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- Deploy Grafana Tempo in monolithic mode for distributed tracing
- Configure Tempo with OTLP receivers (gRPC:4317, HTTP:4318)
- Set up 10Gi filesystem storage with 7-day retention
- Integrate Tempo datasource in Grafana with traces-to-logs and traces-to-metrics correlation
- Update Grafana Alloy to collect and forward traces
- Add OTLP receiver configuration to alloy-values.yaml
- Configure batch processor for efficient trace forwarding to Tempo
- Patch Alloy service to expose OTLP ports 4317/4318
- Create demo tracing application (frontend, middleware, backend)
- Implement three-tier Python Flask application with OpenTelemetry instrumentation
- Auto-instrument with OpenTelemetry for Flask and requests libraries
- Push Docker images to private registry (registry.lan.buetow.org:30001)
- Deploy via Helm chart with Traefik ingress at tracing-demo.f3s.buetow.org
- Update Grafana configuration in prometheus/persistence-values.yaml
- Add Tempo to additionalDataSources for automatic provisioning
Files added:
- tempo/values.yaml: Tempo Helm chart configuration
- tempo/persistent-volumes.yaml: Storage configuration (10Gi PV/PVC)
- tempo/datasource-configmap.yaml: Grafana datasource with correlations
- tempo/Justfile: Installation automation
- tempo/README.md: Documentation
- tracing-demo/docker/frontend/: Python Flask frontend with OTel
- tracing-demo/docker/middleware/: Python Flask middleware with OTel
- tracing-demo/docker/backend/: Python Flask backend with OTel
- tracing-demo/helm-chart/: Kubernetes deployments, services, ingress
- tracing-demo/docker-image-Justfile: Docker build/push automation
- tracing-demo/Justfile: Helm deployment automation
- tracing-demo/README.md: Documentation
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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