split observability stack into two modes

[skudasov]

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Below is a summarization created by an LLM (gpt-4-0125-preview). Be mindful of hallucinations and verify accuracy.

Why

The changes introduce enhancements and new features to the observability stack command options in a CLI tool, improving flexibility and coverage of observability tools for local development environments. Specifically, it adds a "full" mode to include additional services for more comprehensive monitoring and introduces a new dummy dashboard file for local testing.

What

• book/src/framework/observability/observability_stack.md

  • Added descriptions for default and full observability stack modes including services like Prometheus, Loki, Cadvisor, and more.
  • Introduced new CLI commands for starting, removing, and restarting the observability stack in default and full modes.

• framework/cmd/main.go

  • Modified the observability command to include flags for a "full" stack option, allowing users to choose between a standard and a more comprehensive set of observability tools.
  • Updated help and usage descriptions to reflect the new command options.

• framework/observability.go

  • Implemented two separate functions ObservabilityUp and ObservabilityUpFull to handle the setup of the default and full observability stacks, respectively.
  • Added detailed log information post-setup to inform the user about the URLs of various observability interfaces.

• framework/observability/compose/docker-compose.yaml

  • Made adjustments to the docker-compose file to support the conditional inclusion of additional services (like Cadvisor, Tempo, and PostgreSQL exporters) when the full stack is deployed.
  • Removed a dependency on the "tempo" service from the "grafana" service to align with conditional deployment strategies.

• framework/observability/dashboards/dummy.json

  • Added a new dummy dashboard json file for local testing purposes, ensuring that dashboard embedding capabilities can be tested without requiring a full set of real observability data.