Google Cloud Spanner Query-Level Metrics#24565
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- Add metadata.csv with 10 spanner.queries.* metrics - Add assets/service_checks.json (empty) - Add assets/configuration/spec.yaml with full config schema - Generate conf.yaml.example and config_models/ via ddev - Update manifest.json: add app_uuid, owner, fix metrics prefix to spanner.* - Update pyproject.toml Development Status from Alpha to Beta - Add README.md with beta notice, setup instructions, and tile sections - Fix ruff formatting across all Python files in the integration Environment: Datadog workspace Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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What does this PR do?
This introduces a new integration:
cloud_spanner. This integration adds query-level metrics for Spanner databases by connecting to the DB and querying tables in theSPANNER_SYSschema.This integration should be seen as experimental until otherwise communicated.
Motivation
Today, Datadog collects various metrics for Spanner databases, but it does it via the GCP API. This limits what data is available. For example, query metrics are aggregated across all queries, and a per-query breakdown is not supported.
Query-Level Metrics are a staple of Database Monitoring, so we can support a Database Monitoring experience for Spanner by collecting and sending them.
Review checklist (to be filled by reviewers)
qa/requiredif this PR needs QA validation, orqa/skip-qaif it does not. Exactly one of the two is required.backport/<branch-name>label to the PR and it will automatically open a backport PR once this one is merged