Compare commits

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9 Commits

Author SHA1 Message Date
nityanandagohain
9604438723 Merge remote-tracking branch 'origin/main' into issue_5267 2026-06-25 17:23:58 +05:30
nityanandagohain
e0a66b7a10 fix: more cleanup 2026-06-25 17:20:48 +05:30
nityanandagohain
b01be1f31c fix: update openapi 2026-06-25 11:19:08 +05:30
nityanandagohain
c8a007cd8d fix: cleanup go.mod 2026-06-25 10:55:54 +05:30
nityanandagohain
205b23b830 fix: lint 2026-06-25 10:52:27 +05:30
nityanandagohain
68b166f75e fix: more cleanup and integration test 2026-06-25 10:50:52 +05:30
nityanandagohain
20d8ca6d7d Merge remote-tracking branch 'origin/main' into issue_5267 2026-06-25 10:06:52 +05:30
nityanandagohain
1e1be670f1 feat: integrate with collector 2026-06-23 12:07:16 +05:30
nityanandagohain
d1682f2ab6 feat: span mapper test endpoint 2026-06-19 18:31:31 +05:30
1203 changed files with 59166 additions and 13954 deletions

View File

@@ -38,6 +38,7 @@ jobs:
fail-fast: false
matrix:
suite:
- spanmapper
- alerts
- basepath
- callbackauthn

