in the group; condition
         stays no_data). Supports filtering via a filter expression, custom groupBy,
         ordering by cpu / cpu_allocatable / memory / memory_allocatable, and pagination
-        via offset/limit. Also reports missing required metrics and whether the requested
-        time range falls before the data retention boundary. Numeric metric fields
-        (nodeCPU, nodeCPUAllocatable, nodeMemory, nodeMemoryAllocatable) return -1
-        as a sentinel when no data is available for that field.'
+        via offset/limit. Also reports whether the requested time range falls before
+        the data retention boundary. Numeric metric fields (nodeCPU, nodeCPUAllocatable,
+        nodeMemory, nodeMemoryAllocatable) return -1 as a sentinel when no data is
+        available for that field.'
       operationId: ListNodes
       requestBody:
         content:
@@ -15391,11 +15555,10 @@ paths:
         is one pod with its current phase) or ''grouped_list'' for custom groupBy
         keys (each row aggregates pods in the group with per-phase counts under podCountsByPhase:
         { pending, running, succeeded, failed, unknown } derived from each pod''s
-        latest phase in the window). Also reports missing required metrics and whether
-        the requested time range falls before the data retention boundary. Numeric
-        metric fields (podCPU, podCPURequest, podCPULimit, podMemory, podMemoryRequest,
-        podMemoryLimit, podAge) return -1 as a sentinel when no data is available
-        for that field.'
+        latest phase in the window). Also reports whether the requested time range
+        falls before the data retention boundary. Numeric metric fields (podCPU, podCPURequest,
+        podCPULimit, podMemory, podMemoryRequest, podMemoryLimit, podAge) return -1
+        as a sentinel when no data is available for that field.'
       operationId: ListPods
       requestBody:
         content:
@@ -15462,11 +15625,10 @@ paths:
         usage, inodes, inodes_free, inodes_used), and pagination via offset/limit.
         The response type is ''list'' for the default k8s.persistentvolumeclaim.name
         grouping or ''grouped_list'' for custom groupBy keys; in both modes every
-        row aggregates volumes in the group. Also reports missing required metrics
-        and whether the requested time range falls before the data retention boundary.
-        Numeric metric fields (volumeAvailable, volumeCapacity, volumeUsage, volumeInodes,
-        volumeInodesFree, volumeInodesUsed) return -1 as a sentinel when no data is
-        available for that field.'
+        row aggregates volumes in the group. Also reports whether the requested time
+        range falls before the data retention boundary. Numeric metric fields (volumeAvailable,
+        volumeCapacity, volumeUsage, volumeInodes, volumeInodesFree, volumeInodesUsed)
+        return -1 as a sentinel when no data is available for that field.'
       operationId: ListVolumes
       requestBody:
         content:
@@ -15537,11 +15699,10 @@ paths:
         statefulsets in the group. Supports filtering via a filter expression, custom
         groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request
         / memory_limit / desired_pods / current_pods, and pagination via offset/limit.
-        Also reports missing required metrics and whether the requested time range
-        falls before the data retention boundary. Numeric metric fields (statefulSetCPU,
-        statefulSetCPURequest, statefulSetCPULimit, statefulSetMemory, statefulSetMemoryRequest,
-        statefulSetMemoryLimit, desiredPods, currentPods) return -1 as a sentinel
-        when no data is available for that field.'
+        Also reports whether the requested time range falls before the data retention
+        boundary. Numeric metric fields (statefulSetCPU, statefulSetCPURequest, statefulSetCPULimit,
+        statefulSetMemory, statefulSetMemoryRequest, statefulSetMemoryLimit, desiredPods,
+        currentPods) return -1 as a sentinel when no data is available for that field.'
       operationId: ListStatefulSets
       requestBody:
         content:

ee/query-service/app/server.go

@@ -90,8 +90,12 @@ func NewServer(config signoz.Config, signoz *signoz.SigNoz) (*Server, error) {
 
 	// initiate agent config handler
 	agentConfMgr, err := agentConf.Initiate(&agentConf.ManagerOptions{
-		Store:         signoz.SQLStore,
-		AgentFeatures: []agentConf.AgentFeature{logParsingPipelineController},
+		Store: signoz.SQLStore,
+		AgentFeatures: []agentConf.AgentFeature{
+			logParsingPipelineController,
+			signoz.Modules.SpanMapper,
+			signoz.Modules.LLMPricingRule,
+		},
 	})
 	if err != nil {
 		return nil, err

frontend/public/locales/en/routes.json

@@ -15,6 +15,8 @@
 	"logs_to_metrics": "Logs To Metrics",
 	"roles": "Roles",
 	"role_details": "Role Details",
+	"role_edit": "Edit Role",
+	"role_create": "Create Role",
 	"members": "Members",
 	"service_accounts": "Service Accounts",
 	"mcp_server": "MCP Server"

frontend/public/locales/en/titles.json

@@ -82,6 +82,8 @@
 	"TRACE_DETAIL_OLD": "SigNoz | Trace Detail",
 	"SERVICE_TOP_LEVEL_OPERATIONS": "SigNoz | Service Operations",
 	"ROLE_DETAILS": "SigNoz | Role Details",
+	"ROLE_CREATE": "SigNoz | Create Role",
+	"ROLE_EDIT": "SigNoz | Edit Role",
 	"TRACES_FUNNELS_DETAIL": "SigNoz | Funnel",
 	"INTEGRATIONS_DETAIL": "SigNoz | Integration",
 	"PUBLIC_DASHBOARD": "SigNoz | Dashboard"

frontend/scripts/extract-md-languages.sh

@@ -1,13 +0,0 @@
-#!/usr/bin/env bash
-# Extracts unique fenced code block language identifiers from all .md files under frontend/src/
-# Usage: bash frontend/scripts/extract-md-languages.sh
-
-set -euo pipefail
-
-SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-SRC_DIR="$SCRIPT_DIR/../src"
-
-grep -roh '```[a-zA-Z0-9_+-]*' "$SRC_DIR" --include='*.md' \
-  | sed 's/^```//' \
-  | grep -v '^$' \
-  | sort -u

frontend/scripts/validate-md-languages.sh

@@ -1,41 +0,0 @@
-#!/usr/bin/env bash
-# Validates that all fenced code block languages used in .md files are registered
-# in the syntax highlighter.
-# Usage: bash frontend/scripts/validate-md-languages.sh
-
-set -euo pipefail
-
-SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-SYNTAX_HIGHLIGHTER="$SCRIPT_DIR/../src/components/MarkdownRenderer/syntaxHighlighter.ts"
-
-# Get all languages used in .md files
-md_languages=$("$SCRIPT_DIR/extract-md-languages.sh")
-
-# Get all registered languages from syntaxHighlighter.ts
-registered_languages=$(grep -oP "registerLanguage\('\K[^']+" "$SYNTAX_HIGHLIGHTER" | sort -u)
-
-missing_languages=()
-
-for lang in $md_languages; do
-  # Skip ai-* block markers — these are custom AI block types rendered by
-  # RichCodeBlock as React components (e.g. ActionBlock, LineChartBlock),
-  # not real syntax languages, so they don't need highlighter registration.
-  if [[ "$lang" == ai-* ]]; then
-    continue
-  fi
-  if ! echo "$registered_languages" | grep -qx "$lang"; then
-    missing_languages+=("$lang")
-  fi
-done
-
-if [ ${#missing_languages[@]} -gt 0 ]; then
-  echo "Error: The following languages are used in .md files but not registered in syntaxHighlighter.ts:"
-  for lang in "${missing_languages[@]}"; do
-    echo "  - $lang"
-  done
-  echo ""
-  echo "Please add them to: frontend/src/components/MarkdownRenderer/syntaxHighlighter.ts"
-  exit 1
-fi
-
-echo "All markdown code block languages are registered in syntaxHighlighter.ts"

frontend/src/AppRoutes/Private.tsx

@@ -3,7 +3,6 @@ import { matchPath, Redirect, useLocation } from 'react-router-dom';
 import getLocalStorageApi from 'api/browser/localstorage/get';
 import setLocalStorageApi from 'api/browser/localstorage/set';
 import { useListUsers } from 'api/generated/services/users';
-import { FeatureKeys } from 'constants/features';
 import { LOCALSTORAGE } from 'constants/localStorage';
 import { ORG_PREFERENCES } from 'constants/orgPreferences';
 import ROUTES from 'constants/routes';
@@ -37,7 +36,6 @@ function PrivateRoute({ children }: PrivateRouteProps): JSX.Element {
 		activeLicense,
 		isFetchingActiveLicense,
 		trialInfo,
-		featureFlags,
 	} = useAppContext();
 
 	const isAdmin = user.role === USER_ROLES.ADMIN;
@@ -212,14 +210,6 @@ function PrivateRoute({ children }: PrivateRouteProps): JSX.Element {
 		}
 	}
 
-	// Check for GET_STARTED → GET_STARTED_WITH_CLOUD redirect (feature flag)
-	if (
-		currentRoute?.path === ROUTES.GET_STARTED &&
-		featureFlags?.find((e) => e.name === FeatureKeys.ONBOARDING_V3)?.active
-	) {
-		return <Redirect to={ROUTES.GET_STARTED_WITH_CLOUD} />;
-	}
-
 	// Main routing logic
 	if (currentRoute) {
 		const { isPrivate, key } = currentRoute;

frontend/src/AppRoutes/__tests__/Private.test.tsx

@@ -2,7 +2,6 @@ import { ReactElement } from 'react';
 import { QueryClient, QueryClientProvider } from 'react-query';
 import { MemoryRouter, Route, Switch, useLocation } from 'react-router-dom';
 import { act, render, screen, waitFor } from '@testing-library/react';
-import { FeatureKeys } from 'constants/features';
 import { LOCALSTORAGE } from 'constants/localStorage';
 import { ORG_PREFERENCES } from 'constants/orgPreferences';
 import ROUTES from 'constants/routes';
@@ -1263,80 +1262,6 @@ describe('PrivateRoute', () => {
 		});
 	});
 
-	describe('Get Started Route Redirect', () => {
-		it('should redirect to GET_STARTED_WITH_CLOUD when on GET_STARTED and ONBOARDING_V3 feature flag is active', async () => {
-			renderPrivateRoute({
-				initialRoute: ROUTES.GET_STARTED,
-				appContext: {
-					isLoggedIn: true,
-					featureFlags: [
-						{
-							name: FeatureKeys.ONBOARDING_V3,
-							active: true,
-							usage: 0,
-							usage_limit: -1,
-							route: '',
-						},
-					],
-				},
-			});
-
-			await assertRedirectsTo(ROUTES.GET_STARTED_WITH_CLOUD);
-		});
-
-		it('should not redirect when on GET_STARTED and ONBOARDING_V3 feature flag is inactive', () => {
-			renderPrivateRoute({
-				initialRoute: ROUTES.GET_STARTED,
-				appContext: {
-					isLoggedIn: true,
-					featureFlags: [
-						{
-							name: FeatureKeys.ONBOARDING_V3,
-							active: false,
-							usage: 0,
-							usage_limit: -1,
-							route: '',
-						},
-					],
-				},
-			});
-
-			assertStaysOnRoute(ROUTES.GET_STARTED);
-		});
-
-		it('should not redirect when on GET_STARTED and ONBOARDING_V3 feature flag is not present', () => {
-			renderPrivateRoute({
-				initialRoute: ROUTES.GET_STARTED,
-				appContext: {
-					isLoggedIn: true,
-					featureFlags: [],
-				},
-			});
-
-			assertStaysOnRoute(ROUTES.GET_STARTED);
-		});
-
-		it('should not redirect when on different route even if ONBOARDING_V3 is active', () => {
-			renderPrivateRoute({
-				initialRoute: ROUTES.HOME,
-				appContext: {
-					isLoggedIn: true,
-					featureFlags: [
-						{
-							name: FeatureKeys.ONBOARDING_V3,
-							active: true,
-							usage: 0,
-							usage_limit: -1,
-							route: '',
-						},
-					],
-				},
-			});
-
-			assertStaysOnRoute(ROUTES.HOME);
-		});
-	});
-
 	describe('Loading States', () => {
 		it('should not redirect while license is still being fetched', () => {
 			renderPrivateRoute({
@@ -1496,16 +1421,16 @@ describe('PrivateRoute', () => {
 			await assertRedirectsTo(ROUTES.UN_AUTHORIZED);
 		});
 
-		it('should allow EDITOR to access /get-started route', () => {
+		it('should allow EDITOR to access /get-started-with-signoz-cloud route', () => {
 			renderPrivateRoute({
-				initialRoute: ROUTES.GET_STARTED,
+				initialRoute: ROUTES.GET_STARTED_WITH_CLOUD,
 				appContext: {
 					isLoggedIn: true,
 					user: createMockUser({ role: USER_ROLES.EDITOR as ROLES }),
 				},
 			});
 
-			assertStaysOnRoute(ROUTES.GET_STARTED);
+			assertStaysOnRoute(ROUTES.GET_STARTED_WITH_CLOUD);
 		});
 	});
 

frontend/src/AppRoutes/pageComponents.ts

@@ -90,14 +90,6 @@ export const SettingsPage = Loadable(
 	() => import(/* webpackChunkName: "SettingsPage" */ 'pages/Settings'),
 );
 
-export const GettingStarted = Loadable(
-	() => import(/* webpackChunkName: "GettingStarted" */ 'pages/GettingStarted'),
-);
-
-export const Onboarding = Loadable(
-	() => import(/* webpackChunkName: "Onboarding" */ 'pages/OnboardingPage'),
-);
-
 export const OrgOnboarding = Loadable(
 	() => import(/* webpackChunkName: "OrgOnboarding" */ 'pages/OrgOnboarding'),
 );

frontend/src/AppRoutes/routes.ts

@@ -33,7 +33,6 @@ import {
 	MeterExplorerPage,
 	MetricsExplorer,
 	OldLogsExplorer,
-	Onboarding,
 	OnboardingV2,
 	OrgOnboarding,
 	PasswordReset,
@@ -70,13 +69,6 @@ const routes: AppRoutes[] = [
 		isPrivate: false,
 		key: 'SIGN_UP',
 	},
-	{
-		path: ROUTES.GET_STARTED,
-		exact: false,
-		component: Onboarding,
-		isPrivate: true,
-		key: 'GET_STARTED',
-	},
 	{
 		path: ROUTES.GET_STARTED_WITH_CLOUD,
 		exact: false,

frontend/src/api/generated/services/inframonitoring/index.ts

@@ -4,14 +4,22 @@
  * * regenerate with 'pnpm generate:api'
  * SigNoz
  */
-import { useMutation } from 'react-query';
+import { useMutation, useQuery } from 'react-query';
 import type {
+	InvalidateOptions,
 	MutationFunction,
+	QueryClient,
+	QueryFunction,
+	QueryKey,
 	UseMutationOptions,
 	UseMutationResult,
+	UseQueryOptions,
+	UseQueryResult,
 } from 'react-query';
 
 import type {
+	GetChecks200,
+	GetChecksParams,
 	InframonitoringtypesPostableClustersDTO,
 	InframonitoringtypesPostableDaemonSetsDTO,
 	InframonitoringtypesPostableDeploymentsDTO,
@@ -39,7 +47,94 @@ import { GeneratedAPIInstance } from '../../../generatedAPIInstance';
 import type { ErrorType, BodyType } from '../../../generatedAPIInstance';
 
