DEVOPS
Weekly DORA Scorecard from GitLab Pipelines to BigQuery
Every Monday, pulls the past week of GitLab pipelines and merge requests, computes deploy frequency and lead-time-for-changes per team.
How it runs
The automated pipeline, trigger to output.
- TriggerMonday 06:00 weekly schedule
- ActionFetch trailing-7-day pipelines and merged MRsGitLab
- LogicAggregate deploy frequency and lead time per team
- LogicDrop teams with zero deploys
- OutputAppend dated scorecard rows to BigQueryBigQuery
What it does
This workflow compiles two of the four DORA metrics — deployment frequency and lead time for changes — for each engineering team and lands them in a warehouse table you can chart over time.
When to use it
Run it when leadership wants a defensible, automated weekly read on delivery throughput instead of hand-built spreadsheets. Ideal once you have GitLab as the source of truth for CI/CD and BigQuery as your metrics warehouse.
How it works
- 1A Monday 06:00 schedule fires the run.
- 2It calls the GitLab API for all pipelines and merged MRs in the trailing 7 days across the configured group.
- 3A compute step groups records by the team label on each project, counts production deploys (deploy frequency), and measures hours from first commit to deploy (lead time), emitting per-team aggregates.
- 4A filter drops teams with zero deploys so empty rows do not skew dashboards.
- 5The final step appends one dated row per team to the BigQuery `dora_team_scorecard` table, ready for Looker or scheduled queries.
Set it up
What you configure once, before turning it on.
- 1Connect GitLabRepos, MRs, pipelines, registry.
- 2Connect BigQueryDatasets, queries, schemas.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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