View File

@@ -56,6 +56,17 @@ 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' ||

View File

@@ -1,76 +1,48 @@
# 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.
# Migrating from the install script to Foundry
> [!IMPORTANT]
> 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].
> The install script is now deprecated and will no longer receive updates.
## How it works
This guide walks you through migrating an existing SigNoz deployment running via
Docker Compose to [Foundry](https://signoz.io/docs/install/docker/).
Foundry splits a deployment into two commands:
> [!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.
- `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.
## Overview
To stay up to date on new installation platforms and patterns, please refer to [Foundry](https://github.com/SigNoz/foundry).
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).
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).
## Prerequisites
- [ ] Install Foundry - `curl -fsSL https://signoz.io/foundry.sh | bash`
- An existing SigNoz deployment from `install.sh` or `deploy/` (Compose or
Swarm).
- `foundryctl` (installed in step 1).
## 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.
## Migrate
1. Make a note of the volume names used by your existing deployment for the following components:
- ClickHouse
- SigNoz
- ZooKeeper
### 1. Install Foundry
> If you used the docker compose file we provided, the volumes will be `signoz-clickhouse`, `signoz-sqlite`, and `signoz-zookeeper-1`.
```bash
curl -fsSL https://signoz.io/foundry.sh | bash
```
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`.
### 2. Keep your rollback path
Foundry has a [Docker Compose example](https://github.com/SigNoz/foundry/tree/main/docs/examples/docker/compose). Please use it as a reference.
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.
> [!WARNING]
> If your deployment had more than 1 shard or replica, you will need to adjust your manifest volumes accordingly.
> [!IMPORTANT]
> 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>
> 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.
```yaml
# casting.yaml
apiVersion: v1alpha1
kind: Installation
metadata:
@@ -89,8 +61,8 @@ spec:
data:
config-0-0.yaml: |
macros:
replica: "example01-01-1" # replace with your replica macro
shard: "01" # replace with your shard macro
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)
patches:
- target: "deployment/compose.yaml"
operations:
@@ -108,163 +80,50 @@ spec:
value: root
```
</details>
> [!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>
<summary><b>Docker Swarm</b> casting.yaml</summary>
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.
```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
```
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.
</details>
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.
> [!NOTE]
> 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.
> This will generate downtime so please plan accordingly.
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].
5. Validate the SigNoz containers are down with `docker ps -a`. Multiple containers cannot bind the same volume.
### 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
```
6. Run `foundryctl cast -f casting.yaml`. This will recreate the containers based on the spec. This process will download new container images.
> [!NOTE]
> This causes downtime, so plan accordingly.
> When `cast` is run, the migration container will execute its migrations.
Confirm nothing is still bound to the volumes before continuing:
## 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.
```bash
docker ps -a
```
## 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:
### 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.
- 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.
## Troubleshooting
If the migration runs into trouble, reach out on [Slack][slack] or open a
[Foundry issue][foundry-issues].
- Please reach out to our community on [Slack](https://signoz.io/slack).
## References
- [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
- [SigNoz Docker installation docs](https://signoz.io/docs/install/docker/)
- [SigNoz documentation](https://signoz.io/docs)
- [Foundry](https://github.com/SigNoz/foundry)

View File

@@ -4011,94 +4011,6 @@ 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:
@@ -4433,57 +4345,6 @@ components:
- total
- 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:
@@ -7207,6 +7068,19 @@ components:
required:
- items
type: object
SpantypesGettableSpanMapperTest:
properties:
collectorLogs:
items:
type: string
nullable: true
type: array
spans:
items:
$ref: '#/components/schemas/SpantypesSpanMapperTestSpan'
nullable: true
type: array
type: object
SpantypesGettableTraceAggregations:
properties:
aggregations:
@@ -7294,6 +7168,39 @@ components:
- name
- condition
type: object
SpantypesPostableSpanMapperTest:
properties:
groups:
items:
$ref: '#/components/schemas/SpantypesPostableSpanMapperTestGroup'
nullable: true
type: array
spans:
items:
$ref: '#/components/schemas/SpantypesSpanMapperTestSpan'
nullable: true
type: array
required:
- spans
- groups
type: object
SpantypesPostableSpanMapperTestGroup:
properties:
condition:
$ref: '#/components/schemas/SpantypesSpanMapperGroupCondition'
enabled:
type: boolean
mappers:
items:
$ref: '#/components/schemas/SpantypesPostableSpanMapper'
nullable: true
type: array
name:
type: string
required:
- name
- condition
type: object
SpantypesPostableTraceAggregations:
properties:
aggregations:
@@ -7455,6 +7362,17 @@ components:
- operation
- priority
type: object
SpantypesSpanMapperTestSpan:
properties:
attributes:
additionalProperties: {}
nullable: true
type: object
resource:
additionalProperties: {}
nullable: true
type: object
type: object
SpantypesUpdatableSpanMapper:
properties:
config:
@@ -13083,6 +13001,69 @@ paths:
summary: Update a span mapper
tags:
- spanmapper
/api/v1/span_mapper_groups/test:
post:
deprecated: false
description: Tests how span mappers would transform sample spans
operationId: TestSpanMappers
requestBody:
content:
application/json:
schema:
$ref: '#/components/schemas/SpantypesPostableSpanMapperTest'
responses:
"200":
content:
application/json:
schema:
properties:
data:
$ref: '#/components/schemas/SpantypesGettableSpanMapperTest'
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
"404":
content:
application/json:
schema:
$ref: '#/components/schemas/RenderErrorResponse'
description: Not Found
"500":
content:
application/json:
schema:
$ref: '#/components/schemas/RenderErrorResponse'
description: Internal Server Error
security:
- api_key:
- VIEWER
- tokenizer:
- VIEWER
summary: Test span mappers against sample spans
tags:
- spanmapper
/api/v1/stats:
get:
deprecated: false
@@ -14967,72 +14948,6 @@ 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

View File

@@ -15,8 +15,6 @@
"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"

View File

@@ -82,8 +82,6 @@
"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"

View File

@@ -0,0 +1,13 @@
#!/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

View File

@@ -0,0 +1,41 @@
#!/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"

View File

@@ -3,6 +3,7 @@ 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';
@@ -36,6 +37,7 @@ function PrivateRoute({ children }: PrivateRouteProps): JSX.Element {
activeLicense,
isFetchingActiveLicense,
trialInfo,
featureFlags,
} = useAppContext();
const isAdmin = user.role === USER_ROLES.ADMIN;
@@ -210,6 +212,14 @@ 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;

View File

@@ -2,6 +2,7 @@ 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';
@@ -1262,6 +1263,80 @@ 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({
@@ -1421,16 +1496,16 @@ describe('PrivateRoute', () => {
await assertRedirectsTo(ROUTES.UN_AUTHORIZED);
});
it('should allow EDITOR to access /get-started-with-signoz-cloud route', () => {
it('should allow EDITOR to access /get-started route', () => {
renderPrivateRoute({
initialRoute: ROUTES.GET_STARTED_WITH_CLOUD,
initialRoute: ROUTES.GET_STARTED,
appContext: {
isLoggedIn: true,
user: createMockUser({ role: USER_ROLES.EDITOR as ROLES }),
},
});
assertStaysOnRoute(ROUTES.GET_STARTED_WITH_CLOUD);
assertStaysOnRoute(ROUTES.GET_STARTED);
});
});

View File

@@ -90,6 +90,14 @@ 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'),
);

View File

@@ -33,6 +33,7 @@ import {
MeterExplorerPage,
MetricsExplorer,
OldLogsExplorer,
Onboarding,
OnboardingV2,
OrgOnboarding,
PasswordReset,
@@ -69,6 +70,13 @@ 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,

View File

@@ -4,22 +4,14 @@
* * regenerate with 'pnpm generate:api'
* SigNoz
*/
import { useMutation, useQuery } from 'react-query';
import { useMutation } from 'react-query';
import type {
InvalidateOptions,
MutationFunction,
QueryClient,
QueryFunction,
QueryKey,
UseMutationOptions,
UseMutationResult,