 /**
- * Returns a paginated list of Kubernetes clusters with key aggregated metrics derived by summing per-node values within the group: CPU usage, CPU allocatable, memory working set, memory allocatable. Each row also reports per-group nodeCountsByReadiness ({ ready, notReady } from each node's latest k8s.node.condition_ready value) and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each cluster includes metadata attributes (k8s.cluster.name). The response type is 'list' for the default k8s.cluster.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates nodes and pods in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_allocatable / memory / memory_allocatable, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (clusterCPU, clusterCPUAllocatable, clusterMemory, clusterMemoryAllocatable) return -1 as a sentinel when no data is available for that field.
+ * Checks whether the metrics and attributes required to power the infra-monitoring section selected by the 'type' query parameter (hosts, processes, pods, nodes, deployments, daemonsets, statefulsets, jobs, namespaces, clusters, volumes) are being received. For each collector receiver or processor that contributes required metrics or attributes, lists what is present and what is missing, with a prebuilt user-facing message and a docs link per missing component. Default-enabled metrics are those expected as soon as the receiver is configured; optional metrics require 'enabled: true' in receiver config. 'ready' is true only when every missing list is empty.
+ * @summary Run Infra Monitoring Setup Checks
+ */
+export const getChecks = (params: GetChecksParams, signal?: AbortSignal) => {
+	return GeneratedAPIInstance<GetChecks200>({
+		url: `/api/v2/infra_monitoring/checks`,
+		method: 'GET',
+		params,
+		signal,
+	});
+};
+
+export const getGetChecksQueryKey = (params?: GetChecksParams) => {
+	return [
+		`/api/v2/infra_monitoring/checks`,
+		...(params ? [params] : []),
+	] as const;
+};
+
+export const getGetChecksQueryOptions = <
+	TData = Awaited<ReturnType<typeof getChecks>>,
+	TError = ErrorType<RenderErrorResponseDTO>,
+>(
+	params: GetChecksParams,
+	options?: {
+		query?: UseQueryOptions<Awaited<ReturnType<typeof getChecks>>, TError, TData>;
+	},
+) => {
+	const { query: queryOptions } = options ?? {};
+
+	const queryKey = queryOptions?.queryKey ?? getGetChecksQueryKey(params);
+
+	const queryFn: QueryFunction<Awaited<ReturnType<typeof getChecks>>> = ({
+		signal,
+	}) => getChecks(params, signal);
+
+	return { queryKey, queryFn, ...queryOptions } as UseQueryOptions<
+		Awaited<ReturnType<typeof getChecks>>,
+		TError,
+		TData
+	> & { queryKey: QueryKey };
+};
+
+export type GetChecksQueryResult = NonNullable<
+	Awaited<ReturnType<typeof getChecks>>
+>;
+export type GetChecksQueryError = ErrorType<RenderErrorResponseDTO>;
+
+/**
+ * @summary Run Infra Monitoring Setup Checks
+ */
+
+export function useGetChecks<
+	TData = Awaited<ReturnType<typeof getChecks>>,
+	TError = ErrorType<RenderErrorResponseDTO>,
+>(
+	params: GetChecksParams,
+	options?: {
+		query?: UseQueryOptions<Awaited<ReturnType<typeof getChecks>>, TError, TData>;
+	},
+): UseQueryResult<TData, TError> & { queryKey: QueryKey } {
+	const queryOptions = getGetChecksQueryOptions(params, options);
+
+	const query = useQuery(queryOptions) as UseQueryResult<TData, TError> & {
+		queryKey: QueryKey;
+	};
+
+	return { ...query, queryKey: queryOptions.queryKey };
+}
+
+/**
+ * @summary Run Infra Monitoring Setup Checks
+ */
+export const invalidateGetChecks = async (
+	queryClient: QueryClient,
+	params: GetChecksParams,
+	options?: InvalidateOptions,
+): Promise<QueryClient> => {
+	await queryClient.invalidateQueries(
+		{ queryKey: getGetChecksQueryKey(params) },
+		options,
+	);
+
+	return queryClient;
+};
+
+/**
+ * Returns a paginated list of Kubernetes clusters with key aggregated metrics derived by summing per-node values within the group: CPU usage, CPU allocatable, memory working set, memory allocatable. Each row also reports per-group nodeCountsByReadiness ({ ready, notReady } from each node's latest k8s.node.condition_ready value) and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each cluster includes metadata attributes (k8s.cluster.name). The response type is 'list' for the default k8s.cluster.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates nodes and pods in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_allocatable / memory / memory_allocatable, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (clusterCPU, clusterCPUAllocatable, clusterMemory, clusterMemoryAllocatable) return -1 as a sentinel when no data is available for that field.
  * @summary List Clusters for Infra Monitoring
  */
 export const listClusters = (
@@ -122,7 +217,7 @@ export const useListClusters = <
 	return useMutation(getListClustersMutationOptions(options));
 };
 /**
- * Returns a paginated list of Kubernetes DaemonSets with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the daemonset, plus average CPU/memory request and limit utilization (daemonSetCPURequest, daemonSetCPULimit, daemonSetMemoryRequest, daemonSetMemoryLimit). Each row also reports the latest known node-level counters from kube-state-metrics: desiredNodes (k8s.daemonset.desired_scheduled_nodes, the number of nodes the daemonset wants to run on) and currentNodes (k8s.daemonset.current_scheduled_nodes, the number of nodes the daemonset currently runs on) — note these are node counts, not pod counts. It also reports per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each daemonset includes metadata attributes (k8s.daemonset.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.daemonset.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by daemonsets in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_nodes / current_nodes, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (daemonSetCPU, daemonSetCPURequest, daemonSetCPULimit, daemonSetMemory, daemonSetMemoryRequest, daemonSetMemoryLimit, desiredNodes, currentNodes) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of Kubernetes DaemonSets with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the daemonset, plus average CPU/memory request and limit utilization (daemonSetCPURequest, daemonSetCPULimit, daemonSetMemoryRequest, daemonSetMemoryLimit). Each row also reports the latest known node-level counters from kube-state-metrics: desiredNodes (k8s.daemonset.desired_scheduled_nodes, the number of nodes the daemonset wants to run on) and currentNodes (k8s.daemonset.current_scheduled_nodes, the number of nodes the daemonset currently runs on) — note these are node counts, not pod counts. It also reports per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each daemonset includes metadata attributes (k8s.daemonset.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.daemonset.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by daemonsets in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_nodes / current_nodes, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (daemonSetCPU, daemonSetCPURequest, daemonSetCPULimit, daemonSetMemory, daemonSetMemoryRequest, daemonSetMemoryLimit, desiredNodes, currentNodes) return -1 as a sentinel when no data is available for that field.
  * @summary List DaemonSets for Infra Monitoring
  */
 export const listDaemonSets = (
@@ -205,7 +300,7 @@ export const useListDaemonSets = <
 	return useMutation(getListDaemonSetsMutationOptions(options));
 };
 /**
- * Returns a paginated list of Kubernetes Deployments with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the deployment, plus average CPU/memory request and limit utilization (deploymentCPURequest, deploymentCPULimit, deploymentMemoryRequest, deploymentMemoryLimit). Each row also reports the latest known desiredPods (k8s.deployment.desired) and availablePods (k8s.deployment.available) replica counts and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each deployment includes metadata attributes (k8s.deployment.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.deployment.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by deployments in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_pods / available_pods, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (deploymentCPU, deploymentCPURequest, deploymentCPULimit, deploymentMemory, deploymentMemoryRequest, deploymentMemoryLimit, desiredPods, availablePods) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of Kubernetes Deployments with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the deployment, plus average CPU/memory request and limit utilization (deploymentCPURequest, deploymentCPULimit, deploymentMemoryRequest, deploymentMemoryLimit). Each row also reports the latest known desiredPods (k8s.deployment.desired) and availablePods (k8s.deployment.available) replica counts and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each deployment includes metadata attributes (k8s.deployment.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.deployment.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by deployments in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_pods / available_pods, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (deploymentCPU, deploymentCPURequest, deploymentCPULimit, deploymentMemory, deploymentMemoryRequest, deploymentMemoryLimit, desiredPods, availablePods) return -1 as a sentinel when no data is available for that field.
  * @summary List Deployments for Infra Monitoring
  */
 export const listDeployments = (
@@ -288,7 +383,7 @@ export const useListDeployments = <
 	return useMutation(getListDeploymentsMutationOptions(options));
 };
 /**
- * Returns a paginated list of hosts with key infrastructure metrics: CPU usage (%), memory usage (%), I/O wait (%), disk usage (%), and 15-minute load average. Each host includes its current status (active/inactive based on metrics reported in the last 10 minutes) and metadata attributes (e.g., os.type). Supports filtering via a filter expression, filtering by host status, custom groupBy to aggregate hosts by any attribute, ordering by any of the five metrics, and pagination via offset/limit. The response type is 'list' for the default host.name grouping or 'grouped_list' for custom groupBy keys. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (cpu, memory, wait, load15, diskUsage) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of hosts with key infrastructure metrics: CPU usage (%), memory usage (%), I/O wait (%), disk usage (%), and 15-minute load average. Each host includes its current status (active/inactive based on metrics reported in the last 10 minutes) and metadata attributes (e.g., os.type). Supports filtering via a filter expression, filtering by host status, custom groupBy to aggregate hosts by any attribute, ordering by any of the five metrics, and pagination via offset/limit. The response type is 'list' for the default host.name grouping or 'grouped_list' for custom groupBy keys. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (cpu, memory, wait, load15, diskUsage) return -1 as a sentinel when no data is available for that field.
  * @summary List Hosts for Infra Monitoring
  */
 export const listHosts = (
@@ -371,7 +466,7 @@ export const useListHosts = <
 	return useMutation(getListHostsMutationOptions(options));
 };
 /**
- * Returns a paginated list of Kubernetes Jobs with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the job, plus average CPU/memory request and limit utilization (jobCPURequest, jobCPULimit, jobMemoryRequest, jobMemoryLimit). Each row also reports the latest known job-level counters from kube-state-metrics: desiredSuccessfulPods (k8s.job.desired_successful_pods, the target completion count), activePods (k8s.job.active_pods), failedPods (k8s.job.failed_pods, cumulative across the lifetime of the job), and successfulPods (k8s.job.successful_pods, cumulative). It also reports per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value); note podCountsByPhase.failed (current pod-phase) is distinct from failedPods (cumulative job kube-state-metric). Each job includes metadata attributes (k8s.job.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.job.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by jobs in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_successful_pods / active_pods / failed_pods / successful_pods, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (jobCPU, jobCPURequest, jobCPULimit, jobMemory, jobMemoryRequest, jobMemoryLimit, desiredSuccessfulPods, activePods, failedPods, successfulPods) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of Kubernetes Jobs with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the job, plus average CPU/memory request and limit utilization (jobCPURequest, jobCPULimit, jobMemoryRequest, jobMemoryLimit). Each row also reports the latest known job-level counters from kube-state-metrics: desiredSuccessfulPods (k8s.job.desired_successful_pods, the target completion count), activePods (k8s.job.active_pods), failedPods (k8s.job.failed_pods, cumulative across the lifetime of the job), and successfulPods (k8s.job.successful_pods, cumulative). It also reports per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value); note podCountsByPhase.failed (current pod-phase) is distinct from failedPods (cumulative job kube-state-metric). Each job includes metadata attributes (k8s.job.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.job.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by jobs in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_successful_pods / active_pods / failed_pods / successful_pods, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (jobCPU, jobCPURequest, jobCPULimit, jobMemory, jobMemoryRequest, jobMemoryLimit, desiredSuccessfulPods, activePods, failedPods, successfulPods) return -1 as a sentinel when no data is available for that field.
  * @summary List Jobs for Infra Monitoring
  */
 export const listJobs = (
@@ -454,7 +549,7 @@ export const useListJobs = <
 	return useMutation(getListJobsMutationOptions(options));
 };
 /**
- * Returns a paginated list of Kubernetes namespaces with key aggregated pod metrics: CPU usage and memory working set (summed across pods in the group), plus per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value in the window). Each namespace includes metadata attributes (k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.namespace.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / memory, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (namespaceCPU, namespaceMemory) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of Kubernetes namespaces with key aggregated pod metrics: CPU usage and memory working set (summed across pods in the group), plus per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value in the window). Each namespace includes metadata attributes (k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.namespace.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / memory, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (namespaceCPU, namespaceMemory) return -1 as a sentinel when no data is available for that field.
  * @summary List Namespaces for Infra Monitoring
  */
 export const listNamespaces = (
@@ -537,7 +632,7 @@ export const useListNamespaces = <
 	return useMutation(getListNamespacesMutationOptions(options));
 };
 /**
- * Returns a paginated list of Kubernetes nodes with key metrics: CPU usage, CPU allocatable, memory working set, memory allocatable, per-group nodeCountsByReadiness ({ ready, notReady } from each node's latest k8s.node.condition_ready in the window) and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } for pods scheduled on the listed nodes). Each node includes metadata attributes (k8s.node.uid, k8s.cluster.name). The response type is 'list' for the default k8s.node.name grouping (each row is one node with its current condition string: ready / not_ready / no_data) or 'grouped_list' for custom groupBy keys (each row aggregates nodes in the group; condition stays no_data). Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_allocatable / memory / memory_allocatable, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (nodeCPU, nodeCPUAllocatable, nodeMemory, nodeMemoryAllocatable) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of Kubernetes nodes with key metrics: CPU usage, CPU allocatable, memory working set, memory allocatable, per-group nodeCountsByReadiness ({ ready, notReady } from each node's latest k8s.node.condition_ready in the window) and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } for pods scheduled on the listed nodes). Each node includes metadata attributes (k8s.node.uid, k8s.cluster.name). The response type is 'list' for the default k8s.node.name grouping (each row is one node with its current condition string: ready / not_ready / no_data) or 'grouped_list' for custom groupBy keys (each row aggregates nodes in the group; condition stays no_data). Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_allocatable / memory / memory_allocatable, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (nodeCPU, nodeCPUAllocatable, nodeMemory, nodeMemoryAllocatable) return -1 as a sentinel when no data is available for that field.
  * @summary List Nodes for Infra Monitoring
  */
 export const listNodes = (
@@ -620,7 +715,7 @@ export const useListNodes = <
 	return useMutation(getListNodesMutationOptions(options));
 };
 /**
- * Returns a paginated list of Kubernetes pods with key metrics: CPU usage, CPU request/limit utilization, memory working set, memory request/limit utilization, current pod phase (pending/running/succeeded/failed/unknown/no_data), and pod age (ms since start time). Each pod includes metadata attributes (namespace, node, workload owner such as deployment/statefulset/daemonset/job/cronjob, cluster). Supports filtering via a filter expression, custom groupBy to aggregate pods by any attribute, ordering by any of the six metrics (cpu, cpu_request, cpu_limit, memory, memory_request, memory_limit), and pagination via offset/limit. The response type is 'list' for the default k8s.pod.uid grouping (each row is one pod with its current phase) or 'grouped_list' for custom groupBy keys (each row aggregates pods in the group with per-phase counts under podCountsByPhase: { pending, running, succeeded, failed, unknown } derived from each pod's latest phase in the window). Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (podCPU, podCPURequest, podCPULimit, podMemory, podMemoryRequest, podMemoryLimit, podAge) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of Kubernetes pods with key metrics: CPU usage, CPU request/limit utilization, memory working set, memory request/limit utilization, current pod phase (pending/running/succeeded/failed/unknown/no_data), and pod age (ms since start time). Each pod includes metadata attributes (namespace, node, workload owner such as deployment/statefulset/daemonset/job/cronjob, cluster). Supports filtering via a filter expression, custom groupBy to aggregate pods by any attribute, ordering by any of the six metrics (cpu, cpu_request, cpu_limit, memory, memory_request, memory_limit), and pagination via offset/limit. The response type is 'list' for the default k8s.pod.uid grouping (each row is one pod with its current phase) or 'grouped_list' for custom groupBy keys (each row aggregates pods in the group with per-phase counts under podCountsByPhase: { pending, running, succeeded, failed, unknown } derived from each pod's latest phase in the window). Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (podCPU, podCPURequest, podCPULimit, podMemory, podMemoryRequest, podMemoryLimit, podAge) return -1 as a sentinel when no data is available for that field.
  * @summary List Pods for Infra Monitoring
  */
 export const listPods = (
@@ -703,7 +798,7 @@ export const useListPods = <
 	return useMutation(getListPodsMutationOptions(options));
 };
 /**
- * Returns a paginated list of Kubernetes persistent volume claims (PVCs) with key volume metrics: available bytes, capacity bytes, usage (capacity - available), inodes, free inodes, and used inodes. Each row also includes metadata attributes (k8s.persistentvolumeclaim.name, k8s.pod.uid, k8s.pod.name, k8s.namespace.name, k8s.node.name, k8s.statefulset.name, k8s.cluster.name). Supports filtering via a filter expression, custom groupBy to aggregate volumes by any attribute, ordering by any of the six metrics (available, capacity, usage, inodes, inodes_free, inodes_used), and pagination via offset/limit. The response type is 'list' for the default k8s.persistentvolumeclaim.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates volumes in the group. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (volumeAvailable, volumeCapacity, volumeUsage, volumeInodes, volumeInodesFree, volumeInodesUsed) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of Kubernetes persistent volume claims (PVCs) with key volume metrics: available bytes, capacity bytes, usage (capacity - available), inodes, free inodes, and used inodes. Each row also includes metadata attributes (k8s.persistentvolumeclaim.name, k8s.pod.uid, k8s.pod.name, k8s.namespace.name, k8s.node.name, k8s.statefulset.name, k8s.cluster.name). Supports filtering via a filter expression, custom groupBy to aggregate volumes by any attribute, ordering by any of the six metrics (available, capacity, usage, inodes, inodes_free, inodes_used), and pagination via offset/limit. The response type is 'list' for the default k8s.persistentvolumeclaim.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates volumes in the group. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (volumeAvailable, volumeCapacity, volumeUsage, volumeInodes, volumeInodesFree, volumeInodesUsed) return -1 as a sentinel when no data is available for that field.
  * @summary List Volumes for Infra Monitoring
  */
 export const listVolumes = (
@@ -786,7 +881,7 @@ export const useListVolumes = <
 	return useMutation(getListVolumesMutationOptions(options));
 };
 /**
- * Returns a paginated list of Kubernetes StatefulSets with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the statefulset, plus average CPU/memory request and limit utilization (statefulSetCPURequest, statefulSetCPULimit, statefulSetMemoryRequest, statefulSetMemoryLimit). Each row also reports the latest known desiredPods (k8s.statefulset.desired_pods) and currentPods (k8s.statefulset.current_pods) replica counts and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each statefulset includes metadata attributes (k8s.statefulset.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.statefulset.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by statefulsets in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_pods / current_pods, and pagination via offset/limit. Also reports missing required metrics and whether the requested time range falls before the data retention boundary. Numeric metric fields (statefulSetCPU, statefulSetCPURequest, statefulSetCPULimit, statefulSetMemory, statefulSetMemoryRequest, statefulSetMemoryLimit, desiredPods, currentPods) return -1 as a sentinel when no data is available for that field.
+ * Returns a paginated list of Kubernetes StatefulSets with key aggregated pod metrics: CPU usage and memory working set summed across pods owned by the statefulset, plus average CPU/memory request and limit utilization (statefulSetCPURequest, statefulSetCPULimit, statefulSetMemoryRequest, statefulSetMemoryLimit). Each row also reports the latest known desiredPods (k8s.statefulset.desired_pods) and currentPods (k8s.statefulset.current_pods) replica counts and per-group podCountsByPhase ({ pending, running, succeeded, failed, unknown } from each pod's latest k8s.pod.phase value). Each statefulset includes metadata attributes (k8s.statefulset.name, k8s.namespace.name, k8s.cluster.name). The response type is 'list' for the default k8s.statefulset.name grouping or 'grouped_list' for custom groupBy keys; in both modes every row aggregates pods owned by statefulsets in the group. Supports filtering via a filter expression, custom groupBy, ordering by cpu / cpu_request / cpu_limit / memory / memory_request / memory_limit / desired_pods / current_pods, and pagination via offset/limit. Also reports whether the requested time range falls before the data retention boundary. Numeric metric fields (statefulSetCPU, statefulSetCPURequest, statefulSetCPULimit, statefulSetMemory, statefulSetMemoryRequest, statefulSetMemoryLimit, desiredPods, currentPods) return -1 as a sentinel when no data is available for that field.
  * @summary List StatefulSets for Infra Monitoring
  */
 export const listStatefulSets = (

frontend/src/api/generated/services/sigNoz.schemas.ts

@@ -5458,6 +5458,121 @@ export interface GlobaltypesConfigDTO {
 	mcp_url: string | null;
 }
 
+export enum InframonitoringtypesCheckComponentTypeDTO {
+	receiver = 'receiver',
+	processor = 'processor',
+}
+export interface InframonitoringtypesAssociatedComponentDTO {
+	/**
+	 * @type string
+	 */
+	name: string;
+	type: InframonitoringtypesCheckComponentTypeDTO;
+}
+
+export interface InframonitoringtypesAttributesComponentEntryDTO {
+	associatedComponent: InframonitoringtypesAssociatedComponentDTO;
+	/**
+	 * @type array,null
+	 */
+	attributes: string[] | null;
+}
+
+export enum InframonitoringtypesCheckTypeDTO {
+	hosts = 'hosts',
+	processes = 'processes',
+	pods = 'pods',
+	nodes = 'nodes',
+	deployments = 'deployments',
+	daemonsets = 'daemonsets',
+	statefulsets = 'statefulsets',
+	jobs = 'jobs',
+	namespaces = 'namespaces',
+	clusters = 'clusters',
+	volumes = 'volumes',
+}
+export interface InframonitoringtypesMissingMetricsComponentEntryDTO {
+	associatedComponent: InframonitoringtypesAssociatedComponentDTO;
+	/**
+	 * @type string
+	 */
+	documentationLink: string;
+	/**
+	 * @type string
+	 */
+	message: string;
+	/**
+	 * @type array,null
+	 */
+	metrics: string[] | null;
+}
+
+export interface InframonitoringtypesMissingAttributesComponentEntryDTO {
+	associatedComponent: InframonitoringtypesAssociatedComponentDTO;
+	/**
+	 * @type array,null
+	 */
+	attributes: string[] | null;
+	/**
+	 * @type string
+	 */
+	documentationLink: string;
+	/**
+	 * @type string
+	 */
+	message: string;
+}
+
+export interface InframonitoringtypesMetricsComponentEntryDTO {
+	associatedComponent: InframonitoringtypesAssociatedComponentDTO;
+	/**
+	 * @type array,null
+	 */
+	metrics: string[] | null;
+}
+
+export interface InframonitoringtypesChecksDTO {
+	/**
+	 * @type array,null
+	 */
+	missingDefaultEnabledMetrics:
+		| InframonitoringtypesMissingMetricsComponentEntryDTO[]
+		| null;
+	/**
+	 * @type array,null
+	 */
+	missingOptionalMetrics:
+		| InframonitoringtypesMissingMetricsComponentEntryDTO[]
+		| null;
+	/**
+	 * @type array,null
+	 */
+	missingRequiredAttributes:
+		| InframonitoringtypesMissingAttributesComponentEntryDTO[]
+		| null;
+	/**
+	 * @type array,null
+	 */
+	presentDefaultEnabledMetrics:
+		| InframonitoringtypesMetricsComponentEntryDTO[]
+		| null;
+	/**
+	 * @type array,null
+	 */
+	presentOptionalMetrics: InframonitoringtypesMetricsComponentEntryDTO[] | null;
+	/**
+	 * @type array,null
+	 */
+	presentRequiredAttributes:
+		| InframonitoringtypesAttributesComponentEntryDTO[]
+		| null;
+	/**
+	 * @type boolean
+	 */
+	ready: boolean;
+	type: InframonitoringtypesCheckTypeDTO;
+}
+
 export type InframonitoringtypesClusterRecordDTOMetaAnyOf = {
 	[key: string]: string;
 };
@@ -5535,13 +5650,6 @@ export interface InframonitoringtypesClusterRecordDTO {
 	podCountsByPhase: InframonitoringtypesPodCountsByPhaseDTO;
 }
 
-export interface InframonitoringtypesRequiredMetricsCheckDTO {
-	/**
-	 * @type array,null
-	 */
-	missingMetrics: string[] | null;
-}
-
 export enum InframonitoringtypesResponseTypeDTO {
 	list = 'list',
 	grouped_list = 'grouped_list',
@@ -5577,7 +5685,6 @@ export interface InframonitoringtypesClustersDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesClusterRecordDTO[];
-	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -5655,7 +5762,6 @@ export interface InframonitoringtypesDaemonSetsDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesDaemonSetRecordDTO[];
-	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -5733,7 +5839,6 @@ export interface InframonitoringtypesDeploymentsDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesDeploymentRecordDTO[];
-	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -5819,7 +5924,6 @@ export interface InframonitoringtypesHostsDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesHostRecordDTO[];
-	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -5905,7 +6009,6 @@ export interface InframonitoringtypesJobsDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesJobRecordDTO[];
-	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -5955,7 +6058,6 @@ export interface InframonitoringtypesNamespacesDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesNamespaceRecordDTO[];
-	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -6022,7 +6124,6 @@ export interface InframonitoringtypesNodesDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesNodeRecordDTO[];
-	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -6106,7 +6207,6 @@ export interface InframonitoringtypesPodsDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesPodRecordDTO[];
-	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -6454,7 +6554,6 @@ export interface InframonitoringtypesStatefulSetsDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesStatefulSetRecordDTO[];
-	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -6523,7 +6622,6 @@ export interface InframonitoringtypesVolumesDTO {
 	 * @type array
 	 */
 	records: InframonitoringtypesVolumeRecordDTO[];
-	requiredMetricsCheck: InframonitoringtypesRequiredMetricsCheckDTO;
 	/**
 	 * @type integer
 	 */
@@ -10246,6 +10344,21 @@ export type Healthz503 = {
 	status: string;
 };
 
+export type GetChecksParams = {
+	/**
+	 * @description undefined
+	 */
+	type: InframonitoringtypesCheckTypeDTO;
+};
+
+export type GetChecks200 = {
+	data: InframonitoringtypesChecksDTO;
+	/**
+	 * @type string
+	 */
+	status: string;
+};
+
 export type ListClusters200 = {
 	data: InframonitoringtypesClustersDTO;
 	/**

frontend/src/components/ErrorInPlace/ErrorInPlace.tsx

@@ -21,6 +21,8 @@ interface ErrorInPlaceProps {
 	width?: string | number;
 	/** Custom content instead of ErrorContent */
 	children?: ReactNode;
+	/** Test ID for testing */
+	'data-testid'?: string;
 }
 
 /**
@@ -44,6 +46,7 @@ function ErrorInPlace({
 	height = '100%',
 	width = '100%',
 	children,
+	'data-testid': dataTestId,
 }: ErrorInPlaceProps): JSX.Element {
 	const containerStyle: React.CSSProperties = {
 		display: 'flex',
@@ -59,7 +62,11 @@ function ErrorInPlace({
 	};
 
 	return (
-		<div className={`error-in-place ${className}`.trim()} style={containerStyle}>
+		<div
+			className={`error-in-place ${className}`.trim()}
+			style={containerStyle}
+			data-testid={dataTestId}
+		>
 			{children || <ErrorContent error={error} />}
 		</div>
 	);

frontend/src/components/MessagingQueueHealthCheck/AttributeCheckList.tsx

@@ -62,13 +62,13 @@ function ErrorTitleAndKey({
 
 		switch (parentTitle) {
 			case 'Consumers':
-				link = `${ROUTES.GET_STARTED_APPLICATION_MONITORING}?${QueryParams.getStartedSource}=kafka&${QueryParams.getStartedSourceService}=${MessagingQueueHealthCheckService.Consumers}`;
+				link = `${ROUTES.GET_STARTED_WITH_CLOUD}?${QueryParams.getStartedSource}=self-hosted-kafka&${QueryParams.getStartedSourceService}=${MessagingQueueHealthCheckService.Consumers}`;
 				break;
 			case 'Producers':
-				link = `${ROUTES.GET_STARTED_APPLICATION_MONITORING}?${QueryParams.getStartedSource}=kafka&${QueryParams.getStartedSourceService}=${MessagingQueueHealthCheckService.Producers}`;
+				link = `${ROUTES.GET_STARTED_WITH_CLOUD}?${QueryParams.getStartedSource}=self-hosted-kafka&${QueryParams.getStartedSourceService}=${MessagingQueueHealthCheckService.Producers}`;
 				break;
 			case 'Kafka':
-				link = `${ROUTES.GET_STARTED_INFRASTRUCTURE_MONITORING}?${QueryParams.getStartedSource}=kafka&${QueryParams.getStartedSourceService}=${MessagingQueueHealthCheckService.Kafka}`;
+				link = `${ROUTES.GET_STARTED_WITH_CLOUD}?${QueryParams.getStartedSource}=self-hosted-kafka&${QueryParams.getStartedSourceService}=${MessagingQueueHealthCheckService.Kafka}`;
 				break;
 			default:
 				link = '';

frontend/src/components/PermissionDeniedFullPage/PermissionDeniedFullPage.test.tsx

@@ -5,13 +5,9 @@ describe('PermissionDeniedFullPage', () => {
 	it('renders the title and subtitle with the permissionName interpolated', () => {
 		render(<PermissionDeniedFullPage permissionName="serviceaccount:list" />);
 
