DEVOPS

Daily DORA scorecard from GitLab merges + Honeycomb deploys

Each morning, joins yesterday's GitLab MR merge events with Honeycomb deploy markers to compute per-team deploy frequency and change lead time.

CategoryDevOps
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily 7am schedule (prior 24h window)
  • ActionFetch merged MRs from GitLabGitLabGitLab
  • ActionFetch deploy markers from HoneycombHoneycomb
  • LogicJoin markers to MRs by SHA, compute lead time + deploy counts
  • ActionAppend scorecard rows to BigQueryGoogle BigQueryBigQuery
  • OutputPost per-team digest to SlackSlack

What it does

Produces a daily, per-team DORA scorecard for the two flow metrics: deployment frequency and change lead time. It pairs each merged GitLab merge request with the Honeycomb deploy marker that shipped it, derives lead time (merge to deploy), counts deploys per team, persists the rows to BigQuery, and drops a readable summary in Slack.

When to use it

Run this when engineering leadership wants a trustworthy daily pulse on delivery throughput without anyone hand-assembling spreadsheets. Ideal for orgs that merge in GitLab and emit deploy markers to Honeycomb but lack a unified DORA view.

How it works

  1. 1A scheduled trigger fires at 7am for the prior 24-hour window.
  2. 2Pull merged MRs from GitLab, tagging each with its owning team via project-to-team mapping.
  3. 3Pull Honeycomb deploy markers for the same window.
  4. 4Logic step joins markers to MRs by commit SHA and computes per-MR lead time and per-team deploy counts.
  5. 5Append the computed scorecard rows to a BigQuery DORA table for history.
  6. 6Post the formatted per-team digest to Slack.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GitLabRepos, MRs, pipelines, registry.
  2. 2
    Connect HoneycombDistributed traces and queries.
  3. 3
    Connect BigQueryDatasets, queries, schemas.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

14-day trial. No DevOps. No Sales call. Provisioned in under a minute.