UseQueryOptions,
UseQueryResult,
} from 'react-query';
import type {
GetChecks200,
GetChecksParams,
InframonitoringtypesPostableClustersDTO,
InframonitoringtypesPostableDaemonSetsDTO,
InframonitoringtypesPostableDeploymentsDTO,
@@ -46,93 +38,6 @@ import type {
import { GeneratedAPIInstance } from '../../../generatedAPIInstance';
import type { ErrorType, BodyType } from '../../../generatedAPIInstance';
/**
* 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

View File

@@ -5458,121 +5458,6 @@ 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;
};
@@ -8345,6 +8230,48 @@ export interface SpantypesGettableSpanMapperGroupsDTO {
items: SpantypesSpanMapperGroupDTO[];
}
export type SpantypesSpanMapperTestSpanDTOAttributesAnyOf = {
[key: string]: unknown;
};
/**
* @nullable
*/
export type SpantypesSpanMapperTestSpanDTOAttributes =
SpantypesSpanMapperTestSpanDTOAttributesAnyOf | null;
export type SpantypesSpanMapperTestSpanDTOResourceAnyOf = {
[key: string]: unknown;
};
/**
* @nullable
*/
export type SpantypesSpanMapperTestSpanDTOResource =
SpantypesSpanMapperTestSpanDTOResourceAnyOf | null;
export interface SpantypesSpanMapperTestSpanDTO {
/**
* @type object,null
*/
attributes?: SpantypesSpanMapperTestSpanDTOAttributes;
/**
* @type object,null
*/
resource?: SpantypesSpanMapperTestSpanDTOResource;
}
export interface SpantypesGettableSpanMapperTestDTO {
/**
* @type array,null
*/
collectorLogs?: string[] | null;
/**
* @type array,null
*/
spans?: SpantypesSpanMapperTestSpanDTO[] | null;
}
export enum SpantypesSpanAggregationTypeDTO {
span_count = 'span_count',
execution_time_percentage = 'execution_time_percentage',
@@ -8640,6 +8567,33 @@ export interface SpantypesPostableSpanMapperGroupDTO {
name: string;
}
export interface SpantypesPostableSpanMapperTestGroupDTO {
condition: SpantypesSpanMapperGroupConditionDTO | null;
/**
* @type boolean
*/
enabled?: boolean;
/**
* @type array,null
*/
mappers?: SpantypesPostableSpanMapperDTO[] | null;
/**
* @type string
*/
name: string;
}
export interface SpantypesPostableSpanMapperTestDTO {
/**
* @type array,null
*/
groups: SpantypesPostableSpanMapperTestGroupDTO[] | null;
/**
* @type array,null
*/
spans: SpantypesSpanMapperTestSpanDTO[] | null;
}
export interface SpantypesSpanAggregationDTO {
aggregation: SpantypesSpanAggregationTypeDTO;
field: TelemetrytypesTelemetryFieldKeyDTO;
@@ -10021,6 +9975,14 @@ export type UpdateSpanMapperPathParameters = {
groupId: string;
mapperId: string;
};
export type TestSpanMappers200 = {
data: SpantypesGettableSpanMapperTestDTO;
/**
* @type string
*/
status: string;
};
export type GetStats200Data = { [key: string]: unknown };
export type GetStats200 = {
@@ -10344,21 +10306,6 @@ 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;
/**

View File

@@ -30,8 +30,10 @@ import type {
RenderErrorResponseDTO,
SpantypesPostableSpanMapperDTO,
SpantypesPostableSpanMapperGroupDTO,
SpantypesPostableSpanMapperTestDTO,
SpantypesUpdatableSpanMapperDTO,
SpantypesUpdatableSpanMapperGroupDTO,
TestSpanMappers200,
UpdateSpanMapperGroupPathParameters,
UpdateSpanMapperPathParameters,
} from '../sigNoz.schemas';
@@ -780,3 +782,86 @@ export const useUpdateSpanMapper = <
> => {
return useMutation(getUpdateSpanMapperMutationOptions(options));
};
/**
* Tests how span mappers would transform sample spans
* @summary Test span mappers against sample spans
*/
export const testSpanMappers = (
spantypesPostableSpanMapperTestDTO?: BodyType<SpantypesPostableSpanMapperTestDTO>,
signal?: AbortSignal,
) => {
return GeneratedAPIInstance<TestSpanMappers200>({
url: `/api/v1/span_mapper_groups/test`,
method: 'POST',
headers: { 'Content-Type': 'application/json' },
data: spantypesPostableSpanMapperTestDTO,
signal,
});
};
export const getTestSpanMappersMutationOptions = <
TError = ErrorType<RenderErrorResponseDTO>,
TContext = unknown,
>(options?: {
mutation?: UseMutationOptions<
Awaited<ReturnType<typeof testSpanMappers>>,
TError,
{ data?: BodyType<SpantypesPostableSpanMapperTestDTO> },
TContext
>;
}): UseMutationOptions<
Awaited<ReturnType<typeof testSpanMappers>>,
TError,
{ data?: BodyType<SpantypesPostableSpanMapperTestDTO> },
TContext
> => {
const mutationKey = ['testSpanMappers'];
const { mutation: mutationOptions } = options
? options.mutation &&
'mutationKey' in options.mutation &&
options.mutation.mutationKey
? options
: { ...options, mutation: { ...options.mutation, mutationKey } }
: { mutation: { mutationKey } };
const mutationFn: MutationFunction<
Awaited<ReturnType<typeof testSpanMappers>>,
{ data?: BodyType<SpantypesPostableSpanMapperTestDTO> }
> = (props) => {
const { data } = props ?? {};
return testSpanMappers(data);
};
return { mutationFn, ...mutationOptions };
};
export type TestSpanMappersMutationResult = NonNullable<
Awaited<ReturnType<typeof testSpanMappers>>
>;
export type TestSpanMappersMutationBody =
| BodyType<SpantypesPostableSpanMapperTestDTO>
| undefined;
export type TestSpanMappersMutationError = ErrorType<RenderErrorResponseDTO>;
/**
* @summary Test span mappers against sample spans
*/
export const useTestSpanMappers = <
TError = ErrorType<RenderErrorResponseDTO>,
TContext = unknown,
>(options?: {
mutation?: UseMutationOptions<
Awaited<ReturnType<typeof testSpanMappers>>,
TError,
{ data?: BodyType<SpantypesPostableSpanMapperTestDTO> },
TContext
>;
}): UseMutationResult<
Awaited<ReturnType<typeof testSpanMappers>>,
TError,
{ data?: BodyType<SpantypesPostableSpanMapperTestDTO> },
TContext
> => {
return useMutation(getTestSpanMappersMutationOptions(options));
};

View File

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

View File

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

View File

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

View File

@@ -2,7 +2,6 @@ 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;
@@ -11,18 +10,18 @@ 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 are not authorized</p>
<p className={styles.title}>
Uh-oh! You don&apos;t have permission to view this page.
</p>
<p className={styles.subtitle}>
<code className={styles.permission}>user/{user.id}</code> is not authorized
to perform <code className={styles.permission}>{permissionName}</code>
You need <code className={styles.permission}>{permissionName}</code> to
view this page. Please ask your SigNoz administrator to grant access.
</p>
</div>
</div>

View File

@@ -1,9 +1,7 @@
import { useCallback, useEffect, useState } from 'react';
import { Check, Copy, LockKeyhole } from '@signozhq/icons';
import { useCallback } from 'react';
import { 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';
@@ -48,23 +46,6 @@ 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 => {
@@ -112,17 +93,6 @@ 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>

View File

@@ -203,19 +203,6 @@
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;

View File

@@ -16,6 +16,7 @@ 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';
@@ -476,9 +477,15 @@ function ServiceAccountDrawer({
!isAccountLoading &&
!isAccountError &&
selectedAccountId && (
<>
{activeTab === ServiceAccountDrawerTab.Overview &&
(canRead && account ? (
<GuardAuthZ
relation="read"
object={`serviceaccount:${selectedAccountId}`}
fallbackOnNoPermissions={(): JSX.Element => (
<PermissionDeniedCallout permissionName="serviceaccount:read" />
)}
>
<>
{activeTab === ServiceAccountDrawerTab.Overview && account && (
<OverviewTab
account={account}
localName={localName}
@@ -497,24 +504,23 @@ function ServiceAccountDrawer({
onRefetchRoles={refetchRoles}
saveErrors={saveErrors}
/>
) : (
<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" />
))}
</>
)}
{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>
)}
</div>
</div>

View File

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

View File

@@ -7,6 +7,7 @@ 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',

View File

@@ -11,7 +11,14 @@ 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',
@@ -49,9 +56,7 @@ 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',

View File

@@ -413,8 +413,14 @@ 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;

View File

@@ -0,0 +1,29 @@
.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);
}
}
}

View File

@@ -0,0 +1,28 @@
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: '/',
};

View File

@@ -1,12 +1,10 @@
.members-settings-page {
.members-settings {
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;

View File

@@ -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>
</>
);
}

View File

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

View File

@@ -0,0 +1,106 @@
### 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
```
&nbsp;
### 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.
&nbsp;
Heres 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();
```
&nbsp;
The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, were 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"]
```

View File

@@ -0,0 +1,21 @@
Once you update your Dockerfile, you can build and run it using the commands below.
&nbsp;
### 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>
```

View File

@@ -0,0 +1,12 @@
## Setup OpenTelemetry Binary as an agent
&nbsp;
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/).
&nbsp;
Once you are done setting up the OTel collector binary, you can follow the next steps.
&nbsp;

View File

@@ -0,0 +1,101 @@
After setting up the Otel collector agent, follow the steps below to instrument your .NET Application
&nbsp;
&nbsp;
### 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
```
&nbsp;
### 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.
&nbsp;
Heres 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();
```
&nbsp;
The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, were 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.
&nbsp;
### 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"]
```

View File

@@ -0,0 +1,21 @@
Once you update your Dockerfile, you can build and run it using the commands below.
&nbsp;
### 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>
```

View File

@@ -0,0 +1,43 @@
### Install otel-collector in your Kubernetes infra
Add the SigNoz Helm Chart repository
```bash
helm repo add signoz https://charts.signoz.io
```
&nbsp;
If the chart is already present, update the chart to the latest using:
```bash
helm repo update
```
&nbsp;
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
```

View File

@@ -0,0 +1,65 @@
After setting up the Otel collector agent, follow the steps below to instrument your .NET Application
&nbsp;
&nbsp;
### 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
```
&nbsp;
### 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.
&nbsp;
Heres 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, were 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.

View File

@@ -0,0 +1,10 @@
&nbsp;
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.

View File

@@ -0,0 +1,71 @@
### 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
```
&nbsp;
### 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.
&nbsp;
Heres 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();
```
&nbsp;
The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, were 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.

View File

@@ -0,0 +1,10 @@
&nbsp;
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.

View File

@@ -0,0 +1,98 @@
## Setup OpenTelemetry Binary as an agent
&nbsp;
### 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
```
&nbsp;
### 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
```
&nbsp;
### 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]
```

View File

@@ -0,0 +1,67 @@
After setting up the Otel collector agent, follow the steps below to instrument your .NET Application
&nbsp;
&nbsp;
### 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
```
&nbsp;
### 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.
&nbsp;
Heres 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();
```
&nbsp;
The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, were 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.

View File

@@ -0,0 +1,18 @@
&nbsp;
Once you are done intrumenting your .NET application, you can run it using the below commands
&nbsp;
### 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
```
&nbsp;
### Step 2: Run your .NET application
```bash
dotnet build
dotnet run
```

View File

@@ -0,0 +1,70 @@
### 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
```
&nbsp;
### 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.
&nbsp;
Heres 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();
```
&nbsp;
The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, were 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.

View File

@@ -0,0 +1,10 @@
&nbsp;
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.

View File

@@ -0,0 +1,99 @@
## Setup OpenTelemetry Binary as an agent
&nbsp;
### 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
```
&nbsp;
### 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
```
&nbsp;
### 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]
```

View File

@@ -0,0 +1,68 @@
After setting up the Otel collector agent, follow the steps below to instrument your .NET Application
&nbsp;
&nbsp;
### 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
```
&nbsp;
### 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.
&nbsp;
Heres 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();
```
&nbsp;
The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, were 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.

View File

@@ -0,0 +1,18 @@
&nbsp;
Once you are done intrumenting your .NET application, you can run it using the below commands
&nbsp;
### 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
```
&nbsp;
### Step 2: Run your .NET application
```bash
dotnet build
dotnet run
```

View File

@@ -0,0 +1,70 @@
### 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
```
&nbsp;
### 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.
&nbsp;
Heres 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();
```
&nbsp;
The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, were 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.

View File

@@ -0,0 +1,10 @@
&nbsp;
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.

View File

@@ -0,0 +1,97 @@
## Setup OpenTelemetry Binary as an agent
&nbsp;
### 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
```
&nbsp;
### 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
```
&nbsp;
### 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]
```

View File

@@ -0,0 +1,67 @@
After setting up the Otel collector agent, follow the steps below to instrument your .NET Application
&nbsp;
&nbsp;
### 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
```
&nbsp;
### 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.
&nbsp;
Heres 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();
```
&nbsp;
The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, were 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.

View File

@@ -0,0 +1,18 @@
&nbsp;
Once you are done intrumenting your .NET application, you can run it using the below commands
&nbsp;
### 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
```
&nbsp;
### Step 2: Run your .NET application
```bash
dotnet build
dotnet run
```

View File

@@ -0,0 +1,70 @@
### 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
```
&nbsp;
### 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.
&nbsp;
Heres 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();
```
&nbsp;
The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, were 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.

View File

@@ -0,0 +1,10 @@
&nbsp;
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.

View File

@@ -0,0 +1,98 @@
## Setup OpenTelemetry Binary as an agent
&nbsp;
### 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
```
&nbsp;
### 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
```
&nbsp;
### 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]
```

View File

@@ -0,0 +1,68 @@
After setting up the Otel collector agent, follow the steps below to instrument your .NET Application
&nbsp;
&nbsp;
### 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
```
&nbsp;
### 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.
&nbsp;
Heres 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();
```
&nbsp;
The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, were 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.

View File

@@ -0,0 +1,18 @@
&nbsp;
Once you are done intrumenting your .NET application, you can run it using the below commands
&nbsp;
### 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
```
&nbsp;
### Step 2: Run your .NET application
```bash
dotnet build
dotnet run
```

View File

@@ -0,0 +1,67 @@
**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.
Heres 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.

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@@ -0,0 +1,10 @@
&nbsp;
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.

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@@ -0,0 +1,12 @@
## Setup OpenTelemetry Binary as an agent
&nbsp;
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/).
&nbsp;
Once you are done setting up the OTel collector binary, you can follow the next steps.
&nbsp;

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@@ -0,0 +1,63 @@
After setting up the Otel collector agent, follow the steps below to instrument your .NET Application
&nbsp;
&nbsp;
### 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
```
&nbsp;
### 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:
&nbsp;
Heres 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();
```
&nbsp;
The OpenTelemetry.Exporter.Options get or set the target to which the exporter is going to send traces. Here, were 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.

View File

@@ -0,0 +1,18 @@
&nbsp;
Once you are done intrumenting your .NET application, you can run it using the below commands
&nbsp;
### 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
```
&nbsp;
### Step 2: Run your .NET application
```bash
dotnet build
dotnet run
```

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@@ -0,0 +1,67 @@
&nbsp;
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"}
```
&nbsp;
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])
```
&nbsp;
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
```
&nbsp;
### 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}} }
]
}
}
}
```
&nbsp;
### 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.

View File

@@ -0,0 +1,25 @@
Once you update your Dockerfile, you can build and run it using the commands below.
&nbsp;
### 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)

View File

@@ -0,0 +1,12 @@
## Setup OpenTelemetry Binary as an agent
&nbsp;
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/).
&nbsp;
Once you are done setting up the OTel collector binary, you can follow the next steps.
&nbsp;

View File

@@ -0,0 +1,61 @@
&nbsp;
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"}
```
&nbsp;
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])
```
&nbsp;
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
```
&nbsp;
### 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"]}
}
}
```
&nbsp;
### 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.

View File

@@ -0,0 +1,25 @@
Once you update your Dockerfile, you can build and run it using the commands below.
&nbsp;
### 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)

View File

@@ -0,0 +1,43 @@
### Install otel-collector in your Kubernetes infra
Add the SigNoz Helm Chart repository
```bash
helm repo add signoz https://charts.signoz.io
```
&nbsp;
If the chart is already present, update the chart to the latest using:
```bash
helm repo update
```
&nbsp;
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
```

View File

@@ -0,0 +1,57 @@
&nbsp;
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"}
```
&nbsp;
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])
```
&nbsp;
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
```
&nbsp;
### 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"]}
}
}
```

View File

@@ -0,0 +1,6 @@
### 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)

View File

@@ -0,0 +1,62 @@
&nbsp;
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"}
```
&nbsp;
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])
```
&nbsp;
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
```
&nbsp;
### 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}} }
]
}
}
}
```

View File

@@ -0,0 +1,6 @@
### 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)

View File

@@ -0,0 +1,96 @@
## Setup OpenTelemetry Binary as an agent
&nbsp;
### 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
```
&nbsp;
### 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
```
&nbsp;
### 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]
```

View File

@@ -0,0 +1,57 @@
&nbsp;
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"}
```
&nbsp;
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])
```
&nbsp;
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
```
&nbsp;
### 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"]}
}
}
```

View File

@@ -0,0 +1,29 @@
&nbsp;
### 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 "$!" > otel-pid
```
&nbsp;
#### (Optional Step): View last 50 lines of `otelcol` logs
```bash
tail -f -n 50 otelcol-output.log
```
#### (Optional Step): Stop `otelcol`
```bash
kill "$(< 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)
```

View File

@@ -0,0 +1,62 @@
&nbsp;
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"}
```
&nbsp;
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])
```
&nbsp;
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
```
&nbsp;
### 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}} }
]
}
}
}
```

View File

@@ -0,0 +1,6 @@
### 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)

View File

@@ -0,0 +1,96 @@
## Setup OpenTelemetry Binary as an agent
&nbsp;
### 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
```
&nbsp;
### 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
```
&nbsp;
### 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]
```

View File

@@ -0,0 +1,57 @@
&nbsp;
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"}
```
&nbsp;
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])
```
&nbsp;
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
```
&nbsp;
### 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"]}
}
}
```