-		expect(
-			screen.getByText("Uh-oh! You don't have permission to view this page."),
-		).toBeInTheDocument();
+		expect(screen.getByText('Uh-oh! You are not authorized')).toBeInTheDocument();
 		expect(screen.getByText(/serviceaccount:list/)).toBeInTheDocument();
-		expect(
-			screen.getByText(/Please ask your SigNoz administrator to grant access/),
-		).toBeInTheDocument();
+		expect(screen.getByText(/is not authorized to perform/)).toBeInTheDocument();
 	});
 
 	it('renders with a different permissionName', () => {

frontend/src/components/PermissionDeniedFullPage/PermissionDeniedFullPage.tsx

@@ -2,6 +2,7 @@ import { CircleSlash2 } from '@signozhq/icons';
 
 import styles from './PermissionDeniedFullPage.module.scss';
 import { Style } from '@signozhq/design-tokens';
+import { useAppContext } from 'providers/App/App';
 
 interface PermissionDeniedFullPageProps {
 	permissionName: string;
@@ -10,18 +11,18 @@ interface PermissionDeniedFullPageProps {
 function PermissionDeniedFullPage({
 	permissionName,
 }: PermissionDeniedFullPageProps): JSX.Element {
+	const { user } = useAppContext();
+
 	return (
 		<div className={styles.container}>
 			<div className={styles.content}>
 				<span className={styles.icon}>
 					<CircleSlash2 color={Style.CALLOUT_WARNING_TITLE} size={14} />
 				</span>
-				<p className={styles.title}>
-					Uh-oh! You don&apos;t have permission to view this page.
-				</p>
+				<p className={styles.title}>Uh-oh! You are not authorized</p>
 				<p className={styles.subtitle}>
-					You need <code className={styles.permission}>{permissionName}</code> to
-					view this page. Please ask your SigNoz administrator to grant access.
+					<code className={styles.permission}>user/{user.id}</code> is not authorized
+					to perform <code className={styles.permission}>{permissionName}</code>
 				</p>
 			</div>
 		</div>

frontend/src/components/ServiceAccountDrawer/OverviewTab.tsx

@@ -1,7 +1,9 @@
-import { useCallback } from 'react';
-import { LockKeyhole } from '@signozhq/icons';
+import { useCallback, useEffect, useState } from 'react';
+import { Check, Copy, LockKeyhole } from '@signozhq/icons';
 import { Badge } from '@signozhq/ui/badge';
+import { Button } from '@signozhq/ui/button';
 import { Input } from '@signozhq/ui/input';
+import { useCopyToClipboard } from 'react-use';
 import type { AuthtypesRoleDTO } from 'api/generated/services/sigNoz.schemas';
 import AuthZTooltip from 'components/AuthZTooltip/AuthZTooltip';
 import RolesSelect from 'components/RolesSelect';
@@ -46,6 +48,23 @@ function OverviewTab({
 	saveErrors = [],
 }: OverviewTabProps): JSX.Element {
 	const { formatTimezoneAdjustedTimestamp } = useTimezone();
+	const [, copyToClipboard] = useCopyToClipboard();
+	const [hasCopiedId, setHasCopiedId] = useState(false);
+
+	const handleCopyId = useCallback((): void => {
+		if (account.id) {
+			copyToClipboard(account.id);
+			setHasCopiedId(true);
+		}
+	}, [account.id, copyToClipboard]);
+
+	useEffect(() => {
+		if (hasCopiedId) {
+			const timer = setTimeout(() => setHasCopiedId(false), 2000);
+			return (): void => clearTimeout(timer);
+		}
+		return undefined;
+	}, [hasCopiedId]);
 
 	const formatTimestamp = useCallback(
 		(ts: string | null | undefined): string => {
@@ -93,6 +112,17 @@ function OverviewTab({
 				</label>
 				<div className="sa-drawer__input-wrapper sa-drawer__input-wrapper--disabled">
 					<span className="sa-drawer__input-text">{account.id || '—'}</span>
+					{account.id && (
+						<Button
+							variant="link"
+							color="secondary"
+							onClick={handleCopyId}
+							className="sa-drawer__copy-btn"
+							data-testid="copy-id-btn"
+						>
+							{hasCopiedId ? <Check size={14} /> : <Copy size={14} />}
+						</Button>
+					)}
 					<LockKeyhole size={14} className="sa-drawer__lock-icon" />
 				</div>
 			</div>

frontend/src/components/ServiceAccountDrawer/ServiceAccountDrawer.styles.scss

@@ -203,6 +203,19 @@
 		opacity: 0.6;
 	}
 
+	&__copy-btn {
+		flex-shrink: 0;
+		padding: 0;
+		height: auto;
+		min-height: auto;
+		color: var(--foreground);
+		opacity: 0.6;
+
+		&:hover {
+			opacity: 1;
+		}
+	}
+
 	&__disabled-roles {
 		display: flex;
 		flex-wrap: wrap;

frontend/src/components/ServiceAccountDrawer/ServiceAccountDrawer.tsx

@@ -16,7 +16,6 @@ import {
 import type { RenderErrorResponseDTO } from 'api/generated/services/sigNoz.schemas';
 import { AxiosError } from 'axios';
 import ErrorInPlace from 'components/ErrorInPlace/ErrorInPlace';
-import { GuardAuthZ } from 'components/GuardAuthZ/GuardAuthZ';
 import PermissionDeniedCallout from 'components/PermissionDeniedCallout/PermissionDeniedCallout';
 import { useRoles } from 'components/RolesSelect';
 import { SA_QUERY_PARAMS } from 'container/ServiceAccountsSettings/constants';
@@ -477,15 +476,9 @@ function ServiceAccountDrawer({
 					!isAccountLoading &&
 					!isAccountError &&
 					selectedAccountId && (
-						<GuardAuthZ
-							relation="read"
-							object={`serviceaccount:${selectedAccountId}`}
-							fallbackOnNoPermissions={(): JSX.Element => (
-								<PermissionDeniedCallout permissionName="serviceaccount:read" />
-							)}
-						>
-							<>
-								{activeTab === ServiceAccountDrawerTab.Overview && account && (
+						<>
+							{activeTab === ServiceAccountDrawerTab.Overview &&
+								(canRead && account ? (
 									<OverviewTab
 										account={account}
 										localName={localName}
@@ -504,23 +497,24 @@ function ServiceAccountDrawer({
 										onRefetchRoles={refetchRoles}
 										saveErrors={saveErrors}
 									/>
-								)}
-								{activeTab === ServiceAccountDrawerTab.Keys &&
-									(canListKeys ? (
-										<KeysTab
-											keys={keys}
-											isLoading={keysLoading}
-											isDisabled={isDeleted}
-											canUpdate={canUpdate}
-											accountId={selectedAccountId}
-											currentPage={keysPage}
-											pageSize={PAGE_SIZE}
-										/>
-									) : (
-										<PermissionDeniedCallout permissionName="factor-api-key:list" />
-									))}
-							</>
-						</GuardAuthZ>
+								) : (
+									<PermissionDeniedCallout permissionName="serviceaccount:read" />
+								))}
+							{activeTab === ServiceAccountDrawerTab.Keys &&
+								(canListKeys ? (
+									<KeysTab
+										keys={keys}
+										isLoading={keysLoading}
+										isDisabled={isDeleted}
+										canUpdate={canUpdate}
+										accountId={selectedAccountId}
+										currentPage={keysPage}
+										pageSize={PAGE_SIZE}
+									/>
+								) : (
+									<PermissionDeniedCallout permissionName="factor-api-key:list" />
+								))}
+						</>
 					)}
 			</div>
 		</div>

frontend/src/components/SpanHoverCard/__tests__/SpanHoverCard.test.tsx

@@ -22,6 +22,7 @@ jest.mock('providers/Timezone', () => ({
 		},
 		updateTimezone: jest.fn(),
 		formatTimezoneAdjustedTimestamp: jest.fn(() => 'mock-date'),
+		formatTimezoneAdjustedTimestampOptional: jest.fn(() => 'mock-date'),
 		isAdaptationEnabled: true,
 		setIsAdaptationEnabled: jest.fn(),
 	}),

frontend/src/constants/features.ts

@@ -7,7 +7,6 @@ export enum FeatureKeys {
 	GATEWAY = 'gateway',
 	PREMIUM_SUPPORT = 'premium_support',
 	ANOMALY_DETECTION = 'anomaly_detection',
-	ONBOARDING_V3 = 'onboarding_v3',
 	DOT_METRICS_ENABLED = 'dot_metrics_enabled',
 	USE_JSON_BODY = 'use_json_body',
 	USE_FINE_GRAINED_AUTHZ = 'use_fine_grained_authz',

frontend/src/constants/routes.ts

@@ -11,14 +11,7 @@ const ROUTES = {
 	TRACE_DETAIL_OLD: '/trace-old/:id',
 	TRACES_EXPLORER: '/traces-explorer',
 	ONBOARDING: '/onboarding',
-	GET_STARTED: '/get-started',
 	GET_STARTED_WITH_CLOUD: '/get-started-with-signoz-cloud',
-	GET_STARTED_APPLICATION_MONITORING: '/get-started/application-monitoring',
-	GET_STARTED_LOGS_MANAGEMENT: '/get-started/logs-management',
-	GET_STARTED_INFRASTRUCTURE_MONITORING:
-		'/get-started/infrastructure-monitoring',
-	GET_STARTED_AWS_MONITORING: '/get-started/aws-monitoring',
-	GET_STARTED_AZURE_MONITORING: '/get-started/azure-monitoring',
 	USAGE_EXPLORER: '/usage-explorer',
 	APPLICATION: '/services',
 	ALL_DASHBOARD: '/dashboard',
@@ -56,7 +49,9 @@ const ROUTES = {
 	TRACE_EXPLORER: '/trace-explorer',
 	BILLING: '/settings/billing',
 	ROLES_SETTINGS: '/settings/roles',
+	ROLE_CREATE: '/settings/roles/new',
 	ROLE_DETAILS: '/settings/roles/:roleId',
+	ROLE_EDIT: '/settings/roles/:roleId/edit',
 	MEMBERS_SETTINGS: '/settings/members',
 	SUPPORT: '/support',
 	LOGS_SAVE_VIEWS: '/logs/saved-views',

frontend/src/container/AppLayout/index.tsx

@@ -413,14 +413,8 @@ function AppLayout(props: AppLayoutProps): JSX.Element {
 	const isPanelEditorV2 = routeKey === 'DASHBOARD_PANEL_EDITOR';
 
 	const renderFullScreen =
-		pathname === ROUTES.GET_STARTED ||
 		pathname === ROUTES.ONBOARDING ||
 		pathname === ROUTES.GET_STARTED_WITH_CLOUD ||
-		pathname === ROUTES.GET_STARTED_APPLICATION_MONITORING ||
-		pathname === ROUTES.GET_STARTED_INFRASTRUCTURE_MONITORING ||
-		pathname === ROUTES.GET_STARTED_LOGS_MANAGEMENT ||
-		pathname === ROUTES.GET_STARTED_AWS_MONITORING ||
-		pathname === ROUTES.GET_STARTED_AZURE_MONITORING ||
 		isPublicDashboard ||
 		isPanelEditorV2;
 

frontend/src/container/FullScreenHeader/FullScreenHeader.styles.scss

@@ -1,29 +0,0 @@
-.full-screen-header-container {
-	display: flex;
-	justify-content: center;
-	align-items: center;
-	padding: 24px 0;
-
-	.brand-logo {
-		display: flex;
-		justify-content: center;
-		align-items: center;
-		gap: 16px;
-		cursor: pointer;
-
-		img {
-			height: 32px;
-			width: 32px;
-		}
-
-		.brand-logo-name {
-			font-family: 'Work Sans', sans-serif;
-			font-size: 24px;
-			font-style: normal;
-			font-weight: 500;
-			line-height: 18px;
-
-			color: var(--l1-foreground);
-		}
-	}
-}

frontend/src/container/FullScreenHeader/FullScreenHeader.tsx

@@ -1,28 +0,0 @@
-import history from 'lib/history';
-
-import signozBrandLogoUrl from '@/assets/Logos/signoz-brand-logo.svg';
-
-import './FullScreenHeader.styles.scss';
-
-export default function FullScreenHeader({
-	overrideRoute,
-}: {
-	overrideRoute?: string;
-}): React.ReactElement {
-	const handleLogoClick = (): void => {
-		history.push(overrideRoute || '/');
-	};
-	return (
-		<div className="full-screen-header-container">
-			<div className="brand-logo" onClick={handleLogoClick}>
-				<img src={signozBrandLogoUrl} alt="SigNoz" />
-
-				<div className="brand-logo-name">SigNoz</div>
-			</div>
-		</div>
-	);
-}
-
-FullScreenHeader.defaultProps = {
-	overrideRoute: '/',
-};

frontend/src/container/MembersSettings/MembersSettings.styles.scss

@@ -1,10 +1,12 @@
-.members-settings {
+.members-settings-page {
 	display: flex;
 	flex-direction: column;
 	gap: var(--spacing-8);
 	padding: var(--padding-4) var(--padding-2) var(--padding-6) var(--padding-4);
 	height: 100%;
+}
 
+.members-settings {
 	&__header {
 		display: flex;
 		flex-direction: column;

frontend/src/container/MembersSettings/MembersSettings.tsx

@@ -160,7 +160,7 @@ function MembersSettings(): JSX.Element {
 	}, [refetchUsers]);
 
 	return (
-		<>
+		<div className="members-settings-page">
 			<div className="members-settings">
 				<div className="members-settings__header">
 					<h1 className="members-settings__title">Members</h1>
@@ -231,7 +231,7 @@ function MembersSettings(): JSX.Element {
 				onClose={handleDrawerClose}
 				onComplete={handleMemberEditComplete}
 			/>
-		</>
+		</div>
 	);
 }
 

frontend/src/container/NoLogs/NoLogs.tsx

@@ -33,15 +33,7 @@ export default function NoLogs({
 			} else if (dataSource === DataSource.METRICS) {
 				logEvent('Metrics Explorer: Navigate to onboarding', {});
 			}
-			let link;
-			if (dataSource === DataSource.TRACES) {
-				link = ROUTES.GET_STARTED_APPLICATION_MONITORING;
-			} else if (dataSource === DataSource.METRICS) {
-				link = ROUTES.GET_STARTED_WITH_CLOUD;
-			} else {
-				link = ROUTES.GET_STARTED_LOGS_MANAGEMENT;
-			}
-			history.push(link);
+			history.push(ROUTES.GET_STARTED_WITH_CLOUD);
 		} else if (dataSource === 'traces') {
 			openInNewTab(DOCLINKS.TRACES_EXPLORER_EMPTY_STATE);
 		} else if (dataSource === DataSource.METRICS) {

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/Docker/QuickStart/dotnet-docker-quickStart-instrumentApplication.md

@@ -1,106 +0,0 @@
-
-### Step 1: Install OpenTelemetry Dependencies
-Dependencies related to OpenTelemetry exporter and SDK have to be installed first.
-
-Run the below commands after navigating to the application source folder:
-```bash
-dotnet add package OpenTelemetry
-dotnet add package OpenTelemetry.Exporter.OpenTelemetryProtocol 
-dotnet add package OpenTelemetry.Extensions.Hosting
-dotnet add package OpenTelemetry.Instrumentation.Runtime
-dotnet add package OpenTelemetry.Instrumentation.AspNetCore 
-dotnet add package OpenTelemetry.AutoInstrumentation
-```
-
- 
-
-### Step 2:  Adding OpenTelemetry as a service and configuring exporter options
-
-In your `Program.cs` file, add OpenTelemetry as a service. Here, we are configuring these variables:
-
-`serviceName` - It is the name of your service.
-
-`otlpOptions.Endpoint` - It is the endpoint for your OTel Collector agent.
-
- 
-
-Here’s a sample `Program.cs` file with the configured variables:
-
-```bash
-using System.Diagnostics;
-using OpenTelemetry.Exporter;
-using OpenTelemetry.Resources;
-using OpenTelemetry.Trace;
-
-var builder = WebApplication.CreateBuilder(args);
-
-// Configure OpenTelemetry with tracing and auto-start.
-builder.Services.AddOpenTelemetry()
-    .ConfigureResource(resource => 
-        resource.AddService(serviceName: "{{MYAPP}}"))
-    .WithTracing(tracing => tracing
-        .AddAspNetCoreInstrumentation()
-        .AddOtlpExporter(otlpOptions =>
-        {
-                        //sigNoz Cloud Endpoint 
-            otlpOptions.Endpoint = new Uri("https://ingest.{{REGION}}.signoz.cloud:443");
-
-            otlpOptions.Protocol = OtlpExportProtocol.Grpc;
-                        
-                        //SigNoz Cloud account Ingestion key
-            string headerKey = "signoz-ingestion-key";
-            string headerValue = "{{SIGNOZ_INGESTION_KEY}}";
-
-            string formattedHeader = $"{headerKey}={headerValue}";
-            otlpOptions.Headers = formattedHeader;
-        }));
-
-var app = builder.Build();
-
-//The index route ("/") is set up to write out the OpenTelemetry trace information on the response:
-app.MapGet("/", () => $"Hello World! OpenTelemetry Trace: {Activity.Current?.Id}");
-
-app.Run();
-```
-
- 
-
-
-The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, we’re configuring it to send traces to the OTel Collector agent. The target must be a valid Uri with the scheme (http or https) and host and may contain a port and a path.
-
-This is done by configuring an OpenTelemetry [TracerProvider](https://github.com/open-telemetry/opentelemetry-dotnet/tree/main/docs/trace/customizing-the-sdk#readme) using extension methods and setting it to auto-start when the host is started.
-
-
-### Step 3: Dockerize your application
-
-Since the environment variables like SIGNOZ_INGESTION_KEY, Ingestion Endpoint and Service name are set in the `program.cs` file, you don't need to add any additional steps in your Dockerfile.
-
-An **example** of a Dockerfile could look like this:
-
-```bash
-
-# Use the Microsoft official .NET SDK image to build the application
-FROM mcr.microsoft.com/dotnet/sdk:8.0 AS build-env
-WORKDIR /app
-
-# Copy the CSPROJ file and restore any dependencies (via NUGET)
-COPY *.csproj ./
-RUN dotnet restore
-
-# Copy the rest of the project files and build the application
-COPY . ./
-RUN dotnet publish -c Release -o out
-
-# Generate the runtime image
-FROM mcr.microsoft.com/dotnet/aspnet:8.0
-WORKDIR /app
-COPY --from=build-env /app/out .
-
-# Expose port 5145 for the application
-EXPOSE 5145
-
-# Set the ASPNETCORE_URLS environment variable to listen on port 5145
-ENV ASPNETCORE_URLS=http://+:5145
-
-ENTRYPOINT ["dotnet", "YOUR-APPLICATION.dll"]
-```

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/Docker/QuickStart/dotnet-docker-quickStart-runApplication.md

@@ -1,21 +0,0 @@
-Once you update your Dockerfile, you can build and run it using the commands below.
-
- 
-
-### Step 1: Build your dockerfile
-
-Build your docker image
-
-```bash
-docker build -t <your-image-name> .
-```
-
-- `<your-image-name>` is the name of your Docker Image
-
-&nbsp;
-
-### Step 2: Run your docker image
-
-```bash
-docker run <your-image-name>
-```

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/Docker/Recommended/dotnet-docker-recommended-installOtelCollector.md

@@ -1,12 +0,0 @@
-## Setup OpenTelemetry Binary as an agent
-
- 
-
-As a first step, you should install the OTel collector Binary according to the instructions provided on [this link](https://signoz.io/docs/tutorial/opentelemetry-binary-usage-in-virtual-machine/).
-
- 
-
-Once you are done setting up the OTel collector binary, you can follow the next steps.
-
- 
-

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/Docker/Recommended/dotnet-docker-recommended-instrumentApplication.md

@@ -1,101 +0,0 @@
-After setting up the Otel collector agent, follow the steps below to instrument your .NET Application
-
- 
- 
-
-### Step 1: Install OpenTelemetry Dependencies
-Install the following dependencies in your application.
-
-```bash
-dotnet add package OpenTelemetry
-dotnet add package OpenTelemetry.Exporter.OpenTelemetryProtocol 
-dotnet add package OpenTelemetry.Extensions.Hosting
-dotnet add package OpenTelemetry.Instrumentation.Runtime
-dotnet add package OpenTelemetry.Instrumentation.AspNetCore 
-dotnet add package OpenTelemetry.AutoInstrumentation
-```
-
- 
-
-### Step 2:  Adding OpenTelemetry as a service and configuring exporter options
-
-In your `Program.cs` file, add OpenTelemetry as a service. Here, we are configuring these variables:
-
-`serviceName` - It is the name of your service.
-
-`otlpOptions.Endpoint` - It is the endpoint for your OTel Collector agent.
-
- 
-
-Here’s a sample `Program.cs` file with the configured variables:
-
-```bash
-using System.Diagnostics;
-using OpenTelemetry.Exporter;
-using OpenTelemetry.Resources;
-using OpenTelemetry.Trace;
-
-var builder = WebApplication.CreateBuilder(args);
-
-// Configure OpenTelemetry with tracing and auto-start.
-builder.Services.AddOpenTelemetry()
-    .ConfigureResource(resource => 
-        resource.AddService(serviceName: "{{MYAPP}}"))
-    .WithTracing(tracing => tracing
-        .AddAspNetCoreInstrumentation()
-        .AddOtlpExporter(otlpOptions =>
-        {
-            otlpOptions.Endpoint = new Uri("http://localhost:4317");
-
-            otlpOptions.Protocol = OtlpExportProtocol.Grpc;
-        }));
-
-var app = builder.Build();
-
-//The index route ("/") is set up to write out the OpenTelemetry trace information on the response:
-app.MapGet("/", () => $"Hello World! OpenTelemetry Trace: {Activity.Current?.Id}");
-
-app.Run();
-```
- 
-
-The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, we’re configuring it to send traces to the OTel Collector agent. The target must be a valid Uri with the scheme (http or https) and host and may contain a port and a path.
-
-This is done by configuring an OpenTelemetry [TracerProvider](https://github.com/open-telemetry/opentelemetry-dotnet/tree/main/docs/trace/customizing-the-sdk#readme) using extension methods and setting it to auto-start when the host is started.
-
-
- 
-
-### Step 3: Dockerize your application
-
-Since the crucial environment variables like SIGNOZ_INGESTION_KEY, Ingestion Endpoint and Service name are set in the `program.cs` file, you don't need to add any additional steps in your Dockerfile.
-
-An **example** of a Dockerfile could look like this:
-
-```bash
-
-# Use the Microsoft official .NET SDK image to build the application
-FROM mcr.microsoft.com/dotnet/sdk:8.0 AS build-env
-WORKDIR /app
-
-# Copy the CSPROJ file and restore any dependencies (via NUGET)
-COPY *.csproj ./
-RUN dotnet restore
-
-# Copy the rest of the project files and build the application
-COPY . ./
-RUN dotnet publish -c Release -o out
-
-# Generate the runtime image
-FROM mcr.microsoft.com/dotnet/aspnet:8.0
-WORKDIR /app
-COPY --from=build-env /app/out .
-
-# Expose port 5145 for the application
-EXPOSE 5145
-
-# Set the ASPNETCORE_URLS environment variable to listen on port 5145
-ENV ASPNETCORE_URLS=http://+:5145
-
-ENTRYPOINT ["dotnet", "YOUR-APPLICATION.dll"]
-```

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/Docker/Recommended/dotnet-docker-recommended-runApplication.md

@@ -1,21 +0,0 @@
-Once you update your Dockerfile, you can build and run it using the commands below.
-
- 
-
-### Step 1: Build your dockerfile
-
-Build your docker image
-
-```bash
-docker build -t <your-image-name> .
-```
-
-- `<your-image-name>` is the name of your Docker Image
-
-&nbsp;
-
-### Step 2: Run your docker image
-
-```bash
-docker run <your-image-name>
-```

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/Kubernetes/dotnet-kubernetes-installOtelCollector.md

@@ -1,43 +0,0 @@
-### Install otel-collector in your Kubernetes infra
-
-Add the SigNoz Helm Chart repository
-```bash
-helm repo add signoz https://charts.signoz.io
-```
-
- 
-
-If the chart is already present, update the chart to the latest using:
-```bash
-helm repo update
-```
-
- 
-
-For generic Kubernetes clusters, you can create *override-values.yaml* with the following configuration:
-
-```yaml
-global:
-  cloud: others
-  clusterName: <CLUSTER_NAME>
-  deploymentEnvironment: <DEPLOYMENT_ENVIRONMENT>
-otelCollectorEndpoint: ingest.{{REGION}}.signoz.cloud:443
-otelInsecure: false
-signozApiKey: {{SIGNOZ_INGESTION_KEY}}
-presets:
-  otlpExporter:
-    enabled: true
-  loggingExporter:
-    enabled: false
-```
-
-- Replace `<CLUSTER_NAME>` with the name of the Kubernetes cluster or a unique identifier of the cluster.
-- Replace `<DEPLOYMENT_ENVIRONMENT>` with the deployment environment of your application. Example: **"staging"**, **"production"**, etc.
-
-&nbsp;
-
-To install the k8s-infra chart with the above configuration, run the following command:
-
-```bash
-helm install my-release signoz/k8s-infra -f override-values.yaml
-```

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/Kubernetes/dotnet-kubernetes-instrumentApplication.md

@@ -1,65 +0,0 @@
-After setting up the Otel collector agent, follow the steps below to instrument your .NET Application
- 
- 
-
-### Step 1: Install OpenTelemetry Dependencies
-Install the following dependencies in your application.
-
-```bash
-dotnet add package OpenTelemetry
-dotnet add package OpenTelemetry.Exporter.OpenTelemetryProtocol 
-dotnet add package OpenTelemetry.Extensions.Hosting
-dotnet add package OpenTelemetry.Instrumentation.Runtime
-dotnet add package OpenTelemetry.Instrumentation.AspNetCore 
-dotnet add package OpenTelemetry.AutoInstrumentation
-```
-
- 
-
-### Step 2:  Adding OpenTelemetry as a service and configuring exporter options
-
-In your `Program.cs` file, add OpenTelemetry as a service. Here, we are configuring these variables:
-
-`serviceName` - It is the name of your service.
-
-`otlpOptions.Endpoint` - It is the endpoint for your OTel Collector agent.
-
- 
-
-Here’s a sample `Program.cs` file with the configured variables:
-
-```bash
-using System.Diagnostics;
-using OpenTelemetry.Exporter;
-using OpenTelemetry.Resources;
-using OpenTelemetry.Trace;
-
-var builder = WebApplication.CreateBuilder(args);
-
-// Configure OpenTelemetry with tracing and auto-start.
-builder.Services.AddOpenTelemetry()
-    .ConfigureResource(resource => 
-        resource.AddService(serviceName: "{{MYAPP}}"))
-    .WithTracing(tracing => tracing
-        .AddAspNetCoreInstrumentation()
-        .AddOtlpExporter(otlpOptions =>
-        {
-            otlpOptions.Endpoint = new Uri("http://localhost:4317");
-
-            otlpOptions.Protocol = OtlpExportProtocol.Grpc;
-        }));
-
-var app = builder.Build();
-
-//The index route ("/") is set up to write out the OpenTelemetry trace information on the response:
-app.MapGet("/", () => $"Hello World! OpenTelemetry Trace: {Activity.Current?.Id}");
-
-app.Run();
-```
-
-The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, we’re configuring it to send traces to the OTel Collector agent. The target must be a valid Uri with the scheme (http or https) and host and may contain a port and a path.
-
-This is done by configuring an OpenTelemetry [TracerProvider](https://github.com/open-telemetry/opentelemetry-dotnet/tree/main/docs/trace/customizing-the-sdk#readme) using extension methods and setting it to auto-start when the host is started.
-
-
-

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/Kubernetes/dotnet-kubernetes-runApplication.md

@@ -1,10 +0,0 @@
- 
-
-To run your .NET application, use the below command :
-
-```bash
-dotnet build
-dotnet run
-```
-
-Once you run your .NET application, interact with your application to generate some load and see your application in the SigNoz UI.

