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Contributing

Thanks for your interest in improving this project! It's a focused demo of a real-time GPU efficiency anomaly-detection pattern on Confluent Cloud, so contributions that sharpen the pattern, the documentation, or the developer experience are especially welcome.

Ways to contribute

  • Bugs / inaccuracies — open an issue (especially anything where the Flink SQL, schema, or Terraform doesn't match current Confluent Cloud behavior).
  • Docs — clarity on the synthetic-vs-production story, the schema provenance, or setup.
  • Roadmap items — see the Roadmap section of the README (multi-deployment, physically-correlated synthetic data, the OpenTelemetry Collector production source).

Development setup

uv sync            # create the environment
uv run pytest -q   # run the test suite
uv run ruff check .
terraform -chdir=terraform fmt -recursive
terraform -chdir=terraform init -backend=false && terraform -chdir=terraform validate

Before you open a PR

  • uv run ruff check . is clean.
  • uv run pytest -q passes.
  • terraform fmt and terraform validate pass.
  • No secrets. Credentials go in terraform/terraform.tfvars (gitignored) or TF_VAR_* environment variables — never in tracked files. CI runs a gitleaks scan.
  • Commits are small, atomic, and use Conventional Commits (feat:, fix:, docs:, chore:, …) in English.

By contributing, you agree that your contributions are licensed under the Apache-2.0 license.