View File

@@ -0,0 +1,28 @@
&nbsp;
### 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 "$!" > otel-pid
```
&nbsp;
#### (Optional Step): View last 50 lines of `otelcol` logs
```bash
tail -f -n 50 otelcol-output.log
```
#### (Optional Step): Stop `otelcol`
```bash
kill "$(< 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)
```

View File

@@ -0,0 +1,62 @@
&nbsp;
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"}
```
&nbsp;
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])
```
&nbsp;
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
```
&nbsp;
### 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}} }
]
}
}
}
```

View File

@@ -0,0 +1,6 @@
### 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)

View File

@@ -0,0 +1,96 @@
### Setup OpenTelemetry Binary as an agent
&nbsp;
### 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
```
&nbsp;
### 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
```
&nbsp;
### 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]
```

View File

@@ -0,0 +1,57 @@
&nbsp;
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"}
```
&nbsp;
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])
```
&nbsp;
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
```
&nbsp;
### 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"]}
}
}
```

View File

@@ -0,0 +1,28 @@
&nbsp;
### 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 "$!" > otel-pid
```
&nbsp;
#### (Optional Step): View last 50 lines of `otelcol` logs
```bash
tail -f -n 50 otelcol-output.log
```
#### (Optional Step): Stop `otelcol`
```bash
kill "$(< 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)
```

View File

@@ -0,0 +1,62 @@
&nbsp;
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"}
```
&nbsp;
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])
```
&nbsp;
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
```
&nbsp;
### 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}} }
]
}
}
}
```

View File

@@ -0,0 +1,6 @@
### 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)

View File

@@ -0,0 +1,96 @@
## Setup OpenTelemetry Binary as an agent
&nbsp;
### 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
```
&nbsp;
### 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
```
&nbsp;
### 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]
```

View File

@@ -0,0 +1,57 @@
&nbsp;
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"}
```
&nbsp;
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])
```
&nbsp;
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
```
&nbsp;
### 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"]}
}
}
```

View File

@@ -0,0 +1,28 @@
&nbsp;
### 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 "$!" > otel-pid
```
&nbsp;
#### (Optional Step): View last 50 lines of `otelcol` logs
```bash
tail -f -n 50 otelcol-output.log
```
#### (Optional Step): Stop `otelcol`
```bash
kill "$(< 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)
```

View File

@@ -0,0 +1,62 @@
&nbsp;
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"}
```
&nbsp;
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])
```
&nbsp;
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
```
&nbsp;
### 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}} }
]
}
}
}
```

View File

@@ -0,0 +1,6 @@
### 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)

View File

@@ -0,0 +1,105 @@
## Setup OpenTelemetry Binary as an agent
&nbsp;
### Step 1: Download otel-collector tar.gz
&nbsp;
```bash
wget https://github.com/open-telemetry/opentelemetry-collector-releases/releases/download/v{{OTEL_VERSION}}/otelcol-contrib_{{OTEL_VERSION}}_linux_amd64.tar.gz
```
&nbsp;
### Step 2: Extract otel-collector tar.gz to the `otelcol-contrib` folder
&nbsp;
```bash
mkdir otelcol-contrib && tar xvzf otelcol-contrib_{{OTEL_VERSION}}_linux_amd64.tar.gz -C otelcol-contrib
```
&nbsp;
### Step 3: Create config.yaml in folder otelcol-contrib with the below content in it
&nbsp;
```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]
```

View File

@@ -0,0 +1,57 @@
&nbsp;
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"}
```
&nbsp;
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])
```
&nbsp;
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
```
&nbsp;
### 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"]}
}
}
```

View File

@@ -0,0 +1,55 @@
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"]}
}
}
```

View File

@@ -0,0 +1,414 @@
## 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.

View File

@@ -0,0 +1,135 @@
### 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).
&nbsp;
&nbsp;
### 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")
)
```
&nbsp;
### 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
}
```
&nbsp;
### 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())
......
}
```
&nbsp;
### 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))
......
}
```
&nbsp;
### 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
...
```

View File

@@ -0,0 +1,21 @@
Once you update your Dockerfile, you can build and run it using the commands below.
&nbsp;
### 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>
```

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