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/LinuxAMD64/QuickStart/dotnet-linuxamd64-quickStart-instrumentApplication.md

@@ -1,71 +0,0 @@
-
-### Step 1: Install OpenTelemetry Dependencies
-Dependencies related to OpenTelemetry exporter and SDK have to be installed first.
-
-Run the below commands after navigating to the application source folder:
-```bash
-dotnet add package OpenTelemetry
-dotnet add package OpenTelemetry.Exporter.OpenTelemetryProtocol 
-dotnet add package OpenTelemetry.Extensions.Hosting
-dotnet add package OpenTelemetry.Instrumentation.Runtime
-dotnet add package OpenTelemetry.Instrumentation.AspNetCore 
-dotnet add package OpenTelemetry.AutoInstrumentation
-```
-
- 
-
-### Step 2:  Adding OpenTelemetry as a service and configuring exporter options
-
-In your `Program.cs` file, add OpenTelemetry as a service. Here, we are configuring these variables:
-
-`serviceName` - It is the name of your service.
-
-`otlpOptions.Endpoint` - It is the endpoint for your OTel Collector agent.
-
- 
-
-Here’s a sample `Program.cs` file with the configured variables:
-
-```bash
-using System.Diagnostics;
-using OpenTelemetry.Exporter;
-using OpenTelemetry.Resources;
-using OpenTelemetry.Trace;
-
-var builder = WebApplication.CreateBuilder(args);
-
-// Configure OpenTelemetry with tracing and auto-start.
-builder.Services.AddOpenTelemetry()
-    .ConfigureResource(resource => 
-        resource.AddService(serviceName: "{{MYAPP}}"))
-    .WithTracing(tracing => tracing
-        .AddAspNetCoreInstrumentation()
-        .AddOtlpExporter(otlpOptions =>
-        {
-                        //sigNoz Cloud Endpoint 
-            otlpOptions.Endpoint = new Uri("https://ingest.{{REGION}}.signoz.cloud:443");
-
-            otlpOptions.Protocol = OtlpExportProtocol.Grpc;
-                        
-                        //SigNoz Cloud account Ingestion key
-            string headerKey = "signoz-ingestion-key";
-            string headerValue = "{{SIGNOZ_INGESTION_KEY}}";
-
-            string formattedHeader = $"{headerKey}={headerValue}";
-            otlpOptions.Headers = formattedHeader;
-        }));
-
-var app = builder.Build();
-
-//The index route ("/") is set up to write out the OpenTelemetry trace information on the response:
-app.MapGet("/", () => $"Hello World! OpenTelemetry Trace: {Activity.Current?.Id}");
-
-app.Run();
-```
-
- 
-
-
-The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, we’re configuring it to send traces to the OTel Collector agent. The target must be a valid Uri with the scheme (http or https) and host and may contain a port and a path.
-
-This is done by configuring an OpenTelemetry [TracerProvider](https://github.com/open-telemetry/opentelemetry-dotnet/tree/main/docs/trace/customizing-the-sdk#readme) using extension methods and setting it to auto-start when the host is started.

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/LinuxAMD64/QuickStart/dotnet-linuxamd64-quickStart-runApplication.md

@@ -1,10 +0,0 @@
- 
-To run your .NET application, use the below command :
-
-```bash
-dotnet build
-dotnet run
-```
-
-Once you run your .NET application, interact with your application to generate some load and see your application in the SigNoz UI.
-

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/LinuxAMD64/Recommended/dotnet-linuxamd64-recommended-installOtelCollector.md

@@ -1,98 +0,0 @@
-## Setup OpenTelemetry Binary as an agent
- 
-
-### Step 1: Download otel-collector tar.gz
-```bash
-wget https://github.com/open-telemetry/opentelemetry-collector-releases/releases/download/v{{OTEL_VERSION}}/otelcol-contrib_{{OTEL_VERSION}}_linux_amd64.tar.gz
-```
-
- 
-
-### Step 2: Extract otel-collector tar.gz to the `otelcol-contrib` folder
-```bash
-mkdir otelcol-contrib && tar xvzf otelcol-contrib_{{OTEL_VERSION}}_linux_amd64.tar.gz -C otelcol-contrib
-```
-
- 
-
-### Step 3: Create `config.yaml` in `otelcol-contrib` folder with the below content in it
-```bash
-receivers:
-  otlp:
-    protocols:
-      grpc:
-        endpoint: 0.0.0.0:4317
-      http:
-        endpoint: 0.0.0.0:4318
-  hostmetrics:
-    collection_interval: 60s
-    scrapers:
-      cpu: {}
-      disk: {}
-      load: {}
-      filesystem: {}
-      memory: {}
-      network: {}
-      paging: {}
-      process:
-        mute_process_name_error: true
-        mute_process_exe_error: true
-        mute_process_io_error: true
-      processes: {}
-  prometheus:
-    config:
-      global:
-        scrape_interval: 60s
-      scrape_configs:
-        - job_name: otel-collector-binary
-          static_configs:
-            - targets:
-              # - localhost:8888
-processors:
-  batch:
-    send_batch_size: 1000
-    timeout: 10s
-  # Ref: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/processor/resourcedetectionprocessor/README.md
-  resourcedetection:
-    detectors: [env, system] # Before system detector, include ec2 for AWS, gcp for GCP and azure for Azure.
-    # Using OTEL_RESOURCE_ATTRIBUTES envvar, env detector adds custom labels.
-    timeout: 2s
-    system:
-      hostname_sources: [os] # alternatively, use [dns,os] for setting FQDN as host.name and os as fallback
-extensions:
-  health_check: {}
-  zpages: {}
-exporters:
-  otlp:
-    endpoint: "ingest.{{REGION}}.signoz.cloud:443"
-    tls:
-      insecure: false
-    headers:
-      "signoz-ingestion-key": "{{SIGNOZ_INGESTION_KEY}}"
-  logging:
-    verbosity: normal
-service:
-  telemetry:
-    metrics:
-      address: 0.0.0.0:8888
-  extensions: [health_check, zpages]
-  pipelines:
-    metrics:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    metrics/internal:
-      receivers: [prometheus, hostmetrics]
-      processors: [resourcedetection, batch]
-      exporters: [otlp]
-    traces:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    logs:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-```
-
-

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/LinuxAMD64/Recommended/dotnet-linuxamd64-recommended-instrumentApplication.md

@@ -1,67 +0,0 @@
-After setting up the Otel collector agent, follow the steps below to instrument your .NET Application
-
- 
- 
-
-### Step 1: Install OpenTelemetry Dependencies
-Install the following dependencies in your application.
-
-```bash
-dotnet add package OpenTelemetry
-dotnet add package OpenTelemetry.Exporter.OpenTelemetryProtocol 
-dotnet add package OpenTelemetry.Extensions.Hosting
-dotnet add package OpenTelemetry.Instrumentation.Runtime
-dotnet add package OpenTelemetry.Instrumentation.AspNetCore 
-dotnet add package OpenTelemetry.AutoInstrumentation
-```
-
- 
-
-### Step 2:  Adding OpenTelemetry as a service and configuring exporter options
-
-In your `Program.cs` file, add OpenTelemetry as a service. Here, we are configuring these variables:
-
-`serviceName` - It is the name of your service.
-
-`otlpOptions.Endpoint` - It is the endpoint for your OTel Collector agent.
-
- 
-
-Here’s a sample `Program.cs` file with the configured variables:
-
-```bash
-using System.Diagnostics;
-using OpenTelemetry.Exporter;
-using OpenTelemetry.Resources;
-using OpenTelemetry.Trace;
-
-var builder = WebApplication.CreateBuilder(args);
-
-// Configure OpenTelemetry with tracing and auto-start.
-builder.Services.AddOpenTelemetry()
-    .ConfigureResource(resource => 
-        resource.AddService(serviceName: "{{MYAPP}}"))
-    .WithTracing(tracing => tracing
-        .AddAspNetCoreInstrumentation()
-        .AddOtlpExporter(otlpOptions =>
-        {
-            otlpOptions.Endpoint = new Uri("http://localhost:4317");
-
-            otlpOptions.Protocol = OtlpExportProtocol.Grpc;
-        }));
-
-var app = builder.Build();
-
-//The index route ("/") is set up to write out the OpenTelemetry trace information on the response:
-app.MapGet("/", () => $"Hello World! OpenTelemetry Trace: {Activity.Current?.Id}");
-
-app.Run();
-```
- 
-
-The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, we’re configuring it to send traces to the OTel Collector agent. The target must be a valid Uri with the scheme (http or https) and host and may contain a port and a path.
-
-This is done by configuring an OpenTelemetry [TracerProvider](https://github.com/open-telemetry/opentelemetry-dotnet/tree/main/docs/trace/customizing-the-sdk#readme) using extension methods and setting it to auto-start when the host is started.
-
-
-

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/LinuxAMD64/Recommended/dotnet-linuxamd64-recommended-runApplication.md

@@ -1,18 +0,0 @@
- 
-Once you are done intrumenting your .NET application, you can run it using the below commands
- 
-
-### Step 1: Run OTel Collector
- Run this command inside the `otelcol-contrib` directory that you created in the install Otel Collector step
-
-```bash
-./otelcol-contrib --config ./config.yaml
-```
-
- 
-
-### Step 2: Run your .NET application
-```bash
-dotnet build
-dotnet run
-```

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/LinuxARM64/QuickStart/dotnet-linuxarm64-quickStart-instrumentApplication.md

@@ -1,70 +0,0 @@
-
-### Step 1: Install OpenTelemetry Dependencies
-Dependencies related to OpenTelemetry exporter and SDK have to be installed first.
-
-Run the below commands after navigating to the application source folder:
-```bash
-dotnet add package OpenTelemetry
-dotnet add package OpenTelemetry.Exporter.OpenTelemetryProtocol 
-dotnet add package OpenTelemetry.Extensions.Hosting
-dotnet add package OpenTelemetry.Instrumentation.Runtime
-dotnet add package OpenTelemetry.Instrumentation.AspNetCore 
-dotnet add package OpenTelemetry.AutoInstrumentation
-```
-
- 
-
-### Step 2:  Adding OpenTelemetry as a service and configuring exporter options
-
-In your `Program.cs` file, add OpenTelemetry as a service. Here, we are configuring these variables:
-
-`serviceName` - It is the name of your service.
-
-`otlpOptions.Endpoint` - It is the endpoint for your OTel Collector agent.
-
- 
-
-Here’s a sample `Program.cs` file with the configured variables:
-
-```bash
-using System.Diagnostics;
-using OpenTelemetry.Exporter;
-using OpenTelemetry.Resources;
-using OpenTelemetry.Trace;
-
-var builder = WebApplication.CreateBuilder(args);
-
-// Configure OpenTelemetry with tracing and auto-start.
-builder.Services.AddOpenTelemetry()
-    .ConfigureResource(resource => 
-        resource.AddService(serviceName: "{{MYAPP}}"))
-    .WithTracing(tracing => tracing
-        .AddAspNetCoreInstrumentation()
-        .AddOtlpExporter(otlpOptions =>
-        {
-                        //sigNoz Cloud Endpoint 
-            otlpOptions.Endpoint = new Uri("https://ingest.{{REGION}}.signoz.cloud:443");
-
-            otlpOptions.Protocol = OtlpExportProtocol.Grpc;
-                        
-                        //SigNoz Cloud account Ingestion key
-            string headerKey = "signoz-ingestion-key";
-            string headerValue = "{{SIGNOZ_INGESTION_KEY}}";
-
-            string formattedHeader = $"{headerKey}={headerValue}";
-            otlpOptions.Headers = formattedHeader;
-        }));
-
-var app = builder.Build();
-
-//The index route ("/") is set up to write out the OpenTelemetry trace information on the response:
-app.MapGet("/", () => $"Hello World! OpenTelemetry Trace: {Activity.Current?.Id}");
-
-app.Run();
-```
-
- 
-
-The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, we’re configuring it to send traces to the OTel Collector agent. The target must be a valid Uri with the scheme (http or https) and host and may contain a port and a path.
-
-This is done by configuring an OpenTelemetry [TracerProvider](https://github.com/open-telemetry/opentelemetry-dotnet/tree/main/docs/trace/customizing-the-sdk#readme) using extension methods and setting it to auto-start when the host is started.

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/LinuxARM64/QuickStart/dotnet-linuxarm64-quickStart-runApplication.md

@@ -1,10 +0,0 @@
- 
-To run your .NET application, use the below command :
-
-```bash
-dotnet build
-dotnet run
-```
-
-Once you run your .NET application, interact with your application to generate some load and see your application in the SigNoz UI.
-

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/LinuxARM64/Recommended/dotnet-linuxarm64-recommended-installOtelCollector.md

@@ -1,99 +0,0 @@
-## Setup OpenTelemetry Binary as an agent
-
- 
-
-### Step 1: Download otel-collector tar.gz
-```bash
-wget https://github.com/open-telemetry/opentelemetry-collector-releases/releases/download/v{{OTEL_VERSION}}/otelcol-contrib_{{OTEL_VERSION}}_linux_arm64.tar.gz
-```
-
- 
-
-### Step 2: Extract otel-collector tar.gz to the `otelcol-contrib` folder
-```bash
-mkdir otelcol-contrib && tar xvzf otelcol-contrib_{{OTEL_VERSION}}_linux_arm64.tar.gz -C otelcol-contrib
-```
-
- 
-
-### Step 3: Create `config.yaml` in `otelcol-contrib` folder with the below content in it
-```bash
-receivers:
-  otlp:
-    protocols:
-      grpc:
-        endpoint: 0.0.0.0:4317
-      http:
-        endpoint: 0.0.0.0:4318
-  hostmetrics:
-    collection_interval: 60s
-    scrapers:
-      cpu: {}
-      disk: {}
-      load: {}
-      filesystem: {}
-      memory: {}
-      network: {}
-      paging: {}
-      process:
-        mute_process_name_error: true
-        mute_process_exe_error: true
-        mute_process_io_error: true
-      processes: {}
-  prometheus:
-    config:
-      global:
-        scrape_interval: 60s
-      scrape_configs:
-        - job_name: otel-collector-binary
-          static_configs:
-            - targets:
-              # - localhost:8888
-processors:
-  batch:
-    send_batch_size: 1000
-    timeout: 10s
-  # Ref: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/processor/resourcedetectionprocessor/README.md
-  resourcedetection:
-    detectors: [env, system] # Before system detector, include ec2 for AWS, gcp for GCP and azure for Azure.
-    # Using OTEL_RESOURCE_ATTRIBUTES envvar, env detector adds custom labels.
-    timeout: 2s
-    system:
-      hostname_sources: [os] # alternatively, use [dns,os] for setting FQDN as host.name and os as fallback
-extensions:
-  health_check: {}
-  zpages: {}
-exporters:
-  otlp:
-    endpoint: "ingest.{{REGION}}.signoz.cloud:443"
-    tls:
-      insecure: false
-    headers:
-      "signoz-ingestion-key": "{{SIGNOZ_INGESTION_KEY}}"
-  logging:
-    verbosity: normal
-service:
-  telemetry:
-    metrics:
-      address: 0.0.0.0:8888
-  extensions: [health_check, zpages]
-  pipelines:
-    metrics:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    metrics/internal:
-      receivers: [prometheus, hostmetrics]
-      processors: [resourcedetection, batch]
-      exporters: [otlp]
-    traces:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    logs:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-```
-
-

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/LinuxARM64/Recommended/dotnet-linuxarm64-recommended-instrumentApplication.md

@@ -1,68 +0,0 @@
-After setting up the Otel collector agent, follow the steps below to instrument your .NET Application
-
- 
- 
-
-### Step 1: Install OpenTelemetry Dependencies
-Install the following dependencies in your application.
-
-```bash
-dotnet add package OpenTelemetry
-dotnet add package OpenTelemetry.Exporter.OpenTelemetryProtocol 
-dotnet add package OpenTelemetry.Extensions.Hosting
-dotnet add package OpenTelemetry.Instrumentation.Runtime
-dotnet add package OpenTelemetry.Instrumentation.AspNetCore 
-dotnet add package OpenTelemetry.AutoInstrumentation
-```
-
- 
-
-### Step 2:  Adding OpenTelemetry as a service and configuring exporter options
-
-In your `Program.cs` file, add OpenTelemetry as a service. Here, we are configuring these variables:
-
-`serviceName` - It is the name of your service.
-
-`otlpOptions.Endpoint` - It is the endpoint for your OTel Collector agent.
-
- 
-
-Here’s a sample `Program.cs` file with the configured variables:
-
-```bash
-using System.Diagnostics;
-using OpenTelemetry.Exporter;
-using OpenTelemetry.Resources;
-using OpenTelemetry.Trace;
-
-var builder = WebApplication.CreateBuilder(args);
-
-// Configure OpenTelemetry with tracing and auto-start.
-builder.Services.AddOpenTelemetry()
-    .ConfigureResource(resource => 
-        resource.AddService(serviceName: "{{MYAPP}}"))
-    .WithTracing(tracing => tracing
-        .AddAspNetCoreInstrumentation()
-        .AddOtlpExporter(otlpOptions =>
-        {
-            otlpOptions.Endpoint = new Uri("http://localhost:4317");
-
-            otlpOptions.Protocol = OtlpExportProtocol.Grpc;
-        }));
-
-var app = builder.Build();
-
-//The index route ("/") is set up to write out the OpenTelemetry trace information on the response:
-app.MapGet("/", () => $"Hello World! OpenTelemetry Trace: {Activity.Current?.Id}");
-
-app.Run();
-```
-
- 
-
-The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, we’re configuring it to send traces to the OTel Collector agent. The target must be a valid Uri with the scheme (http or https) and host and may contain a port and a path.
-
-This is done by configuring an OpenTelemetry [TracerProvider](https://github.com/open-telemetry/opentelemetry-dotnet/tree/main/docs/trace/customizing-the-sdk#readme) using extension methods and setting it to auto-start when the host is started.
-
-
-

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/LinuxARM64/Recommended/dotnet-linuxarm64-recommended-runApplication.md

@@ -1,18 +0,0 @@
- 
-Once you are done intrumenting your .NET application, you can run it using the below commands
- 
-
-### Step 1: Run OTel Collector
- Run this command inside the `otelcol-contrib` directory that you created in the install Otel Collector step
-
-```bash
-./otelcol-contrib --config ./config.yaml
-```
-
- 
-
-### Step 2: Run your .NET application
-```bash
-dotnet build
-dotnet run
-```

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/MacOsAMD64/QuickStart/dotnet-macosamd64-quickStart-instrumentApplication.md

@@ -1,70 +0,0 @@
-
-### Step 1: Install OpenTelemetry Dependencies
-Dependencies related to OpenTelemetry exporter and SDK have to be installed first.
-
-Run the below commands after navigating to the application source folder:
-```bash
-dotnet add package OpenTelemetry
-dotnet add package OpenTelemetry.Exporter.OpenTelemetryProtocol 
-dotnet add package OpenTelemetry.Extensions.Hosting
-dotnet add package OpenTelemetry.Instrumentation.Runtime
-dotnet add package OpenTelemetry.Instrumentation.AspNetCore 
-dotnet add package OpenTelemetry.AutoInstrumentation
-```
-
- 
-
-### Step 2:  Adding OpenTelemetry as a service and configuring exporter options
-
-In your `Program.cs` file, add OpenTelemetry as a service. Here, we are configuring these variables:
-
-`serviceName` - It is the name of your service.
-
-`otlpOptions.Endpoint` - It is the endpoint for your OTel Collector agent.
-
- 
-
-Here’s a sample `Program.cs` file with the configured variables:
-
-```bash
-using System.Diagnostics;
-using OpenTelemetry.Exporter;
-using OpenTelemetry.Resources;
-using OpenTelemetry.Trace;
-
-var builder = WebApplication.CreateBuilder(args);
-
-// Configure OpenTelemetry with tracing and auto-start.
-builder.Services.AddOpenTelemetry()
-    .ConfigureResource(resource => 
-        resource.AddService(serviceName: "{{MYAPP}}"))
-    .WithTracing(tracing => tracing
-        .AddAspNetCoreInstrumentation()
-        .AddOtlpExporter(otlpOptions =>
-        {
-                        //sigNoz Cloud Endpoint 
-            otlpOptions.Endpoint = new Uri("https://ingest.{{REGION}}.signoz.cloud:443");
-
-            otlpOptions.Protocol = OtlpExportProtocol.Grpc;
-                        
-                        //SigNoz Cloud account Ingestion key
-            string headerKey = "signoz-ingestion-key";
-            string headerValue = "{{SIGNOZ_INGESTION_KEY}}";
-
-            string formattedHeader = $"{headerKey}={headerValue}";
-            otlpOptions.Headers = formattedHeader;
-        }));
-
-var app = builder.Build();
-
-//The index route ("/") is set up to write out the OpenTelemetry trace information on the response:
-app.MapGet("/", () => $"Hello World! OpenTelemetry Trace: {Activity.Current?.Id}");
-
-app.Run();
-```
-
- 
-
-The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, we’re configuring it to send traces to the OTel Collector agent. The target must be a valid Uri with the scheme (http or https) and host and may contain a port and a path.
-
-This is done by configuring an OpenTelemetry [TracerProvider](https://github.com/open-telemetry/opentelemetry-dotnet/tree/main/docs/trace/customizing-the-sdk#readme) using extension methods and setting it to auto-start when the host is started.

