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Important: This documentation is about an older version. It's relevant only to the release noted, many of the features and functions have been updated or replaced. Please view the current version.

Open source

Sometimes using a tracing system is intimidating because it seems like you need complex application instrumentation or a span ingestion pipeline in order to push spans. This guide aims to show an extremely basic technique for pushing spans with http/json from a Bash script using the Zipkin receiver.

Starting Tempo

Let’s first start Tempo with the Zipkin receiver configured. In order to do this create a config file like so:

yaml
server:
  http_listen_port: 3200

distributor:
  receivers:
    zipkin:

storage:
  trace:
    backend: local
    local:
      path: /tmp/tempo/blocks

and run Tempo using it:

bash
docker run -p 9411:9411 -p 3200:3200 -v $(pwd)/config.yaml:/config.yaml grafana/tempo:latest -config.file /config.yaml

Pushing Spans

Now that Tempo is running and listening on port 9411 for Zipkin spans let’s push a span to it using curl.

bash
curl -X POST http://localhost:9411 -H 'Content-Type: application/json' -d '[{
 "id": "1234",
 "traceId": "0123456789abcdef",
 "timestamp": 1608239395286533,
 "duration": 100000,
 "name": "span from bash!",
 "tags": {
    "http.method": "GET",
    "http.path": "/api"
  },
  "localEndpoint": {
    "serviceName": "shell script"
  }
}]'

Note that the timestamp field is in microseconds and was obtained by running date +%s%6N. The duration field is also in microseconds and so 100000 is 100 milliseconds.

Retrieving Traces

The easiest way to get the trace is to execute a simple curl command to Tempo. The returned format is OTLP.

bash
curl http://localhost:3200/api/traces/0123456789abcdef

{"batches":[{"resource":{"attributes":[{"key":"service.name","value":{"stringValue":"shell script"}}]},"instrumentationLibrarySpans":[{"spans":[{"traceId":"AAAAAAAAAAABI0VniavN7w==","spanId":"AAAAAAAAEjQ=","name":"span from bash!","startTimeUnixNano":"1608239395286533000","endTimeUnixNano":"1608239395386533000","attributes":[{"key":"http.path","value":{"stringValue":"/api"}},{"key":"http.method","value":{"stringValue":"GET"}}]}]}]}]}

However, staring at a json blob in bash is not very fun. Let’s start up Tempo query so we can visualize our trace. Tempo query is Jaeger Query with a GRPC Plugin that allows it to query Tempo.

bash
docker run --env BACKEND=localhost:3200 --net host grafana/tempo-query:latest

And open http://localhost:16686/trace/0123456789abcdef in the browser of your choice to see:

single span

More Spans!

Now that we have the basics down it’s easy to continue building our trace. By specifying the same trace id and a parent span id we can start building a trace.

bash
curl -X POST http://localhost:9411 -H 'Content-Type: application/json' -d '[{
 "id": "5678",
 "traceId": "0123456789abcdef",
 "parentId": "1234",
 "timestamp": 1608239395316533,
 "duration": 100000,
 "name": "child span from bash!",
  "localEndpoint": {
    "serviceName": "shell script"
  }
}]'

And now the UI shows:

parent and child spans

Spans from everything!

Tracing is not limited to enterprise languages with complex frameworks. As you can see it’s easy to store and track events from your js, python or bash scripts. You can use Tempo/distributed tracing today to trace CI pipelines, long running bash processes, python data processing flows or anything else you can think of.

Happy tracing!