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Overview

Applying OpenTelemetry traces to the concept of workflows allows you to monitor the execution of your jobs and their individual tasks. Visualizing the trace for a job in a tool like Axiom may look like this:
Tilebox Workflows tracing in AxiomTilebox Workflows tracing in Axiom
Tracing your workflows enables you to easily observe:
  • The order of task execution
  • Which tasks run in parallel
  • The task runner handling each task
  • The duration of each task
  • The outcome of each task (success or failure)
This information helps identify bottlenecks and performance issues, ensuring that your workflows execute correctly.

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Configure tracing

The Tilebox workflow SDKs have built-in support for exporting OpenTelemetry traces. To enable tracing, call the appropriate configuration functions during the startup of your task runner.
To configure tracing with Axiom, you first need to create a Axiom Dataset to export your workflow traces to. You will also need an Axiom API key with the necessary write permissions for your Axiom dataset.
from tilebox.workflows import Client
from tilebox.workflows.observability.tracing import configure_otel_tracing_axiom

# your own workflow:
from my_workflow import MyTask

def main():
    configure_otel_tracing_axiom(
        # specify an Axiom dataset to export traces to
        dataset="my-axiom-traces-dataset",
        # along with an Axiom API key for ingest permissions
        api_key="my-axiom-api-key",
    )

    # the following task runner generates traces for executed tasks and
    # exports trace and span data to the specified Axiom dataset
    client = Client()
    runner = client.runner(tasks=[MyTask])
    runner.run_forever()

if __name__ == "__main__":
    main()
Set the environment variables AXIOM_API_KEY and AXIOM_TRACES_DATASET to omit those arguments in the configure_otel_tracing_axiom function.
Once the runner picks up tasks and executes them, corresponding traces and spans are automatically generated and exported to the configured backend.