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/MacOsAMD64/QuickStart/dotnet-macosamd64-quickStart-runApplication.md

@@ -1,10 +0,0 @@
- 
-To run your .NET application, use the below command :
-
-```bash
-dotnet build
-dotnet run
-```
-
-Once you run your .NET application, interact with your application to generate some load and see your application in the SigNoz UI.
-

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/MacOsAMD64/Recommended/dotnet-macosamd64-recommended-installOtelCollector.md

@@ -1,97 +0,0 @@
-## Setup OpenTelemetry Binary as an agent
- 
-
-### Step 1: Download otel-collector tar.gz
-```bash
-wget https://github.com/open-telemetry/opentelemetry-collector-releases/releases/download/v{{OTEL_VERSION}}/otelcol-contrib_{{OTEL_VERSION}}_darwin_amd64.tar.gz
-```
- 
-
-### Step 2: Extract otel-collector tar.gz to the `otelcol-contrib` folder
-```bash
-mkdir otelcol-contrib && tar xvzf otelcol-contrib_{{OTEL_VERSION}}_darwin_amd64.tar.gz -C otelcol-contrib
-```
-
- 
-
-### Step 3: Create `config.yaml` in folder `otelcol-contrib` with the below content in it
-```bash
-receivers:
-  otlp:
-    protocols:
-      grpc:
-        endpoint: 0.0.0.0:4317
-      http:
-        endpoint: 0.0.0.0:4318
-  hostmetrics:
-    collection_interval: 60s
-    scrapers:
-      cpu: {}
-      disk: {}
-      load: {}
-      filesystem: {}
-      memory: {}
-      network: {}
-      paging: {}
-      process:
-        mute_process_name_error: true
-        mute_process_exe_error: true
-        mute_process_io_error: true
-      processes: {}
-  prometheus:
-    config:
-      global:
-        scrape_interval: 60s
-      scrape_configs:
-        - job_name: otel-collector-binary
-          static_configs:
-            - targets:
-              # - localhost:8888
-processors:
-  batch:
-    send_batch_size: 1000
-    timeout: 10s
-  # Ref: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/processor/resourcedetectionprocessor/README.md
-  resourcedetection:
-    detectors: [env, system] # Before system detector, include ec2 for AWS, gcp for GCP and azure for Azure.
-    # Using OTEL_RESOURCE_ATTRIBUTES envvar, env detector adds custom labels.
-    timeout: 2s
-    system:
-      hostname_sources: [os] # alternatively, use [dns,os] for setting FQDN as host.name and os as fallback
-extensions:
-  health_check: {}
-  zpages: {}
-exporters:
-  otlp:
-    endpoint: "ingest.{{REGION}}.signoz.cloud:443"
-    tls:
-      insecure: false
-    headers:
-      "signoz-ingestion-key": "{{SIGNOZ_INGESTION_KEY}}"
-  logging:
-    verbosity: normal
-service:
-  telemetry:
-    metrics:
-      address: 0.0.0.0:8888
-  extensions: [health_check, zpages]
-  pipelines:
-    metrics:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    metrics/internal:
-      receivers: [prometheus, hostmetrics]
-      processors: [resourcedetection, batch]
-      exporters: [otlp]
-    traces:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    logs:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-```
-
-

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/MacOsAMD64/Recommended/dotnet-macosamd64-recommended-instrumentApplication.md

@@ -1,67 +0,0 @@
-After setting up the Otel collector agent, follow the steps below to instrument your .NET Application
-
- 
- 
-
-### Step 1: Install OpenTelemetry Dependencies
-Install the following dependencies in your application.
-
-```bash
-dotnet add package OpenTelemetry
-dotnet add package OpenTelemetry.Exporter.OpenTelemetryProtocol 
-dotnet add package OpenTelemetry.Extensions.Hosting
-dotnet add package OpenTelemetry.Instrumentation.Runtime
-dotnet add package OpenTelemetry.Instrumentation.AspNetCore 
-dotnet add package OpenTelemetry.AutoInstrumentation
-```
-
- 
-
-### Step 2:  Adding OpenTelemetry as a service and configuring exporter options
-
-In your `Program.cs` file, add OpenTelemetry as a service. Here, we are configuring these variables:
-
-`serviceName` - It is the name of your service.
-
-`otlpOptions.Endpoint` - It is the endpoint for your OTel Collector agent.
-
- 
-
-Here’s a sample `Program.cs` file with the configured variables:
-
-```bash
-using System.Diagnostics;
-using OpenTelemetry.Exporter;
-using OpenTelemetry.Resources;
-using OpenTelemetry.Trace;
-
-var builder = WebApplication.CreateBuilder(args);
-
-// Configure OpenTelemetry with tracing and auto-start.
-builder.Services.AddOpenTelemetry()
-    .ConfigureResource(resource => 
-        resource.AddService(serviceName: "{{MYAPP}}"))
-    .WithTracing(tracing => tracing
-        .AddAspNetCoreInstrumentation()
-        .AddOtlpExporter(otlpOptions =>
-        {
-            otlpOptions.Endpoint = new Uri("http://localhost:4317");
-
-            otlpOptions.Protocol = OtlpExportProtocol.Grpc;
-        }));
-
-var app = builder.Build();
-
-//The index route ("/") is set up to write out the OpenTelemetry trace information on the response:
-app.MapGet("/", () => $"Hello World! OpenTelemetry Trace: {Activity.Current?.Id}");
-
-app.Run();
-```
- 
-
-The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, we’re configuring it to send traces to the OTel Collector agent. The target must be a valid Uri with the scheme (http or https) and host and may contain a port and a path.
-
-This is done by configuring an OpenTelemetry [TracerProvider](https://github.com/open-telemetry/opentelemetry-dotnet/tree/main/docs/trace/customizing-the-sdk#readme) using extension methods and setting it to auto-start when the host is started.
-
-
-

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/MacOsAMD64/Recommended/dotnet-macosamd64-recommended-runApplication.md

@@ -1,18 +0,0 @@
- 
-Once you are done intrumenting your .NET application, you can run it using the below commands
- 
-
-### Step 1: Run OTel Collector
- Run this command inside the `otelcol-contrib` directory that you created in the install Otel Collector step
-
-```bash
-./otelcol-contrib --config ./config.yaml
-```
-
- 
-
-### Step 2: Run your .NET application
-```bash
-dotnet build
-dotnet run
-```

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/MacOsARM64/QuickStart/dotnet-macosarm64-quickStart-instrumentApplication.md

@@ -1,70 +0,0 @@
-
-### Step 1: Install OpenTelemetry Dependencies
-Dependencies related to OpenTelemetry exporter and SDK have to be installed first.
-
-Run the below commands after navigating to the application source folder:
-```bash
-dotnet add package OpenTelemetry
-dotnet add package OpenTelemetry.Exporter.OpenTelemetryProtocol 
-dotnet add package OpenTelemetry.Extensions.Hosting
-dotnet add package OpenTelemetry.Instrumentation.Runtime
-dotnet add package OpenTelemetry.Instrumentation.AspNetCore 
-dotnet add package OpenTelemetry.AutoInstrumentation
-```
-
- 
-
-### Step 2:  Adding OpenTelemetry as a service and configuring exporter options
-
-In your `Program.cs` file, add OpenTelemetry as a service. Here, we are configuring these variables:
-
-`serviceName` - It is the name of your service.
-
-`otlpOptions.Endpoint` - It is the endpoint for your OTel Collector agent.
-
- 
-
-Here’s a sample `Program.cs` file with the configured variables:
-
-```bash
-using System.Diagnostics;
-using OpenTelemetry.Exporter;
-using OpenTelemetry.Resources;
-using OpenTelemetry.Trace;
-
-var builder = WebApplication.CreateBuilder(args);
-
-// Configure OpenTelemetry with tracing and auto-start.
-builder.Services.AddOpenTelemetry()
-    .ConfigureResource(resource => 
-        resource.AddService(serviceName: "{{MYAPP}}"))
-    .WithTracing(tracing => tracing
-        .AddAspNetCoreInstrumentation()
-        .AddOtlpExporter(otlpOptions =>
-        {
-                        //sigNoz Cloud Endpoint 
-            otlpOptions.Endpoint = new Uri("https://ingest.{{REGION}}.signoz.cloud:443");
-
-            otlpOptions.Protocol = OtlpExportProtocol.Grpc;
-                        
-                        //SigNoz Cloud account Ingestion key
-            string headerKey = "signoz-ingestion-key";
-            string headerValue = "{{SIGNOZ_INGESTION_KEY}}";
-
-            string formattedHeader = $"{headerKey}={headerValue}";
-            otlpOptions.Headers = formattedHeader;
-        }));
-
-var app = builder.Build();
-
-//The index route ("/") is set up to write out the OpenTelemetry trace information on the response:
-app.MapGet("/", () => $"Hello World! OpenTelemetry Trace: {Activity.Current?.Id}");
-
-app.Run();
-```
-
- 
-
-The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, we’re configuring it to send traces to the OTel Collector agent. The target must be a valid Uri with the scheme (http or https) and host and may contain a port and a path.
-
-This is done by configuring an OpenTelemetry [TracerProvider](https://github.com/open-telemetry/opentelemetry-dotnet/tree/main/docs/trace/customizing-the-sdk#readme) using extension methods and setting it to auto-start when the host is started.

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/MacOsARM64/QuickStart/dotnet-macosarm64-quickStart-runApplication.md

@@ -1,10 +0,0 @@
- 
-To run your .NET application, use the below command :
-
-```bash
-dotnet build
-dotnet run
-```
-
-Once you run your .NET application, interact with your application to generate some load and see your application in the SigNoz UI.
-

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/MacOsARM64/Recommended/dotnet-macosarm64-recommended-installOtelCollector.md

@@ -1,98 +0,0 @@
-## Setup OpenTelemetry Binary as an agent
- 
-
-### Step 1: Download otel-collector tar.gz
-```bash
-wget https://github.com/open-telemetry/opentelemetry-collector-releases/releases/download/v{{OTEL_VERSION}}/otelcol-contrib_{{OTEL_VERSION}}_darwin_arm64.tar.gz
-```
-
- 
-
-### Step 2: Extract otel-collector tar.gz to the `otelcol-contrib` folder
-```bash
-mkdir otelcol-contrib && tar xvzf otelcol-contrib_{{OTEL_VERSION}}_darwin_arm64.tar.gz -C otelcol-contrib
-```
-
- 
-
-### Step 3: Create `config.yaml` in folder `otelcol-contrib` with the below content in it
-```bash
-receivers:
-  otlp:
-    protocols:
-      grpc:
-        endpoint: 0.0.0.0:4317
-      http:
-        endpoint: 0.0.0.0:4318
-  hostmetrics:
-    collection_interval: 60s
-    scrapers:
-      cpu: {}
-      disk: {}
-      load: {}
-      filesystem: {}
-      memory: {}
-      network: {}
-      paging: {}
-      process:
-        mute_process_name_error: true
-        mute_process_exe_error: true
-        mute_process_io_error: true
-      processes: {}
-  prometheus:
-    config:
-      global:
-        scrape_interval: 60s
-      scrape_configs:
-        - job_name: otel-collector-binary
-          static_configs:
-            - targets:
-              # - localhost:8888
-processors:
-  batch:
-    send_batch_size: 1000
-    timeout: 10s
-  # Ref: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/processor/resourcedetectionprocessor/README.md
-  resourcedetection:
-    detectors: [env, system] # Before system detector, include ec2 for AWS, gcp for GCP and azure for Azure.
-    # Using OTEL_RESOURCE_ATTRIBUTES envvar, env detector adds custom labels.
-    timeout: 2s
-    system:
-      hostname_sources: [os] # alternatively, use [dns,os] for setting FQDN as host.name and os as fallback
-extensions:
-  health_check: {}
-  zpages: {}
-exporters:
-  otlp:
-    endpoint: "ingest.{{REGION}}.signoz.cloud:443"
-    tls:
-      insecure: false
-    headers:
-      "signoz-ingestion-key": "{{SIGNOZ_INGESTION_KEY}}"
-  logging:
-    verbosity: normal
-service:
-  telemetry:
-    metrics:
-      address: 0.0.0.0:8888
-  extensions: [health_check, zpages]
-  pipelines:
-    metrics:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    metrics/internal:
-      receivers: [prometheus, hostmetrics]
-      processors: [resourcedetection, batch]
-      exporters: [otlp]
-    traces:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    logs:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-```
-
-

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/MacOsARM64/Recommended/dotnet-macosarm64-recommended-instrumentApplication.md

@@ -1,68 +0,0 @@
-After setting up the Otel collector agent, follow the steps below to instrument your .NET Application
-
- 
- 
-
-### Step 1: Install OpenTelemetry Dependencies
-Install the following dependencies in your application.
-
-```bash
-dotnet add package OpenTelemetry
-dotnet add package OpenTelemetry.Exporter.OpenTelemetryProtocol 
-dotnet add package OpenTelemetry.Extensions.Hosting
-dotnet add package OpenTelemetry.Instrumentation.Runtime
-dotnet add package OpenTelemetry.Instrumentation.AspNetCore 
-dotnet add package OpenTelemetry.AutoInstrumentation
-```
-
- 
-
-### Step 2:  Adding OpenTelemetry as a service and configuring exporter options
-
-In your `Program.cs` file, add OpenTelemetry as a service. Here, we are configuring these variables:
-
-`serviceName` - It is the name of your service.
-
-`otlpOptions.Endpoint` - It is the endpoint for your OTel Collector agent.
-
- 
-
-Here’s a sample `Program.cs` file with the configured variables:
-
-```bash
-using System.Diagnostics;
-using OpenTelemetry.Exporter;
-using OpenTelemetry.Resources;
-using OpenTelemetry.Trace;
-
-var builder = WebApplication.CreateBuilder(args);
-
-// Configure OpenTelemetry with tracing and auto-start.
-builder.Services.AddOpenTelemetry()
-    .ConfigureResource(resource => 
-        resource.AddService(serviceName: "{{MYAPP}}"))
-    .WithTracing(tracing => tracing
-        .AddAspNetCoreInstrumentation()
-        .AddOtlpExporter(otlpOptions =>
-        {
-            otlpOptions.Endpoint = new Uri("http://localhost:4317");
-
-            otlpOptions.Protocol = OtlpExportProtocol.Grpc;
-        }));
-
-var app = builder.Build();
-
-//The index route ("/") is set up to write out the OpenTelemetry trace information on the response:
-app.MapGet("/", () => $"Hello World! OpenTelemetry Trace: {Activity.Current?.Id}");
-
-app.Run();
-```
-
- 
-
-The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, we’re configuring it to send traces to the OTel Collector agent. The target must be a valid Uri with the scheme (http or https) and host and may contain a port and a path.
-
-This is done by configuring an OpenTelemetry [TracerProvider](https://github.com/open-telemetry/opentelemetry-dotnet/tree/main/docs/trace/customizing-the-sdk#readme) using extension methods and setting it to auto-start when the host is started.
-
-
-

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/MacOsARM64/Recommended/dotnet-macosarm64-recommended-runApplication.md

@@ -1,18 +0,0 @@
- 
-Once you are done intrumenting your .NET application, you can run it using the below commands
- 
-
-### Step 1: Run OTel Collector
- Run this command inside the `otelcol-contrib` directory that you created in the install Otel Collector step
-
-```bash
-./otelcol-contrib --config ./config.yaml
-```
-
- 
-
-### Step 2: Run your .NET application
-```bash
-dotnet build
-dotnet run
-```

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/Windows/QuickStart/dotnet-windows-quickStart-instrumentApplication.md

@@ -1,67 +0,0 @@
-**Step 1: Installing the OpenTelemetry dependency packages:**
-
-```bash
-dotnet add package OpenTelemetry
-dotnet add package OpenTelemetry.Exporter.OpenTelemetryProtocol 
-dotnet add package OpenTelemetry.Extensions.Hosting
-dotnet add package OpenTelemetry.Instrumentation.Runtime
-dotnet add package OpenTelemetry.Instrumentation.AspNetCore 
-dotnet add package OpenTelemetry.AutoInstrumentation
-```
-
-**Step 2: Adding OpenTelemetry as a service and configuring exporter options in `Program.cs`:**
-
-In your `Program.cs` file, add OpenTelemetry as a service.
-
-Here’s a sample `Program.cs` file with the configured variables.
-
-```bash
-using System.Diagnostics;
-using OpenTelemetry.Exporter;
-using OpenTelemetry.Resources;
-using OpenTelemetry.Trace;
-
-var builder = WebApplication.CreateBuilder(args);
-
-// Configure OpenTelemetry with tracing and auto-start.
-builder.Services.AddOpenTelemetry()
-    .ConfigureResource(resource => 
-		resource.AddService(serviceName: "{{MYAPP}}"))
-    .WithTracing(tracing => tracing
-        .AddAspNetCoreInstrumentation()
-        .AddOtlpExporter(otlpOptions =>
-        {
-						//SigNoz Cloud Endpoint 
-            otlpOptions.Endpoint = new Uri("https://ingest.{{REGION}}.signoz.cloud:443");
-
-            otlpOptions.Protocol = OtlpExportProtocol.Grpc;
-						
-						//SigNoz Cloud account Ingestion key
-            string headerKey = "signoz-ingestion-key";
-            string headerValue = "{{SIGNOZ_INGESTION_KEY}}";
-
-            string formattedHeader = $"{headerKey}={headerValue}";
-            otlpOptions.Headers = formattedHeader;
-        }));
-
-var app = builder.Build();
-
-// The index route ("/") is set up to write out the OpenTelemetry trace information on the response:
-app.MapGet("/", () => $"Hello World! OpenTelemetry Trace: {Activity.Current?.Id}");
-
-app.Run();
-```
-
-
-**Step 3. Running the .NET application:**
-
-```bash
-dotnet build
-dotnet run
-```
-
-**Step 4: Generating some load data and checking your application in SigNoz UI**
-
-Once your application is running, generate some traffic by interacting with it.
-
-In the SigNoz account, open the `Services` tab. Hit the `Refresh` button on the top right corner, and your application should appear in the list of `Applications`. Ensure that you're checking data for the `time range filter` applied in the top right corner. You might have to wait for a few seconds before the data appears on SigNoz UI.

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/Windows/QuickStart/dotnet-windows-quickStart-runApplication.md

@@ -1,10 +0,0 @@
- 
-To run your .NET application, use the below command :
-
-```bash
-dotnet build
-dotnet run
-```
-
-Once you run your .NET application, interact with your application to generate some load and see your application in the SigNoz UI.
-

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/Windows/Recommended/dotnet-windows-recommended-installOtelCollector.md

@@ -1,12 +0,0 @@
-## Setup OpenTelemetry Binary as an agent
-
- 
-
-As a first step, you should install the OTel collector Binary according to the instructions provided on [this link](https://signoz.io/docs/tutorial/opentelemetry-binary-usage-in-virtual-machine/).
-
- 
-
-Once you are done setting up the OTel collector binary, you can follow the next steps.
-
- 
-

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/Windows/Recommended/dotnet-windows-recommended-instrumentApplication.md

@@ -1,63 +0,0 @@
-After setting up the Otel collector agent, follow the steps below to instrument your .NET Application
-
- 
- 
-
-### Step 1: Install OpenTelemetry Dependencies
-Install the following dependencies in your application.
-
-```bash
-dotnet add package OpenTelemetry
-dotnet add package OpenTelemetry.Exporter.OpenTelemetryProtocol 
-dotnet add package OpenTelemetry.Extensions.Hosting
-dotnet add package OpenTelemetry.Instrumentation.Runtime
-dotnet add package OpenTelemetry.Instrumentation.AspNetCore 
-dotnet add package OpenTelemetry.AutoInstrumentation
-```
-
- 
-
-### Step 2:  Adding OpenTelemetry as a service and configuring exporter options
-
-In your `Program.cs` file, add OpenTelemetry as a service. Here, we are configuring these variables:
-
- 
-
-Here’s a sample `Program.cs` file with the configured variables:
-
-```bash
-using System.Diagnostics;
-using OpenTelemetry.Exporter;
-using OpenTelemetry.Resources;
-using OpenTelemetry.Trace;
-
-var builder = WebApplication.CreateBuilder(args);
-
-// Configure OpenTelemetry with tracing and auto-start.
-builder.Services.AddOpenTelemetry()
-    .ConfigureResource(resource => 
-        resource.AddService(serviceName: "{{MYAPP}}"))
-    .WithTracing(tracing => tracing
-        .AddAspNetCoreInstrumentation()
-        .AddOtlpExporter(otlpOptions =>
-        {
-            otlpOptions.Endpoint = new Uri("http://localhost:4317");
-
-            otlpOptions.Protocol = OtlpExportProtocol.Grpc;
-        }));
-
-var app = builder.Build();
-
-//The index route ("/") is set up to write out the OpenTelemetry trace information on the response:
-app.MapGet("/", () => $"Hello World! OpenTelemetry Trace: {Activity.Current?.Id}");
-
-app.Run();
-```
- 
-
-The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, we’re configuring it to send traces to the OTel Collector agent. The target must be a valid Uri with the scheme (http or https) and host and may contain a port and a path.
-
-This is done by configuring an OpenTelemetry [TracerProvider](https://github.com/open-telemetry/opentelemetry-dotnet/tree/main/docs/trace/customizing-the-sdk#readme) using extension methods and setting it to auto-start when the host is started.
-
-
-

frontend/src/container/OnboardingContainer/Modules/APM/Dotnet/md-docs/Windows/Recommended/dotnet-windows-recommended-runApplication.md

@@ -1,18 +0,0 @@
- 
-Once you are done intrumenting your .NET application, you can run it using the below commands
- 
-
-### Step 1: Run OTel Collector
- Run this command inside the `otelcol-contrib` directory that you created in the install Otel Collector step
-
-```bash
-./otelcol-contrib --config ./config.yaml
-```
-
- 
-
-### Step 2: Run your .NET application
-```bash
-dotnet build
-dotnet run
-```

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/Docker/QuickStart/elixir-docker-quickStart-instrumentApplication.md

@@ -1,67 +0,0 @@
- 
-
-Follow the steps below to instrument your Elixir (Phoenix + Ecto) Application
-
-### Step 1: Add dependencies
-Install dependencies related to OpenTelemetry by adding them to `mix.exs` file 
-
-```bash
-    {:opentelemetry_exporter, "~> 1.6"},
-    {:opentelemetry_api, "~> 1.2"},
-    {:opentelemetry, "~> 1.3"},
-    {:opentelemetry_semantic_conventions, "~> 0.2"},
-    {:opentelemetry_cowboy, "~> 0.2.1"},
-    {:opentelemetry_phoenix, "~> 1.1"},
-    {:opentelemetry_ecto, "~> 1.1"}
-```
- 
-
-In your application start, usually the `application.ex` file, setup the telemetry handlers 
-
-```bash
-    :opentelemetry_cowboy.setup()
-    OpentelemetryPhoenix.setup(adapter: :cowboy2)
-    OpentelemetryEcto.setup([:{{MYAPP}}, :repo])
-```
- 
-
-As an example, this is how you can setup the handlers in your application.ex file for an application called demo :
-
-```bash
-# application.ex
-@impl true
-def start(_type, _args) do
-  :opentelemetry_cowboy.setup()
-  OpentelemetryPhoenix.setup(adapter: :cowboy2)
-  OpentelemetryEcto.setup([:demo, :repo])
-
-end
-```
-
- 
-
-### Step 2: Configure Application
-You need to configure your application to send telemetry data by adding the following config to your `runtime.exs` file:
-
-```bash
-config :opentelemetry, :resource, service: %{name: "{{MYAPP}}"}
-
-config :opentelemetry, :processors,
-  otel_batch_processor: %{
-    exporter: {
-      :opentelemetry_exporter,
-      %{
-        endpoints: ["https://ingest.{{REGION}}.signoz.cloud:443"],
-        headers: [
-          {"signoz-ingestion-key", {{SIGNOZ_ACCESS_TOKEN}} }
-        ]
-      }
-    }
-  }
-```
-
- 
-
-### Step 3: Dockerize your application
-
-Since the environment variables like SIGNOZ_INGESTION_KEY, Ingestion Endpoint and Service name are set in the above steps, you don't need to add any additional steps in your Dockerfile.

