https://github.com/grafana/docker-otel-lgtm
OpenTelemetry backend in a Docker image
https://github.com/grafana/docker-otel-lgtm
grafana opentelemetry opetelemetry-collector prometheus
Last synced: 17 days ago
JSON representation
OpenTelemetry backend in a Docker image
- Host: GitHub
- URL: https://github.com/grafana/docker-otel-lgtm
- Owner: grafana
- License: apache-2.0
- Created: 2023-09-26T12:21:12.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-01T13:37:23.000Z (24 days ago)
- Last Synced: 2025-04-01T14:50:03.148Z (24 days ago)
- Topics: grafana, opentelemetry, opetelemetry-collector, prometheus
- Language: Shell
- Homepage:
- Size: 1.05 MB
- Stars: 902
- Watchers: 16
- Forks: 94
- Open Issues: 8
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
README
# docker-otel-lgtm
An OpenTelemetry backend in a Docker image.
The `grafana/otel-lgtm` Docker image is an open source backend for OpenTelemetry that’s intended for development, demo,
and testing environments.
If you are looking for a production-ready, out-of-the box solution to monitor applications and minimize
MTTR (mean time to resolution) with OpenTelemetry and Prometheus,
you should try [Grafana Cloud Application Observability](https://grafana.com/products/cloud/application-observability/).
## Documentation
- Blog post: [An OpenTelemetry backend in a Docker image: Introducing grafana/otel-lgtm](https://grafana.com/blog/2024/03/13/an-opentelemetry-backend-in-a-docker-image-introducing-grafana/otel-lgtm/)
## Get the Docker image
The Docker image is available on Docker hub:
## Run the Docker image
```sh
# Unix/Linux
./run-lgtm.sh
# Windows (PowerShell)
./run-lgtm
# Using mise (Unix/Linux)
mise run lgtm
```
## Configuration
### Enable logging
You can enable logging for troubleshooting:
| Environment Variable | Enable Logging in |
| ---------------------- | ----------------------- |
| ENABLE_LOGS_GRAFANA | Grafana |
| ENABLE_LOGS_LOKI | Loki |
| ENABLE_LOGS_PROMETHEUS | Prometheus |
| ENABLE_LOGS_TEMPO | Tempo |
| ENABLE_LOGS_OTELCOL | OpenTelemetry Collector |
| ENABLE_LOGS_ALL | all of the above |
This has nothing to do with the application logs, which are collected by OpenTelemetry.
### Send data to vendors
In addition to the built-in observability tools, you can also send data to vendors.
That way, you can easily try and switch between different backends.
If the [OTEL_EXPORTER_OTLP_ENDPOINT](https://opentelemetry.io/docs/languages/sdk-configuration/otlp-exporter/#otel_exporter_otlp_endpoint)
variable is set, the OpenTelemetry Collector will send data (logs, metrics, and traces) to the specified endpoint using "OTLP/HTTP".
In addition, you can provide
[OTEL_EXPORTER_OTLP_HEADERS](https://opentelemetry.io/docs/languages/sdk-configuration/otlp-exporter/#otel_exporter_otlp_headers),
for example, to authenticate with the backend.
#### Send data to Grafana Cloud
You can find the values for the environment variables in your
[Grafana Cloud account](https://grafana.com/docs/grafana-cloud/send-data/otlp/send-data-otlp/#manual-opentelemetry-setup-for-advanced-users).
### Persist data across container instantiation
The various components in the repository are configured to write their data to the /data
directory. If you need to persist data across containers being created and destroyed,
you can mount a volume to the /data directory. Note that this image is intended for
development, demo, and testing environments and persisting data to an external volume
doesn't change that. However, this feature could be useful in certain cases for
some users even in testing situations.
## Run lgtm in kubernetes
```sh
# create k8s resources
kubectl apply -f k8s/lgtm.yaml
# port forwarding
kubectl port-forward service/lgtm 3000:3000 4317:4317 4318:4318
# Using mise
mise k8s-apply
mise k8s-port-forward
```
## Send OpenTelemetry Data
There's no need to configure anything: The Docker image works with OpenTelemetry's defaults.
```sh
# Not needed as these are the defaults in OpenTelemetry:
export OTEL_EXPORTER_OTLP_PROTOCOL=http/protobuf
export OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4318
```
## View Grafana
Log in to [http://localhost:3000](http://localhost:3000) with user _admin_ and password _admin_.
## Build the Docker image from scratch
```sh
cd docker/
docker build . -t grafana/otel-lgtm
# Using mise
mise build-lgtm
```
## Build and run the example app
> **_NOTE:_** You can run everything together using [mise](https://mise.jdx.dev/) with `mise run all`
Run the example REST service:
```sh
# Unix/Linux
./run-example.sh
# Windows (PowerShell)
./run-example
# Using mise (Unix/Linux)
mise run example
```
Generate traffic:
```sh
# Unix/Linux
./generate-traffic.sh
# Windows (PowerShell)
./generate-traffic
# Using mise (Unix/Linux)
mise run generate-traffic
```
> **_NOTE:_** You can use [OTel Checker](https://github.com/grafana/otel-checker/) to check if the instrumentation is correct.
## Run example apps in different languages
The example apps are in the `examples/` directory.
Each example has a `run.sh` or `run.cmd` script to start the app.
Every example implements a rolldice service, which returns a random number between 1 and 6.
Each example uses a different application port (to be able to run all applications at the same time).
| Example | Service URL |
| ------- | ------------------------------------- |
| Java | `curl http://localhost:8080/rolldice` |
| Go | `curl http://localhost:8081/rolldice` |
| Python | `curl http://localhost:8082/rolldice` |
| dotnet | `curl http://localhost:8083/rolldice` |
## Related Work
- Metrics, Logs, Traces and Profiles in Grafana: