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A demonstration application to help with exploring Observability best practice including SLI's, SLO's, and Error Budgets

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observability-demo-app

A basic Python Flask application that randomly returns an HTTP error for 25% of queries.

By default, this works in AWS only and is configured to use X-Ray and Prometheus.

Prometheus should scrape the /metrics endpoint of this application

Getting up and running

  1. Create a virtualenv
  2. Activate the virtualenv
  3. Install the requirements: pip install -r requirements.txt
  4. Set the OBSDEMO_OTLP_ENDPOINT environment variable to point to your OTLP collector
  5. Set the OBSDEMO_APP_SECRET environment variable to the value you want to use for your app secret key
  6. Assuming you're running in AWS, set OTEL_PROPAGATORS=xray to send traces to XRay
  7. Alternatively, copy .env.sample to .env, update the values, and source it to setup the environment
  8. Run the app python demo.py

The app is now available at http://localhost:5000/, with metrics at http://localhost:5000/metrics.

Point Prometheus at the /metrics endpoint, and then launch something like apache bench against the root:

ab -n 5000000 -c 5 http://localhost:5000/

Dashboards

Once the Prometheus data is flowing, you can hook Grafana up and use this dashboard to view the data.

The Grafana Dashboard

AWS X-Ray

Whilst the traces aren't anything particularly special, they will prove whether your X-Ray setup is working.

Make sure that AWS OpenTelemetry Collector is running somewhere, then update the OBSDEMO_OTEL_ENDPOINT to point to that location. As long as your IAM policies are correct, your traces should start to show up in X-Ray

The AWS X-Ray Dashboard

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A demonstration application to help with exploring Observability best practice including SLI's, SLO's, and Error Budgets

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