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/Docker/QuickStart/elixir-docker-quickStart-runApplication.md

@@ -1,25 +0,0 @@
-Once you update your Dockerfile, you can build and run it using the commands below.
-
- 
-
-### Step 1: Build your dockerfile
-
-Build your docker image
-
-```bash
-docker build -t <your-image-name> .
-```
-
-- `<your-image-name>` is the name of your Docker Image
-
-&nbsp;
-
-### Step 2: Run your docker image
-
-```bash
-docker run <your-image-name>
-```
-
-&nbsp;
-
-To see some examples for instrumented applications, you can checkout [this link](https://signoz.io/docs/instrumentation/elixir/#sample-examples)

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/Docker/Recommended/elixir-docker-recommended-installOtelCollector.md

@@ -1,12 +0,0 @@
-## Setup OpenTelemetry Binary as an agent
-
- 
-
-As a first step, you should install the OTel collector Binary according to the instructions provided on [this link](https://signoz.io/docs/tutorial/opentelemetry-binary-usage-in-virtual-machine/).
-
- 
-
-Once you are done setting up the OTel collector binary, you can follow the next steps.
-
- 
-

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/Docker/Recommended/elixir-docker-recommended-instrumentApplication.md

@@ -1,61 +0,0 @@
- 
-
-After setting up the Otel collector agent, follow the steps below to instrument your Elixir (Phoenix + Ecto) Application
-
-### Step 1: Add dependencies
-Install dependencies related to OpenTelemetry by adding them to `mix.exs` file 
-
-```bash
-    {:opentelemetry_exporter, "~> 1.6"},
-    {:opentelemetry_api, "~> 1.2"},
-    {:opentelemetry, "~> 1.3"},
-    {:opentelemetry_semantic_conventions, "~> 0.2"},
-    {:opentelemetry_cowboy, "~> 0.2.1"},
-    {:opentelemetry_phoenix, "~> 1.1"},
-    {:opentelemetry_ecto, "~> 1.1"}
-```
- 
-
-In your application start, usually the `application.ex` file, setup the telemetry handlers 
-
-```bash
-    :opentelemetry_cowboy.setup()
-    OpentelemetryPhoenix.setup(adapter: :cowboy2)
-    OpentelemetryEcto.setup([:{{MYAPP}}, :repo])
-```
- 
-
-As an example, this is how you can setup the handlers in your application.ex file for an application called demo :
-
-```bash
-# application.ex
-@impl true
-def start(_type, _args) do
-  :opentelemetry_cowboy.setup()
-  OpentelemetryPhoenix.setup(adapter: :cowboy2)
-  OpentelemetryEcto.setup([:demo, :repo])
-
-end
-```
-
- 
-
-### Step 2: Configure Application
-You need to configure your application to send telemetry data by adding the following config to your `runtime.exs` file:
-
-```bash
-config :opentelemetry, :resource, service: %{name: "{{MYAPP}}"}
-
-config :opentelemetry, :processors,
-    otel_batch_processor: %{
-      exporter: 
-      {:opentelemetry_exporter, 
-      %{endpoints: ["http://localhost:4318"]}
-      }
-  }
-```
- 
-
-### Step 3: Dockerize your application
-
-Since the environment variables like SIGNOZ_INGESTION_KEY, Ingestion Endpoint and Service name are set in the above steps, you don't need to add any additional steps in your Dockerfile.

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/Docker/Recommended/elixir-docker-recommended-runApplication.md

@@ -1,25 +0,0 @@
-Once you update your Dockerfile, you can build and run it using the commands below.
-
- 
-
-### Step 1: Build your dockerfile
-
-Build your docker image
-
-```bash
-docker build -t <your-image-name> .
-```
-
-- `<your-image-name>` is the name of your Docker Image
-
-&nbsp;
-
-### Step 2: Run your docker image
-
-```bash
-docker run <your-image-name>
-```
-
-&nbsp;
-
-To see some examples for instrumented applications, you can checkout [this link](https://signoz.io/docs/instrumentation/elixir/#sample-examples)

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/Kubernetes/elixir-kubernetes-installOtelCollector.md

@@ -1,43 +0,0 @@
-### Install otel-collector in your Kubernetes infra
-
-Add the SigNoz Helm Chart repository
-```bash
-helm repo add signoz https://charts.signoz.io
-```
-
- 
-
-If the chart is already present, update the chart to the latest using:
-```bash
-helm repo update
-```
-
- 
-
-For generic Kubernetes clusters, you can create *override-values.yaml* with the following configuration:
-
-```yaml
-global:
-  cloud: others
-  clusterName: <CLUSTER_NAME>
-  deploymentEnvironment: <DEPLOYMENT_ENVIRONMENT>
-otelCollectorEndpoint: ingest.{{REGION}}.signoz.cloud:443
-otelInsecure: false
-signozApiKey: {{SIGNOZ_INGESTION_KEY}}
-presets:
-  otlpExporter:
-    enabled: true
-  loggingExporter:
-    enabled: false
-```
-
-- Replace `<CLUSTER_NAME>` with the name of the Kubernetes cluster or a unique identifier of the cluster.
-- Replace `<DEPLOYMENT_ENVIRONMENT>` with the deployment environment of your application. Example: **"staging"**, **"production"**, etc.
-
-&nbsp;
-
-To install the k8s-infra chart with the above configuration, run the following command:
-
-```bash
-helm install my-release signoz/k8s-infra -f override-values.yaml
-```

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/Kubernetes/elixir-kubernetes-instrumentApplication.md

@@ -1,57 +0,0 @@
- 
-
-After setting up the Otel collector agent, follow the steps below to instrument your Elixir (Phoenix + Ecto) Application
-
-### Step 1: Add dependencies
-Install dependencies related to OpenTelemetry by adding them to `mix.exs` file 
-
-```bash
-    {:opentelemetry_exporter, "~> 1.6"},
-    {:opentelemetry_api, "~> 1.2"},
-    {:opentelemetry, "~> 1.3"},
-    {:opentelemetry_semantic_conventions, "~> 0.2"},
-    {:opentelemetry_cowboy, "~> 0.2.1"},
-    {:opentelemetry_phoenix, "~> 1.1"},
-    {:opentelemetry_ecto, "~> 1.1"}
-```
- 
-
-In your application start, usually the `application.ex` file, setup the telemetry handlers 
-
-```bash
-    :opentelemetry_cowboy.setup()
-    OpentelemetryPhoenix.setup(adapter: :cowboy2)
-    OpentelemetryEcto.setup([:{{MYAPP}}, :repo])
-```
- 
-
-As an example, this is how you can setup the handlers in your application.ex file for an application called demo :
-
-```bash
-# application.ex
-@impl true
-def start(_type, _args) do
-  :opentelemetry_cowboy.setup()
-  OpentelemetryPhoenix.setup(adapter: :cowboy2)
-  OpentelemetryEcto.setup([:demo, :repo])
-
-end
-```
-
- 
-
-### Step 2: Configure Application
-You need to configure your application to send telemetry data by adding the following config to your `runtime.exs` file:
-
-```bash
-config :opentelemetry, :resource, service: %{name: "{{MYAPP}}"}
-
-config :opentelemetry, :processors,
-    otel_batch_processor: %{
-      exporter: 
-      {:opentelemetry_exporter, 
-      %{endpoints: ["http://localhost:4318"]}
-      }
-  }
-```
-

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/Kubernetes/elixir-kubernetes-runApplication.md

@@ -1,6 +0,0 @@
-### Running your Elixir application
-Once you are done instrumenting your Elixir (Phoenix + Ecto) application with OpenTelemetry, you should install the dependencies needed to run your application and run it as you normally would.
-
- 
-
-To see some examples for instrumented applications, you can checkout [this link](https://signoz.io/docs/instrumentation/elixir/#sample-examples)

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/LinuxAMD64/QuickStart/elixir-linuxamd64-quickStart-instrumentApplication.md

@@ -1,62 +0,0 @@
- 
-
-Follow the steps below to instrument your Elixir (Phoenix + Ecto) Application
-
-### Step 1: Add dependencies
-Install dependencies related to OpenTelemetry by adding them to `mix.exs` file 
-
-```bash
-    {:opentelemetry_exporter, "~> 1.6"},
-    {:opentelemetry_api, "~> 1.2"},
-    {:opentelemetry, "~> 1.3"},
-    {:opentelemetry_semantic_conventions, "~> 0.2"},
-    {:opentelemetry_cowboy, "~> 0.2.1"},
-    {:opentelemetry_phoenix, "~> 1.1"},
-    {:opentelemetry_ecto, "~> 1.1"}
-```
- 
-
-In your application start, usually the `application.ex` file, setup the telemetry handlers 
-
-```bash
-    :opentelemetry_cowboy.setup()
-    OpentelemetryPhoenix.setup(adapter: :cowboy2)
-    OpentelemetryEcto.setup([:{{MYAPP}}, :repo])
-```
- 
-
-As an example, this is how you can setup the handlers in your application.ex file for an application called demo :
-
-```bash
-# application.ex
-@impl true
-def start(_type, _args) do
-  :opentelemetry_cowboy.setup()
-  OpentelemetryPhoenix.setup(adapter: :cowboy2)
-  OpentelemetryEcto.setup([:demo, :repo])
-
-end
-```
-
- 
-
-### Step 2: Configure Application
-You need to configure your application to send telemetry data by adding the following config to your `runtime.exs` file:
-
-```bash
-config :opentelemetry, :resource, service: %{name: "{{MYAPP}}"}
-
-config :opentelemetry, :processors,
-  otel_batch_processor: %{
-    exporter: {
-      :opentelemetry_exporter,
-      %{
-        endpoints: ["https://ingest.{{REGION}}.signoz.cloud:443"],
-        headers: [
-          {"signoz-ingestion-key", {{SIGNOZ_ACCESS_TOKEN}} }
-        ]
-      }
-    }
-  }
-```
-

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/LinuxAMD64/QuickStart/elixir-linuxamd64-quickStart-runApplication.md

@@ -1,6 +0,0 @@
-### Running your Elixir application
-Once you are done instrumenting your Elixir (Phoenix + Ecto) application with OpenTelemetry, you should install the dependencies needed to run your application and run it as you normally would.
-
- 
-
-To see some examples for instrumented applications, you can checkout [this link](https://signoz.io/docs/instrumentation/elixir/#sample-examples)

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/LinuxAMD64/Recommended/elixir-linuxamd64-recommended-installOtelCollector.md

@@ -1,96 +0,0 @@
-## Setup OpenTelemetry Binary as an agent
- 
-
-### Step 1: Download otel-collector tar.gz
-```bash
-wget https://github.com/open-telemetry/opentelemetry-collector-releases/releases/download/v{{OTEL_VERSION}}/otelcol-contrib_{{OTEL_VERSION}}_linux_amd64.tar.gz
-```
- 
-
-### Step 2: Extract otel-collector tar.gz to the `otelcol-contrib` folder
-```bash
-mkdir otelcol-contrib && tar xvzf otelcol-contrib_{{OTEL_VERSION}}_linux_amd64.tar.gz -C otelcol-contrib
-```
- 
-
-### Step 3: Create config.yaml in folder otelcol-contrib with the below content in it
-```bash
-receivers:
-  otlp:
-    protocols:
-      grpc:
-        endpoint: 0.0.0.0:4317
-      http:
-        endpoint: 0.0.0.0:4318
-  hostmetrics:
-    collection_interval: 60s
-    scrapers:
-      cpu: {}
-      disk: {}
-      load: {}
-      filesystem: {}
-      memory: {}
-      network: {}
-      paging: {}
-      process:
-        mute_process_name_error: true
-        mute_process_exe_error: true
-        mute_process_io_error: true
-      processes: {}
-  prometheus:
-    config:
-      global:
-        scrape_interval: 60s
-      scrape_configs:
-        - job_name: otel-collector-binary
-          static_configs:
-            - targets:
-              # - localhost:8888
-processors:
-  batch:
-    send_batch_size: 1000
-    timeout: 10s
-  # Ref: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/processor/resourcedetectionprocessor/README.md
-  resourcedetection:
-    detectors: [env, system] # Before system detector, include ec2 for AWS, gcp for GCP and azure for Azure.
-    # Using OTEL_RESOURCE_ATTRIBUTES envvar, env detector adds custom labels.
-    timeout: 2s
-    system:
-      hostname_sources: [os] # alternatively, use [dns,os] for setting FQDN as host.name and os as fallback
-extensions:
-  health_check: {}
-  zpages: {}
-exporters:
-  otlp:
-    endpoint: "ingest.{{REGION}}.signoz.cloud:443"
-    tls:
-      insecure: false
-    headers:
-      "signoz-ingestion-key": "{{SIGNOZ_INGESTION_KEY}}"
-  logging:
-    verbosity: normal
-service:
-  telemetry:
-    metrics:
-      address: 0.0.0.0:8888
-  extensions: [health_check, zpages]
-  pipelines:
-    metrics:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    metrics/internal:
-      receivers: [prometheus, hostmetrics]
-      processors: [resourcedetection, batch]
-      exporters: [otlp]
-    traces:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    logs:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-```
-
-

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/LinuxAMD64/Recommended/elixir-linuxamd64-recommended-instrumentApplication.md

@@ -1,57 +0,0 @@
- 
-
-After setting up the Otel collector agent, follow the steps below to instrument your Elixir (Phoenix + Ecto) Application
-
-### Step 1: Add dependencies
-Install dependencies related to OpenTelemetry by adding them to `mix.exs` file 
-
-```bash
-    {:opentelemetry_exporter, "~> 1.6"},
-    {:opentelemetry_api, "~> 1.2"},
-    {:opentelemetry, "~> 1.3"},
-    {:opentelemetry_semantic_conventions, "~> 0.2"},
-    {:opentelemetry_cowboy, "~> 0.2.1"},
-    {:opentelemetry_phoenix, "~> 1.1"},
-    {:opentelemetry_ecto, "~> 1.1"}
-```
- 
-
-In your application start, usually the `application.ex` file, setup the telemetry handlers 
-
-```bash
-    :opentelemetry_cowboy.setup()
-    OpentelemetryPhoenix.setup(adapter: :cowboy2)
-    OpentelemetryEcto.setup([:{{MYAPP}}, :repo])
-```
- 
-
-As an example, this is how you can setup the handlers in your application.ex file for an application called demo :
-
-```bash
-# application.ex
-@impl true
-def start(_type, _args) do
-  :opentelemetry_cowboy.setup()
-  OpentelemetryPhoenix.setup(adapter: :cowboy2)
-  OpentelemetryEcto.setup([:demo, :repo])
-
-end
-```
-
- 
-
-### Step 2: Configure Application
-You need to configure your application to send telemetry data by adding the following config to your `runtime.exs` file:
-
-```bash
-config :opentelemetry, :resource, service: %{name: "{{MYAPP}}"}
-
-config :opentelemetry, :processors,
-    otel_batch_processor: %{
-      exporter: 
-      {:opentelemetry_exporter, 
-      %{endpoints: ["http://localhost:4318"]}
-      }
-  }
-```
-

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/LinuxAMD64/Recommended/elixir-linuxamd64-recommended-runApplication.md

@@ -1,29 +0,0 @@
- 
-
-### Step 1: Run OTel Collector
- Run this command inside the `otelcol-contrib` directory that you created in the install Otel Collector step
-
-```bash
-./otelcol-contrib --config ./config.yaml &> otelcol-output.log & echo "$!" > otel-pid
-```
- 
-
-#### (Optional Step): View last 50 lines of `otelcol` logs
-```bash
-tail -f -n 50 otelcol-output.log
-```
-
-#### (Optional Step): Stop `otelcol`
-```bash
-kill "$(< otel-pid)"
-```
-&nbsp;
-
-### Step 2: Running your Elixir application
-
-Once you are done instrumenting your Elixir (Phoenix + Ecto) application with OpenTelemetry, you should install the dependencies needed to run your application and run it as you normally would.
-
-&nbsp;
-
-To see some examples for instrumented applications, you can checkout [this link](https://signoz.io/docs/instrumentation/elixir/#sample-examples)
-```

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/LinuxARM64/QuickStart/elixir-linuxarm64-quickStart-instrumentApplication.md

@@ -1,62 +0,0 @@
- 
-
-Follow the steps below to instrument your Elixir (Phoenix + Ecto) Application
-
-### Step 1: Add dependencies
-Install dependencies related to OpenTelemetry by adding them to `mix.exs` file 
-
-```bash
-    {:opentelemetry_exporter, "~> 1.6"},
-    {:opentelemetry_api, "~> 1.2"},
-    {:opentelemetry, "~> 1.3"},
-    {:opentelemetry_semantic_conventions, "~> 0.2"},
-    {:opentelemetry_cowboy, "~> 0.2.1"},
-    {:opentelemetry_phoenix, "~> 1.1"},
-    {:opentelemetry_ecto, "~> 1.1"}
-```
- 
-
-In your application start, usually the `application.ex` file, setup the telemetry handlers 
-
-```bash
-    :opentelemetry_cowboy.setup()
-    OpentelemetryPhoenix.setup(adapter: :cowboy2)
-    OpentelemetryEcto.setup([:{{MYAPP}}, :repo])
-```
- 
-
-As an example, this is how you can setup the handlers in your application.ex file for an application called demo :
-
-```bash
-# application.ex
-@impl true
-def start(_type, _args) do
-  :opentelemetry_cowboy.setup()
-  OpentelemetryPhoenix.setup(adapter: :cowboy2)
-  OpentelemetryEcto.setup([:demo, :repo])
-
-end
-```
-
- 
-
-### Step 2: Configure Application
-You need to configure your application to send telemetry data by adding the following config to your `runtime.exs` file:
-
-```bash
-config :opentelemetry, :resource, service: %{name: "{{MYAPP}}"}
-
-config :opentelemetry, :processors,
-  otel_batch_processor: %{
-    exporter: {
-      :opentelemetry_exporter,
-      %{
-        endpoints: ["https://ingest.{{REGION}}.signoz.cloud:443"],
-        headers: [
-          {"signoz-ingestion-key", {{SIGNOZ_ACCESS_TOKEN}} }
-        ]
-      }
-    }
-  }
-```
-

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/LinuxARM64/QuickStart/elixir-linuxarm64-quickStart-runApplication.md

@@ -1,6 +0,0 @@
-### Running your Elixir application
-Once you are done instrumenting your Elixir (Phoenix + Ecto) application with OpenTelemetry, you should install the dependencies needed to run your application and run it as you normally would.
-
- 
-
-To see some examples for instrumented applications, you can checkout [this link](https://signoz.io/docs/instrumentation/elixir/#sample-examples)

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/LinuxARM64/Recommended/elixir-linuxarm64-recommended-installOtelCollector.md

@@ -1,96 +0,0 @@
-## Setup OpenTelemetry Binary as an agent
- 
-
-### Step 1: Download otel-collector tar.gz
-```bash
-wget https://github.com/open-telemetry/opentelemetry-collector-releases/releases/download/v{{OTEL_VERSION}}/otelcol-contrib_{{OTEL_VERSION}}_linux_arm64.tar.gz
-```
- 
-
-### Step 2: Extract otel-collector tar.gz to the `otelcol-contrib` folder
-```bash
-mkdir otelcol-contrib && tar xvzf otelcol-contrib_{{OTEL_VERSION}}_linux_arm64.tar.gz -C otelcol-contrib
-```
- 
-
-### Step 3: Create config.yaml in folder otelcol-contrib with the below content in it
-```bash
-receivers:
-  otlp:
-    protocols:
-      grpc:
-        endpoint: 0.0.0.0:4317
-      http:
-        endpoint: 0.0.0.0:4318
-  hostmetrics:
-    collection_interval: 60s
-    scrapers:
-      cpu: {}
-      disk: {}
-      load: {}
-      filesystem: {}
-      memory: {}
-      network: {}
-      paging: {}
-      process:
-        mute_process_name_error: true
-        mute_process_exe_error: true
-        mute_process_io_error: true
-      processes: {}
-  prometheus:
-    config:
-      global:
-        scrape_interval: 60s
-      scrape_configs:
-        - job_name: otel-collector-binary
-          static_configs:
-            - targets:
-              # - localhost:8888
-processors:
-  batch:
-    send_batch_size: 1000
-    timeout: 10s
-  # Ref: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/processor/resourcedetectionprocessor/README.md
-  resourcedetection:
-    detectors: [env, system] # Before system detector, include ec2 for AWS, gcp for GCP and azure for Azure.
-    # Using OTEL_RESOURCE_ATTRIBUTES envvar, env detector adds custom labels.
-    timeout: 2s
-    system:
-      hostname_sources: [os] # alternatively, use [dns,os] for setting FQDN as host.name and os as fallback
-extensions:
-  health_check: {}
-  zpages: {}
-exporters:
-  otlp:
-    endpoint: "ingest.{{REGION}}.signoz.cloud:443"
-    tls:
-      insecure: false
-    headers:
-      "signoz-ingestion-key": "{{SIGNOZ_INGESTION_KEY}}"
-  logging:
-    verbosity: normal
-service:
-  telemetry:
-    metrics:
-      address: 0.0.0.0:8888
-  extensions: [health_check, zpages]
-  pipelines:
-    metrics:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    metrics/internal:
-      receivers: [prometheus, hostmetrics]
-      processors: [resourcedetection, batch]
-      exporters: [otlp]
-    traces:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    logs:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-```
-
-

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/LinuxARM64/Recommended/elixir-linuxarm64-recommended-instrumentApplication.md

@@ -1,57 +0,0 @@
- 
-
-After setting up the Otel collector agent, follow the steps below to instrument your Elixir (Phoenix + Ecto) Application
-
-### Step 1: Add dependencies
-Install dependencies related to OpenTelemetry by adding them to `mix.exs` file 
-
-```bash
-    {:opentelemetry_exporter, "~> 1.6"},
-    {:opentelemetry_api, "~> 1.2"},
-    {:opentelemetry, "~> 1.3"},
-    {:opentelemetry_semantic_conventions, "~> 0.2"},
-    {:opentelemetry_cowboy, "~> 0.2.1"},
-    {:opentelemetry_phoenix, "~> 1.1"},
-    {:opentelemetry_ecto, "~> 1.1"}
-```
- 
-
-In your application start, usually the `application.ex` file, setup the telemetry handlers 
-
-```bash
-    :opentelemetry_cowboy.setup()
-    OpentelemetryPhoenix.setup(adapter: :cowboy2)
-    OpentelemetryEcto.setup([:{{MYAPP}}, :repo])
-```
- 
-
-As an example, this is how you can setup the handlers in your application.ex file for an application called demo :
-
-```bash
-# application.ex
-@impl true
-def start(_type, _args) do
-  :opentelemetry_cowboy.setup()
-  OpentelemetryPhoenix.setup(adapter: :cowboy2)
-  OpentelemetryEcto.setup([:demo, :repo])
-
-end
-```
-
- 
-
-### Step 2: Configure Application
-You need to configure your application to send telemetry data by adding the following config to your `runtime.exs` file:
-
-```bash
-config :opentelemetry, :resource, service: %{name: "{{MYAPP}}"}
-
-config :opentelemetry, :processors,
-    otel_batch_processor: %{
-      exporter: 
-      {:opentelemetry_exporter, 
-      %{endpoints: ["http://localhost:4318"]}
-      }
-  }
-```
-

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/LinuxARM64/Recommended/elixir-linuxarm64-recommended-runApplication.md

@@ -1,28 +0,0 @@
- 
-
-### Step 1: Run OTel Collector
- Run this command inside the `otelcol-contrib` directory that you created in the install Otel Collector step
-
-```bash
-./otelcol-contrib --config ./config.yaml &> otelcol-output.log & echo "$!" > otel-pid
-```
- 
-
-#### (Optional Step): View last 50 lines of `otelcol` logs
-```bash
-tail -f -n 50 otelcol-output.log
-```
-
-#### (Optional Step): Stop `otelcol`
-```bash
-kill "$(< otel-pid)"
-```
-&nbsp;
-
-### Step 2: Running your Elixir application
-Once you are done instrumenting your Elixir (Phoenix + Ecto) application with OpenTelemetry, you should install the dependencies needed to run your application and run it as you normally would.
-
-&nbsp;
-
-To see some examples for instrumented applications, you can checkout [this link](https://signoz.io/docs/instrumentation/elixir/#sample-examples)
-```

