DEVOPS
Per-Deploy Lead-Time Tracker to Datadog Metrics
On every successful GitLab production deployment, calculates lead time for changes for that deploy and ships it as a tagged custom metric to Datadog for real-time DORA monitoring…
How it runs
The automated pipeline, trigger to output.
- TriggerGitLab deployment-success webhookGitLab
- LogicFilter to production environment only
- ActionLook up MR and commit history for the deployGitLab
- LogicCompute lead-time minutes and deploy count
- OutputSubmit tagged DORA custom metrics to DatadogDatadog
What it does
This turns each production deploy into a live DORA data point. As pipelines finish, it measures how long the change took from first commit to release and streams that as a Datadog metric tagged by team and service.
When to use it
Use it when you want continuous, per-deploy DORA telemetry rather than a weekly batch — for example to alert when a team's rolling lead time drifts past an SLO, or to overlay delivery speed on incident dashboards.
How it works
- 1A GitLab pipeline webhook fires when a deployment job succeeds.
- 2A filter confirms the job targeted the production environment and ignores staging or review apps.
- 3An action queries the GitLab API for the merge request and commit history behind the deploy to find the first-commit timestamp.
- 4A compute step derives lead-time-in-minutes and a deploy-count of one for this event.
- 5The output step submits both as Datadog custom metrics (`dora.lead_time`, `dora.deploys`) tagged with team and service, where monitors and dashboards pick them up instantly.
Set it up
What you configure once, before turning it on.
- 1Connect GitLabRepos, MRs, pipelines, registry.
- 2Connect DatadogMetrics, traces, log search.
- 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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