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/MacOsAMD64/QuickStart/elixir-macosamd64-quickStart-instrumentApplication.md

@@ -1,62 +0,0 @@
- 
-
-Follow the steps below to instrument your Elixir (Phoenix + Ecto) Application
-
-### Step 1: Add dependencies
-Install dependencies related to OpenTelemetry by adding them to `mix.exs` file 
-
-```bash
-    {:opentelemetry_exporter, "~> 1.6"},
-    {:opentelemetry_api, "~> 1.2"},
-    {:opentelemetry, "~> 1.3"},
-    {:opentelemetry_semantic_conventions, "~> 0.2"},
-    {:opentelemetry_cowboy, "~> 0.2.1"},
-    {:opentelemetry_phoenix, "~> 1.1"},
-    {:opentelemetry_ecto, "~> 1.1"}
-```
- 
-
-In your application start, usually the `application.ex` file, setup the telemetry handlers 
-
-```bash
-    :opentelemetry_cowboy.setup()
-    OpentelemetryPhoenix.setup(adapter: :cowboy2)
-    OpentelemetryEcto.setup([:{{MYAPP}}, :repo])
-```
- 
-
-As an example, this is how you can setup the handlers in your application.ex file for an application called demo :
-
-```bash
-# application.ex
-@impl true
-def start(_type, _args) do
-  :opentelemetry_cowboy.setup()
-  OpentelemetryPhoenix.setup(adapter: :cowboy2)
-  OpentelemetryEcto.setup([:demo, :repo])
-
-end
-```
-
- 
-
-### Step 2: Configure Application
-You need to configure your application to send telemetry data by adding the following config to your `runtime.exs` file:
-
-```bash
-config :opentelemetry, :resource, service: %{name: "{{MYAPP}}"}
-
-config :opentelemetry, :processors,
-  otel_batch_processor: %{
-    exporter: {
-      :opentelemetry_exporter,
-      %{
-        endpoints: ["https://ingest.{{REGION}}.signoz.cloud:443"],
-        headers: [
-          {"signoz-ingestion-key", {{SIGNOZ_ACCESS_TOKEN}} }
-        ]
-      }
-    }
-  }
-```
-

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/MacOsAMD64/QuickStart/elixir-macosamd64-quickStart-runApplication.md

@@ -1,6 +0,0 @@
-### Running your Elixir application
-Once you are done instrumenting your Elixir (Phoenix + Ecto) application with OpenTelemetry, you should install the dependencies needed to run your application and run it as you normally would.
-
- 
-
-To see some examples for instrumented applications, you can checkout [this link](https://signoz.io/docs/instrumentation/elixir/#sample-examples)

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/MacOsAMD64/Recommended/elixir-macosamd64-recommended-installOtelCollector.md

@@ -1,96 +0,0 @@
-### Setup OpenTelemetry Binary as an agent
- 
-
-### Step 1: Download otel-collector tar.gz
-```bash
-wget https://github.com/open-telemetry/opentelemetry-collector-releases/releases/download/v{{OTEL_VERSION}}/otelcol-contrib_{{OTEL_VERSION}}_darwin_amd64.tar.gz
-```
- 
-
-### Step 2: Extract otel-collector tar.gz to the `otelcol-contrib` folder
-```bash
-mkdir otelcol-contrib && tar xvzf otelcol-contrib_{{OTEL_VERSION}}_darwin_amd64.tar.gz -C otelcol-contrib
-```
- 
-
-### Step 3: Create config.yaml in folder otelcol-contrib with the below content in it
-```bash
-receivers:
-  otlp:
-    protocols:
-      grpc:
-        endpoint: 0.0.0.0:4317
-      http:
-        endpoint: 0.0.0.0:4318
-  hostmetrics:
-    collection_interval: 60s
-    scrapers:
-      cpu: {}
-      disk: {}
-      load: {}
-      filesystem: {}
-      memory: {}
-      network: {}
-      paging: {}
-      process:
-        mute_process_name_error: true
-        mute_process_exe_error: true
-        mute_process_io_error: true
-      processes: {}
-  prometheus:
-    config:
-      global:
-        scrape_interval: 60s
-      scrape_configs:
-        - job_name: otel-collector-binary
-          static_configs:
-            - targets:
-              # - localhost:8888
-processors:
-  batch:
-    send_batch_size: 1000
-    timeout: 10s
-  # Ref: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/processor/resourcedetectionprocessor/README.md
-  resourcedetection:
-    detectors: [env, system] # Before system detector, include ec2 for AWS, gcp for GCP and azure for Azure.
-    # Using OTEL_RESOURCE_ATTRIBUTES envvar, env detector adds custom labels.
-    timeout: 2s
-    system:
-      hostname_sources: [os] # alternatively, use [dns,os] for setting FQDN as host.name and os as fallback
-extensions:
-  health_check: {}
-  zpages: {}
-exporters:
-  otlp:
-    endpoint: "ingest.{{REGION}}.signoz.cloud:443"
-    tls:
-      insecure: false
-    headers:
-      "signoz-ingestion-key": "{{SIGNOZ_INGESTION_KEY}}"
-  logging:
-    verbosity: normal
-service:
-  telemetry:
-    metrics:
-      address: 0.0.0.0:8888
-  extensions: [health_check, zpages]
-  pipelines:
-    metrics:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    metrics/internal:
-      receivers: [prometheus, hostmetrics]
-      processors: [resourcedetection, batch]
-      exporters: [otlp]
-    traces:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    logs:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-```
-
-

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/MacOsAMD64/Recommended/elixir-macosamd64-recommended-instrumentApplication.md

@@ -1,57 +0,0 @@
- 
-
-After setting up the Otel collector agent, follow the steps below to instrument your Elixir (Phoenix + Ecto) Application
-
-### Step 1: Add dependencies
-Install dependencies related to OpenTelemetry by adding them to `mix.exs` file 
-
-```bash
-    {:opentelemetry_exporter, "~> 1.6"},
-    {:opentelemetry_api, "~> 1.2"},
-    {:opentelemetry, "~> 1.3"},
-    {:opentelemetry_semantic_conventions, "~> 0.2"},
-    {:opentelemetry_cowboy, "~> 0.2.1"},
-    {:opentelemetry_phoenix, "~> 1.1"},
-    {:opentelemetry_ecto, "~> 1.1"}
-```
- 
-
-In your application start, usually the `application.ex` file, setup the telemetry handlers 
-
-```bash
-    :opentelemetry_cowboy.setup()
-    OpentelemetryPhoenix.setup(adapter: :cowboy2)
-    OpentelemetryEcto.setup([:{{MYAPP}}, :repo])
-```
- 
-
-As an example, this is how you can setup the handlers in your application.ex file for an application called demo :
-
-```bash
-# application.ex
-@impl true
-def start(_type, _args) do
-  :opentelemetry_cowboy.setup()
-  OpentelemetryPhoenix.setup(adapter: :cowboy2)
-  OpentelemetryEcto.setup([:demo, :repo])
-
-end
-```
-
- 
-
-### Step 2: Configure Application
-You need to configure your application to send telemetry data by adding the following config to your `runtime.exs` file:
-
-```bash
-config :opentelemetry, :resource, service: %{name: "{{MYAPP}}"}
-
-config :opentelemetry, :processors,
-    otel_batch_processor: %{
-      exporter: 
-      {:opentelemetry_exporter, 
-      %{endpoints: ["http://localhost:4318"]}
-      }
-  }
-```
-

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/MacOsAMD64/Recommended/elixir-macosamd64-recommended-runApplication.md

@@ -1,28 +0,0 @@
- 
-
-### Step 1: Run OTel Collector
- Run this command inside the `otelcol-contrib` directory that you created in the install Otel Collector step
-
-```bash
-./otelcol-contrib --config ./config.yaml &> otelcol-output.log & echo "$!" > otel-pid
-```
- 
-
-#### (Optional Step): View last 50 lines of `otelcol` logs
-```bash
-tail -f -n 50 otelcol-output.log
-```
-
-#### (Optional Step): Stop `otelcol`
-```bash
-kill "$(< otel-pid)"
-```
-&nbsp;
-
-### Step 2: Running your Elixir application
-Once you are done instrumenting your Elixir (Phoenix + Ecto) application with OpenTelemetry, you should install the dependencies needed to run your application and run it as you normally would.
-
-&nbsp;
-
-To see some examples for instrumented applications, you can checkout [this link](https://signoz.io/docs/instrumentation/elixir/#sample-examples)
-```

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/MacOsARM64/QuickStart/elixir-macosarm64-quickStart-instrumentApplication.md

@@ -1,62 +0,0 @@
- 
-
-Follow the steps below to instrument your Elixir (Phoenix + Ecto) Application
-
-### Step 1: Add dependencies
-Install dependencies related to OpenTelemetry by adding them to `mix.exs` file 
-
-```bash
-    {:opentelemetry_exporter, "~> 1.6"},
-    {:opentelemetry_api, "~> 1.2"},
-    {:opentelemetry, "~> 1.3"},
-    {:opentelemetry_semantic_conventions, "~> 0.2"},
-    {:opentelemetry_cowboy, "~> 0.2.1"},
-    {:opentelemetry_phoenix, "~> 1.1"},
-    {:opentelemetry_ecto, "~> 1.1"}
-```
- 
-
-In your application start, usually the `application.ex` file, setup the telemetry handlers 
-
-```bash
-    :opentelemetry_cowboy.setup()
-    OpentelemetryPhoenix.setup(adapter: :cowboy2)
-    OpentelemetryEcto.setup([:{{MYAPP}}, :repo])
-```
- 
-
-As an example, this is how you can setup the handlers in your application.ex file for an application called demo :
-
-```bash
-# application.ex
-@impl true
-def start(_type, _args) do
-  :opentelemetry_cowboy.setup()
-  OpentelemetryPhoenix.setup(adapter: :cowboy2)
-  OpentelemetryEcto.setup([:demo, :repo])
-
-end
-```
-
- 
-
-### Step 2: Configure Application
-You need to configure your application to send telemetry data by adding the following config to your `runtime.exs` file:
-
-```bash
-config :opentelemetry, :resource, service: %{name: "{{MYAPP}}"}
-
-config :opentelemetry, :processors,
-  otel_batch_processor: %{
-    exporter: {
-      :opentelemetry_exporter,
-      %{
-        endpoints: ["https://ingest.{{REGION}}.signoz.cloud:443"],
-        headers: [
-          {"signoz-ingestion-key", {{SIGNOZ_ACCESS_TOKEN}} }
-        ]
-      }
-    }
-  }
-```
-

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/MacOsARM64/QuickStart/elixir-macosarm64-quickStart-runApplication.md

@@ -1,6 +0,0 @@
-### Running your Elixir application
-Once you are done instrumenting your Elixir (Phoenix + Ecto) application with OpenTelemetry, you should install the dependencies needed to run your application and run it as you normally would.
-
- 
-
-To see some examples for instrumented applications, you can checkout [this link](https://signoz.io/docs/instrumentation/elixir/#sample-examples)

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/MacOsARM64/Recommended/elixir-macosarm64-recommended-installOtelCollector.md

@@ -1,96 +0,0 @@
-## Setup OpenTelemetry Binary as an agent
- 
-
-### Step 1: Download otel-collector tar.gz
-```bash
-wget https://github.com/open-telemetry/opentelemetry-collector-releases/releases/download/v{{OTEL_VERSION}}/otelcol-contrib_{{OTEL_VERSION}}_darwin_arm64.tar.gz
-```
- 
-
-### Step 2: Extract otel-collector tar.gz to the `otelcol-contrib` folder
-```bash
-mkdir otelcol-contrib && tar xvzf otelcol-contrib_{{OTEL_VERSION}}_darwin_arm64.tar.gz -C otelcol-contrib
-```
- 
-
-### Step 3: Create config.yaml in folder otelcol-contrib with the below content in it
-```bash
-receivers:
-  otlp:
-    protocols:
-      grpc:
-        endpoint: 0.0.0.0:4317
-      http:
-        endpoint: 0.0.0.0:4318
-  hostmetrics:
-    collection_interval: 60s
-    scrapers:
-      cpu: {}
-      disk: {}
-      load: {}
-      filesystem: {}
-      memory: {}
-      network: {}
-      paging: {}
-      process:
-        mute_process_name_error: true
-        mute_process_exe_error: true
-        mute_process_io_error: true
-      processes: {}
-  prometheus:
-    config:
-      global:
-        scrape_interval: 60s
-      scrape_configs:
-        - job_name: otel-collector-binary
-          static_configs:
-            - targets:
-              # - localhost:8888
-processors:
-  batch:
-    send_batch_size: 1000
-    timeout: 10s
-  # Ref: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/processor/resourcedetectionprocessor/README.md
-  resourcedetection:
-    detectors: [env, system] # Before system detector, include ec2 for AWS, gcp for GCP and azure for Azure.
-    # Using OTEL_RESOURCE_ATTRIBUTES envvar, env detector adds custom labels.
-    timeout: 2s
-    system:
-      hostname_sources: [os] # alternatively, use [dns,os] for setting FQDN as host.name and os as fallback
-extensions:
-  health_check: {}
-  zpages: {}
-exporters:
-  otlp:
-    endpoint: "ingest.{{REGION}}.signoz.cloud:443"
-    tls:
-      insecure: false
-    headers:
-      "signoz-ingestion-key": "{{SIGNOZ_INGESTION_KEY}}"
-  logging:
-    verbosity: normal
-service:
-  telemetry:
-    metrics:
-      address: 0.0.0.0:8888
-  extensions: [health_check, zpages]
-  pipelines:
-    metrics:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    metrics/internal:
-      receivers: [prometheus, hostmetrics]
-      processors: [resourcedetection, batch]
-      exporters: [otlp]
-    traces:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    logs:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-```
-
-

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/MacOsARM64/Recommended/elixir-macosarm64-recommended-instrumentApplication.md

@@ -1,57 +0,0 @@
- 
-
-After setting up the Otel collector agent, follow the steps below to instrument your Elixir (Phoenix + Ecto) Application
-
-### Step 1: Add dependencies
-Install dependencies related to OpenTelemetry by adding them to `mix.exs` file 
-
-```bash
-    {:opentelemetry_exporter, "~> 1.6"},
-    {:opentelemetry_api, "~> 1.2"},
-    {:opentelemetry, "~> 1.3"},
-    {:opentelemetry_semantic_conventions, "~> 0.2"},
-    {:opentelemetry_cowboy, "~> 0.2.1"},
-    {:opentelemetry_phoenix, "~> 1.1"},
-    {:opentelemetry_ecto, "~> 1.1"}
-```
- 
-
-In your application start, usually the `application.ex` file, setup the telemetry handlers 
-
-```bash
-    :opentelemetry_cowboy.setup()
-    OpentelemetryPhoenix.setup(adapter: :cowboy2)
-    OpentelemetryEcto.setup([:{{MYAPP}}, :repo])
-```
- 
-
-As an example, this is how you can setup the handlers in your application.ex file for an application called demo :
-
-```bash
-# application.ex
-@impl true
-def start(_type, _args) do
-  :opentelemetry_cowboy.setup()
-  OpentelemetryPhoenix.setup(adapter: :cowboy2)
-  OpentelemetryEcto.setup([:demo, :repo])
-
-end
-```
-
- 
-
-### Step 2: Configure Application
-You need to configure your application to send telemetry data by adding the following config to your `runtime.exs` file:
-
-```bash
-config :opentelemetry, :resource, service: %{name: "{{MYAPP}}"}
-
-config :opentelemetry, :processors,
-    otel_batch_processor: %{
-      exporter: 
-      {:opentelemetry_exporter, 
-      %{endpoints: ["http://localhost:4318"]}
-      }
-  }
-```
-

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/MacOsARM64/Recommended/elixir-macosarm64-recommended-runApplication.md

@@ -1,28 +0,0 @@
- 
-
-### Step 1: Run OTel Collector
- Run this command inside the `otelcol-contrib` directory that you created in the install Otel Collector step
-
-```bash
-./otelcol-contrib --config ./config.yaml &> otelcol-output.log & echo "$!" > otel-pid
-```
- 
-
-#### (Optional Step): View last 50 lines of `otelcol` logs
-```bash
-tail -f -n 50 otelcol-output.log
-```
-
-#### (Optional Step): Stop `otelcol`
-```bash
-kill "$(< otel-pid)"
-```
-&nbsp;
-
-### Step 2: Running your Elixir application
-Once you are done instrumenting your Elixir (Phoenix + Ecto) application with OpenTelemetry, you should install the dependencies needed to run your application and run it as you normally would.
-
-&nbsp;
-
-To see some examples for instrumented applications, you can checkout [this link](https://signoz.io/docs/instrumentation/elixir/#sample-examples)
-```

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/Windows/QuickStart/elixir-windows-quickStart-instrumentApplication.md

@@ -1,62 +0,0 @@
- 
-
-Follow the steps below to instrument your Elixir (Phoenix + Ecto) Application
-
-### Step 1: Add dependencies
-Install dependencies related to OpenTelemetry by adding them to `mix.exs` file 
-
-```bash
-    {:opentelemetry_exporter, "~> 1.6"},
-    {:opentelemetry_api, "~> 1.2"},
-    {:opentelemetry, "~> 1.3"},
-    {:opentelemetry_semantic_conventions, "~> 0.2"},
-    {:opentelemetry_cowboy, "~> 0.2.1"},
-    {:opentelemetry_phoenix, "~> 1.1"},
-    {:opentelemetry_ecto, "~> 1.1"}
-```
- 
-
-In your application start, usually the `application.ex` file, setup the telemetry handlers 
-
-```bash
-    :opentelemetry_cowboy.setup()
-    OpentelemetryPhoenix.setup(adapter: :cowboy2)
-    OpentelemetryEcto.setup([:{{MYAPP}}, :repo])
-```
- 
-
-As an example, this is how you can setup the handlers in your application.ex file for an application called demo :
-
-```bash
-# application.ex
-@impl true
-def start(_type, _args) do
-  :opentelemetry_cowboy.setup()
-  OpentelemetryPhoenix.setup(adapter: :cowboy2)
-  OpentelemetryEcto.setup([:demo, :repo])
-
-end
-```
-
- 
-
-### Step 2: Configure Application
-You need to configure your application to send telemetry data by adding the following config to your `runtime.exs` file:
-
-```bash
-config :opentelemetry, :resource, service: %{name: "{{MYAPP}}"}
-
-config :opentelemetry, :processors,
-  otel_batch_processor: %{
-    exporter: {
-      :opentelemetry_exporter,
-      %{
-        endpoints: ["https://ingest.{{REGION}}.signoz.cloud:443"],
-        headers: [
-          {"signoz-ingestion-key", {{SIGNOZ_ACCESS_TOKEN}} }
-        ]
-      }
-    }
-  }
-```
-

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/Windows/QuickStart/elixir-windows-quickStart-runApplication.md

@@ -1,6 +0,0 @@
-### Running your Elixir application
-Once you are done instrumenting your Elixir (Phoenix + Ecto) application with OpenTelemetry, you should install the dependencies needed to run your application and run it as you normally would.
-
- 
-
-To see some examples for instrumented applications, you can checkout [this link](https://signoz.io/docs/instrumentation/elixir/#sample-examples)

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/Windows/Recommended/elixir-windows-recommended-installOtelCollector.md

@@ -1,105 +0,0 @@
-## Setup OpenTelemetry Binary as an agent
- 
-
-### Step 1: Download otel-collector tar.gz
-
- 
-
-```bash
-wget https://github.com/open-telemetry/opentelemetry-collector-releases/releases/download/v{{OTEL_VERSION}}/otelcol-contrib_{{OTEL_VERSION}}_linux_amd64.tar.gz
-```
- 
-
-### Step 2: Extract otel-collector tar.gz to the `otelcol-contrib` folder
-
- 
-
-```bash
-mkdir otelcol-contrib && tar xvzf otelcol-contrib_{{OTEL_VERSION}}_linux_amd64.tar.gz -C otelcol-contrib
-```
- 
-
-### Step 3: Create config.yaml in folder otelcol-contrib with the below content in it
-
- 
-
-```bash
-receivers:
-  otlp:
-    protocols:
-      grpc:
-        endpoint: 0.0.0.0:4317
-      http:
-        endpoint: 0.0.0.0:4318
-  hostmetrics:
-    collection_interval: 60s
-    scrapers:
-      cpu: {}
-      disk: {}
-      load: {}
-      filesystem: {}
-      memory: {}
-      network: {}
-      paging: {}
-      process:
-        mute_process_name_error: true
-        mute_process_exe_error: true
-        mute_process_io_error: true
-      processes: {}
-  prometheus:
-    config:
-      global:
-        scrape_interval: 60s
-      scrape_configs:
-        - job_name: otel-collector-binary
-          static_configs:
-            - targets:
-              # - localhost:8888
-processors:
-  batch:
-    send_batch_size: 1000
-    timeout: 10s
-  # Ref: https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/processor/resourcedetectionprocessor/README.md
-  resourcedetection:
-    detectors: [env, system] # Before system detector, include ec2 for AWS, gcp for GCP and azure for Azure.
-    # Using OTEL_RESOURCE_ATTRIBUTES envvar, env detector adds custom labels.
-    timeout: 2s
-    system:
-      hostname_sources: [os] # alternatively, use [dns,os] for setting FQDN as host.name and os as fallback
-extensions:
-  health_check: {}
-  zpages: {}
-exporters:
-  otlp:
-    endpoint: "ingest.{{REGION}}.signoz.cloud:443"
-    tls:
-      insecure: false
-    headers:
-      "signoz-ingestion-key": "{{SIGNOZ_INGESTION_KEY}}"
-  logging:
-    verbosity: normal
-service:
-  telemetry:
-    metrics:
-      address: 0.0.0.0:8888
-  extensions: [health_check, zpages]
-  pipelines:
-    metrics:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    metrics/internal:
-      receivers: [prometheus, hostmetrics]
-      processors: [resourcedetection, batch]
-      exporters: [otlp]
-    traces:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-    logs:
-      receivers: [otlp]
-      processors: [batch]
-      exporters: [otlp]
-```
-
-

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/Windows/Recommended/elixir-windows-recommended-instrumentApplication.md

@@ -1,57 +0,0 @@
- 
-
-After setting up the Otel collector agent, follow the steps below to instrument your Elixir (Phoenix + Ecto) Application
-
-### Step 1: Add dependencies
-Install dependencies related to OpenTelemetry by adding them to `mix.exs` file 
-
-```bash
-    {:opentelemetry_exporter, "~> 1.6"},
-    {:opentelemetry_api, "~> 1.2"},
-    {:opentelemetry, "~> 1.3"},
-    {:opentelemetry_semantic_conventions, "~> 0.2"},
-    {:opentelemetry_cowboy, "~> 0.2.1"},
-    {:opentelemetry_phoenix, "~> 1.1"},
-    {:opentelemetry_ecto, "~> 1.1"}
-```
- 
-
-In your application start, usually the `application.ex` file, setup the telemetry handlers 
-
-```bash
-    :opentelemetry_cowboy.setup()
-    OpentelemetryPhoenix.setup(adapter: :cowboy2)
-    OpentelemetryEcto.setup([:{{MYAPP}}, :repo])
-```
- 
-
-As an example, this is how you can setup the handlers in your application.ex file for an application called demo :
-
-```bash
-# application.ex
-@impl true
-def start(_type, _args) do
-  :opentelemetry_cowboy.setup()
-  OpentelemetryPhoenix.setup(adapter: :cowboy2)
-  OpentelemetryEcto.setup([:demo, :repo])
-
-end
-```
-
- 
-
-### Step 2: Configure Application
-You need to configure your application to send telemetry data by adding the following config to your `runtime.exs` file:
-
-```bash
-config :opentelemetry, :resource, service: %{name: "{{MYAPP}}"}
-
-config :opentelemetry, :processors,
-    otel_batch_processor: %{
-      exporter: 
-      {:opentelemetry_exporter, 
-      %{endpoints: ["http://localhost:4318"]}
-      }
-  }
-```
-

frontend/src/container/OnboardingContainer/Modules/APM/Elixir/md-docs/Windows/Recommended/elixir-windows-recommended-runApplication.md

@@ -1,55 +0,0 @@
-
-OTel Collector binary helps to collect logs, hostmetrics, resource and infra attributes. It is recommended to install Otel Collector binary to collect and send traces to SigNoz cloud. You can correlate signals and have rich contextual data through this way.
-
-You can find instructions to install OTel Collector binary [here](https://signoz.io/docs/tutorial/opentelemetry-binary-usage-in-virtual-machine/) in your VM. Once you are done setting up your OTel Collector binary, you can follow the below steps for instrumenting your Elixir (Phoenix + Ecto) application.
-
-**Step 1. Add dependencies**
-
-Install dependencies related to OpenTelemetry by adding them to `mix.exs` file
-
-```bash
-    {:opentelemetry_exporter, "~> 1.6"},
-    {:opentelemetry_api, "~> 1.2"},
-    {:opentelemetry, "~> 1.3"},
-    {:opentelemetry_semantic_conventions, "~> 0.2"},
-    {:opentelemetry_cowboy, "~> 0.2.1"},
-    {:opentelemetry_phoenix, "~> 1.1"},
-    {:opentelemetry_ecto, "~> 1.1"}
-```
-
-In your application start, usually the `application.ex` file, setup the telemetry handlers
-
-```elixir
-    :opentelemetry_cowboy.setup()
-    OpentelemetryPhoenix.setup(adapter: :cowboy2)
-    OpentelemetryEcto.setup([:YOUR_APP_NAME, :repo])
-```
-
-As an example, this is how you can setup the handlers in your `application.ex` file for an application called `demo` :
-
-```elixir
-# application.ex
-@impl true
-def start(_type, _args) do
-  :opentelemetry_cowboy.setup()
-  OpentelemetryPhoenix.setup(adapter: :cowboy2)
-  OpentelemetryEcto.setup([:demo, :repo])
-
-end
-```
-
-**Step 2. Configure Application**
-
-You need to configure your application to send telemtry data by adding the follwing config to your `runtime.exs` file:
-
-```elixir
-config :opentelemetry, :resource, service: %{name: "{{MYAPP}}"}
-
-config :opentelemetry, :processors,
-    otel_batch_processor: %{
-      exporter: 
-      {:opentelemetry_exporter, 
-      %{endpoints: ["http://localhost:4318"]}
-      }
-  }
-```

frontend/src/container/OnboardingContainer/Modules/APM/GoLang/goLang.md

@@ -1,414 +0,0 @@
-## Send Traces to SigNoz Cloud
-
-### Application on VMs
-
-From VMs, there are two ways to send data to SigNoz Cloud.
-
-- Send traces directly to SigNoz Cloud (quick start)
-- Send traces via OTel Collector binary (recommended)
-
-#### **Send traces directly to SigNoz Cloud**
-
-1. **Install Dependencies**
-   
-   Dependencies related to OpenTelemetry exporter and SDK have to be installed first. Note that we are assuming you are using `gin` request router. If you are using other request routers, check out the [corresponding package](https://signoz.io/docs/instrumentation/golang/#request-routers).
-   
-   Run the below commands after navigating to the application source folder:
-    
-    ```bash
-    go get go.opentelemetry.io/otel \
-      go.opentelemetry.io/otel/trace \
-      go.opentelemetry.io/otel/sdk \
-      go.opentelemetry.io/contrib/instrumentation/github.com/gin-gonic/gin/otelgin \
-      go.opentelemetry.io/otel/exporters/otlp/otlptrace \
-      go.opentelemetry.io/otel/exporters/otlp/otlptrace/otlptracegrpc
-    ```
-    
-2. **Declare environment variables for configuring OpenTelemetry**
-   
-   Declare the following global variables in `main.go` which we will use to configure OpenTelemetry:
-   
-   ```bash
-    var (
-        serviceName  = os.Getenv("SERVICE_NAME")
-        collectorURL = os.Getenv("OTEL_EXPORTER_OTLP_ENDPOINT")
-        insecure     = os.Getenv("INSECURE_MODE")
-    )
-    ```
-    
-3. **Instrument your Go application with OpenTelemetry**
-   
-   To configure your application to send data we will need a function to initialize OpenTelemetry. Add the following snippet of code in your `main.go` file.
-   
-    ```go
-        
-    import (
-        .....
-
-        "github.com/gin-gonic/gin"
-        "go.opentelemetry.io/otel"
-        "go.opentelemetry.io/otel/attribute"
-        "go.opentelemetry.io/otel/exporters/otlp/otlptrace"
-        "go.opentelemetry.io/otel/exporters/otlp/otlptrace/otlptracegrpc"
-
-        "go.opentelemetry.io/otel/sdk/resource"
-        sdktrace "go.opentelemetry.io/otel/sdk/trace"
-    )
-
-    func initTracer() func(context.Context) error {
-
-        var secureOption otlptracegrpc.Option
-
-        if strings.ToLower(insecure) == "false" || insecure == "0" || strings.ToLower(insecure) == "f" {
-            secureOption = otlptracegrpc.WithTLSCredentials(credentials.NewClientTLSFromCert(nil, ""))
-        } else {
-            secureOption = otlptracegrpc.WithInsecure()
-        }
-
-        exporter, err := otlptrace.New(
-            context.Background(),
-            otlptracegrpc.NewClient(
-                secureOption,
-                otlptracegrpc.WithEndpoint(collectorURL),
-            ),
-        )
-
-        if err != nil {
-            log.Fatalf("Failed to create exporter: %v", err)
-        }
-        resources, err := resource.New(
-            context.Background(),
-            resource.WithAttributes(
-                attribute.String("service.name", serviceName),
-                attribute.String("library.language", "go"),
-            ),
-        )
-        if err != nil {
-            log.Fatalf("Could not set resources: %v", err)
-        }
-
-        otel.SetTracerProvider(
-            sdktrace.NewTracerProvider(
-                sdktrace.WithSampler(sdktrace.AlwaysSample()),
-                sdktrace.WithBatcher(exporter),
-                sdktrace.WithResource(resources),
-            ),
-        )
-        return exporter.Shutdown
-    }
-    ```
-    
-4. **Initialize the tracer in main.go**
-   
-   Modify the main function to initialise the tracer in `main.go`. Initiate the tracer at the very beginning of our main function.
-    
-    ```go
-    func main() {
-        cleanup := initTracer()
-        defer cleanup(context.Background())
-    
-        ......
-    }
-    ```
-    
-5. **Add the OpenTelemetry Gin middleware**
-   
-   Configure Gin to use the middleware by adding the following lines in `main.go`.
-    
-    ```go
-    import (
-        ....
-      "go.opentelemetry.io/contrib/instrumentation/github.com/gin-gonic/gin/otelgin"
-    )
-    
-    func main() {
-        ......
-        r := gin.Default()
-        r.Use(otelgin.Middleware(serviceName))
-        ......
-    }
-    ```
-
-6. **Set environment variables and run your Go Gin application**
-   
-   The run command must have some environment variables to send data to SigNoz cloud. The run command:
-    
-    ```bash
-    SERVICE_NAME={{MYAPP}} INSECURE_MODE=false OTEL_EXPORTER_OTLP_HEADERS=signoz-ingestion-key={{SIGNOZ_INGESTION_KEY}} OTEL_EXPORTER_OTLP_ENDPOINT=ingest.{{REGION}}.signoz.cloud:443 go run main.go
-    ```  
-    
-    If you want to update your `service_name`, you can modify the `SERVICE_NAME` variable.
-  
----
-
-#### **Send traces via OTel Collector binary**
-
-OTel Collector binary helps to collect logs, hostmetrics, resource and infra attributes. It is recommended to install Otel Collector binary to collect and send traces to SigNoz cloud. You can correlate signals and have rich contextual data through this way.
-
-You can find instructions to install OTel Collector binary [here](https://signoz.io/docs/tutorial/opentelemetry-binary-usage-in-virtual-machine/) in your VM. Once you are done setting up your OTel Collector binary, you can follow the below steps for instrumenting your Golang application.
-
-1. **Install Dependencies**
-   
-   Dependencies related to OpenTelemetry exporter and SDK have to be installed first. Note that we are assuming you are using `gin` request router. If you are using other request routers, check out the [corresponding package](https://signoz.io/docs/instrumentation/golang/#request-routers).
-   
-   Run the below commands after navigating to the application source folder:
-    
-    ```bash
-    go get go.opentelemetry.io/otel \
-      go.opentelemetry.io/otel/trace \
-      go.opentelemetry.io/otel/sdk \
-      go.opentelemetry.io/contrib/instrumentation/github.com/gin-gonic/gin/otelgin \
-      go.opentelemetry.io/otel/exporters/otlp/otlptrace \
-      go.opentelemetry.io/otel/exporters/otlp/otlptrace/otlptracegrpc
-    ```
-    
-2. **Declare environment variables for configuring OpenTelemetry**
-   
-   Declare the following global variables in `main.go` which we will use to configure OpenTelemetry:
-   
-   ```go
-    var (
-        serviceName  = os.Getenv("SERVICE_NAME")
-        collectorURL = os.Getenv("OTEL_EXPORTER_OTLP_ENDPOINT")
-        insecure     = os.Getenv("INSECURE_MODE")
-    )
-    ```
-    
-3. **Instrument your Go application with OpenTelemetry**
-   
-   To configure your application to send data we will need a function to initialize OpenTelemetry. Add the following snippet of code in your `main.go` file.
-    
-   ```go
-        
-    import (
-        .....
-
-        "github.com/gin-gonic/gin"
-        "go.opentelemetry.io/otel"
-        "go.opentelemetry.io/otel/attribute"
-        "go.opentelemetry.io/otel/exporters/otlp/otlptrace"
-        "go.opentelemetry.io/otel/exporters/otlp/otlptrace/otlptracegrpc"
-
-        "go.opentelemetry.io/otel/sdk/resource"
-        sdktrace "go.opentelemetry.io/otel/sdk/trace"
-    )
-
-    func initTracer() func(context.Context) error {
-
-        var secureOption otlptracegrpc.Option
-
-        if strings.ToLower(insecure) == "false" || insecure == "0" || strings.ToLower(insecure) == "f" {
-            secureOption = otlptracegrpc.WithTLSCredentials(credentials.NewClientTLSFromCert(nil, ""))
-        } else {
-            secureOption = otlptracegrpc.WithInsecure()
-        }
-
-        exporter, err := otlptrace.New(
-            context.Background(),
-            otlptracegrpc.NewClient(
-                secureOption,
-                otlptracegrpc.WithEndpoint(collectorURL),
-            ),
-        )
-
-        if err != nil {
-            log.Fatalf("Failed to create exporter: %v", err)
-        }
-        resources, err := resource.New(
-            context.Background(),
-            resource.WithAttributes(
-                attribute.String("service.name", serviceName),
-                attribute.String("library.language", "go"),
-            ),
-        )
-        if err != nil {
-            log.Fatalf("Could not set resources: %v", err)
-        }
-
-        otel.SetTracerProvider(
-            sdktrace.NewTracerProvider(
-                sdktrace.WithSampler(sdktrace.AlwaysSample()),
-                sdktrace.WithBatcher(exporter),
-                sdktrace.WithResource(resources),
-            ),
-        )
-        return exporter.Shutdown
-    }
-    
-4. **Initialize the tracer in main.go**
-   
-   Modify the main function to initialise the tracer in `main.go`. Initiate the tracer at the very beginning of our main function.
-    
-    ```go
-    func main() {
-        cleanup := initTracer()
-        defer cleanup(context.Background())
-    
-        ......
-    }
-    ```
-    
-5. **Add the OpenTelemetry Gin middleware**
-   
-   Configure Gin to use the middleware by adding the following lines in `main.go`.
-    
-    ```go
-    import (
-        ....
-      "go.opentelemetry.io/contrib/instrumentation/github.com/gin-gonic/gin/otelgin"
-    )
-    
-    func main() {
-        ......
-        r := gin.Default()
-        r.Use(otelgin.Middleware(serviceName))
-        ......
-    }
-    ```
-    
-6. **Set environment variables and run your Go Gin application**
-   
-   The run command must have some environment variables to send data to SigNoz. The run command:
-    
-    ```bash
-    SERVICE_NAME={{MYAPP}} INSECURE_MODE=true OTEL_EXPORTER_OTLP_ENDPOINT=localhost:4317 go run main.go
-    ```
-    
-    If you want to update your `service_name`, you can modify the `SERVICE_NAME` variable.
-
----
-
-### Applications Deployed on Kubernetes
-
-For Golang application deployed on Kubernetes, you need to install OTel Collector agent in your k8s infra to collect and send traces to SigNoz Cloud. You can find the instructions to install OTel Collector agent [here](https://signoz.io/docs/tutorial/kubernetes-infra-metrics/).
-
-Once you have set up OTel Collector agent, you can proceed with OpenTelemetry Golang instrumentation by following the below steps:
-
-1. **Install Dependencies**
-   
-   Dependencies related to OpenTelemetry exporter and SDK have to be installed first. Note that we are assuming you are using `gin` request router. If you are using other request routers, check out the [corresponding package](https://signoz.io/docs/instrumentation/golang/#request-routers).
-   
-   Run the below commands after navigating to the application source folder:
-    
-    ```bash
-    go get go.opentelemetry.io/otel \
-      go.opentelemetry.io/otel/trace \
-      go.opentelemetry.io/otel/sdk \
-      go.opentelemetry.io/contrib/instrumentation/github.com/gin-gonic/gin/otelgin \
-      go.opentelemetry.io/otel/exporters/otlp/otlptrace \
-      go.opentelemetry.io/otel/exporters/otlp/otlptrace/otlptracegrpc
-    ```
-    
-2. **Declare environment variables for configuring OpenTelemetry**
-   
-   Declare the following global variables in `main.go` which we will use to configure OpenTelemetry:
-   
-   ```go
-    var (
-        serviceName  = os.Getenv("SERVICE_NAME")
-        collectorURL = os.Getenv("OTEL_EXPORTER_OTLP_ENDPOINT")
-        insecure     = os.Getenv("INSECURE_MODE")
-    )
-    ```
-    
-3. **Instrument your Go application with OpenTelemetry**
-   
-   To configure your application to send data we will need a function to initialize OpenTelemetry. Add the following snippet of code in your `main.go` file.
-    
-   ```go
-        
-    import (
-        .....
-
-        "github.com/gin-gonic/gin"
-        "go.opentelemetry.io/otel"
-        "go.opentelemetry.io/otel/attribute"
-        "go.opentelemetry.io/otel/exporters/otlp/otlptrace"
-        "go.opentelemetry.io/otel/exporters/otlp/otlptrace/otlptracegrpc"
-
-        "go.opentelemetry.io/otel/sdk/resource"
-        sdktrace "go.opentelemetry.io/otel/sdk/trace"
-    )
-
-    func initTracer() func(context.Context) error {
-
-        var secureOption otlptracegrpc.Option
-
-        if strings.ToLower(insecure) == "false" || insecure == "0" || strings.ToLower(insecure) == "f" {
-            secureOption = otlptracegrpc.WithTLSCredentials(credentials.NewClientTLSFromCert(nil, ""))
-        } else {
-            secureOption = otlptracegrpc.WithInsecure()
-        }
-
-        exporter, err := otlptrace.New(
-            context.Background(),
-            otlptracegrpc.NewClient(
-                secureOption,
-                otlptracegrpc.WithEndpoint(collectorURL),
-            ),
-        )
-
-        if err != nil {
-            log.Fatalf("Failed to create exporter: %v", err)
-        }
-        resources, err := resource.New(
-            context.Background(),
-            resource.WithAttributes(
-                attribute.String("service.name", serviceName),
-                attribute.String("library.language", "go"),
-            ),
-        )
-        if err != nil {
-            log.Fatalf("Could not set resources: %v", err)
-        }
-
-        otel.SetTracerProvider(
-            sdktrace.NewTracerProvider(
-                sdktrace.WithSampler(sdktrace.AlwaysSample()),
-                sdktrace.WithBatcher(exporter),
-                sdktrace.WithResource(resources),
-            ),
-        )
-        return exporter.Shutdown
-    }
-    
-4. **Initialize the tracer in main.go**
-   
-   Modify the main function to initialise the tracer in `main.go`. Initiate the tracer at the very beginning of our main function.
-    
-    ```go
-    func main() {
-        cleanup := initTracer()
-        defer cleanup(context.Background())
-    
-        ......
-    }
-    ```
-    
-5. **Add the OpenTelemetry Gin middleware**
-   
-   Configure Gin to use the middleware by adding the following lines in `main.go`.
-    
-    ```go
-    import (
-        ....
-      "go.opentelemetry.io/contrib/instrumentation/github.com/gin-gonic/gin/otelgin"
-    )
-    
-    func main() {
-        ......
-        r := gin.Default()
-        r.Use(otelgin.Middleware(serviceName))
-        ......
-    }
-    ```
-    
-6. **Set environment variables and run your Go Gin application**
-
-   The run command must have some environment variables to send data to SigNoz. The run command:
-    
-    ```bash
-    SERVICE_NAME={{MYAPP}} INSECURE_MODE=true OTEL_EXPORTER_OTLP_ENDPOINT=localhost:4317 go run main.go
-    ```
-    
-    If you want to update your `service_name`, you can modify the `SERVICE_NAME` variable.

frontend/src/container/OnboardingContainer/Modules/APM/GoLang/md-docs/Docker/QuickStart/golang-docker-quickStart-instrumentApplication.md

@@ -1,135 +0,0 @@
-### Step 1: Install OpenTelemetry Dependencies
-Dependencies related to OpenTelemetry exporter and SDK have to be installed first.
-
-Run the below commands after navigating to the application source folder:
-```bash
-go get go.opentelemetry.io/otel \
-  go.opentelemetry.io/otel/trace \
-  go.opentelemetry.io/otel/sdk \
-  go.opentelemetry.io/contrib/instrumentation/github.com/gin-gonic/gin/otelgin \
-  go.opentelemetry.io/otel/exporters/otlp/otlptrace \
-  go.opentelemetry.io/otel/exporters/otlp/otlptrace/otlptracegrpc
-```
-
-**Note:** We are assuming you are using gin request router. If you are using other request routers, check out the [corresponding package](https://signoz.io/docs/instrumentation/golang/#request-routers).
- 
- 
-
-### Step 2: Declare environment variables for configuring OpenTelemetry
-Declare the following global variables in **`main.go`** which we will use to configure OpenTelemetry:
-```bash
- var (
-     serviceName  = os.Getenv("SERVICE_NAME")
-     collectorURL = os.Getenv("OTEL_EXPORTER_OTLP_ENDPOINT")
-     insecure     = os.Getenv("INSECURE_MODE")
- )
-```
- 
-
-### Step 3: Instrument your Go application 
-To configure your application to send data we will need a function to initialize OpenTelemetry. Add the following snippet of code in your **`main.go`** file.
-
-```bash
-     
- import (
-     .....
-
-     "google.golang.org/grpc/credentials"
-     "github.com/gin-gonic/gin"
-     "go.opentelemetry.io/otel"
-     "go.opentelemetry.io/otel/attribute"
-     "go.opentelemetry.io/otel/exporters/otlp/otlptrace"
-     "go.opentelemetry.io/otel/exporters/otlp/otlptrace/otlptracegrpc"
-
-     "go.opentelemetry.io/otel/sdk/resource"
-     sdktrace "go.opentelemetry.io/otel/sdk/trace"
- )
-
- func initTracer() func(context.Context) error {
-
-     var secureOption otlptracegrpc.Option
-
-     if strings.ToLower(insecure) == "false" || insecure == "0" || strings.ToLower(insecure) == "f" {
-         secureOption = otlptracegrpc.WithTLSCredentials(credentials.NewClientTLSFromCert(nil, ""))
-     } else {
-         secureOption = otlptracegrpc.WithInsecure()
-     }
-
-     exporter, err := otlptrace.New(
-         context.Background(),
-         otlptracegrpc.NewClient(
-             secureOption,
-             otlptracegrpc.WithEndpoint(collectorURL),
-         ),
-     )
-
-     if err != nil {
-         log.Fatalf("Failed to create exporter: %v", err)
-     }
-     resources, err := resource.New(
-         context.Background(),
-         resource.WithAttributes(
-             attribute.String("service.name", serviceName),
-             attribute.String("library.language", "go"),
-         ),
-     )
-     if err != nil {
-         log.Fatalf("Could not set resources: %v", err)
-     }
-
-     otel.SetTracerProvider(
-         sdktrace.NewTracerProvider(
-             sdktrace.WithSampler(sdktrace.AlwaysSample()),
-             sdktrace.WithBatcher(exporter),
-             sdktrace.WithResource(resources),
-         ),
-     )
-     return exporter.Shutdown
- }
-```
- 
-
-### Step 4: Initialise the tracer in **`main.go`**
-Modify the main function to initialise the tracer in **`main.go`**. Initiate the tracer at the very beginning of our main function.
-```bash
-func main() {
-    cleanup := initTracer()
-    defer cleanup(context.Background())
-
-    ......
-}
-```
- 
-
-### Step 5: Add the OpenTelemetry Gin middleware
-Configure Gin to use the middleware by adding the following lines in **`main.go`**
-```bash
-import (
-    ....
-  "go.opentelemetry.io/contrib/instrumentation/github.com/gin-gonic/gin/otelgin"
-)
-
-func main() {
-    ......
-    r := gin.Default()
-    r.Use(otelgin.Middleware(serviceName))
-    ......
-}
-```
-
- 
-
-### Step 6: Dockerize your application
-
-Set the environment variables in your Dockerfile.
-
-```bash
-...
-# Set environment variables
-ENV SERVICE_NAME={{MYAPP}} \
-    INSECURE_MODE=false \
-    OTEL_EXPORTER_OTLP_HEADERS="signoz-ingestion-key=b{{SIGNOZ_INGESTION_KEY}}" \
-    OTEL_EXPORTER_OTLP_ENDPOINT=ingest.{{REGION}}.signoz.cloud:443
-...
-```
-

frontend/src/container/OnboardingContainer/Modules/APM/GoLang/md-docs/Docker/QuickStart/golang-docker-quickStart-runApplication.md

@@ -1,21 +0,0 @@
-Once you update your Dockerfile, you can build and run it using the commands below.
-
- 
-
-### Step 1: Build your dockerfile
-
-Build your docker image
-
-```bash
-docker build -t <your-image-name> .
-```
-
-- `<your-image-name>` is the name of your Docker Image
-
-&nbsp;
-
-### Step 2: Run your docker image
-
-```bash
-docker run <your-image-name>
-```

frontend/src/container/OnboardingContainer/Modules/APM/GoLang/md-docs/Docker/Recommended/golang-docker-recommended-installOtelCollector.md

@@ -1,12 +0,0 @@
-## Setup OpenTelemetry Binary as an agent
-
- 
-
-As a first step, you should install the OTel collector Binary according to the instructions provided on [this link](https://signoz.io/docs/tutorial/opentelemetry-binary-usage-in-virtual-machine/).
-
- 
-
-Once you are done setting up the OTel collector binary, you can follow the next steps.
-
- 
-