GitLab Tutorial
- 1. Introduction to GitLab
- 2. Architecture & Self-Hosting
- 3. Groups, Projects & Namespaces
- 4. Issue Tracking & Agile
- 5. GitLab CI/CD Basics
- 6. GitLab Runners & Executors
- 7. Environments & Deployments
- 8. Merge Requests & Code Review
- 9. GitLab Container Registry
- 10. Package & Infra Registry
- 11. Security & Compliance
- 12. Monitoring & Analytics (DORA)
- 13. GitLab Pages Hosting
- 14. APIs, Webhooks & Integrations
- 15. GitLab Workflow & Best Practices
12. Monitoring & Analytics (DORA)
To improve, you must measure. Understanding the bottlenecks in your development cycle—how long an issue stays in "To Do," how long it takes to review a merge request, and how frequently you deploy to production—is vital for team efficiency. GitLab includes comprehensive dashboards for DevOps Analytics and industry-standard DORA Metrics.
Value Stream Analytics
GitLab Value Stream Analytics visualizes the lifecycle of your product development from planning to delivery. It automatically tracks seven core developmental stages:
- Issue: Time taken from creating an issue to adding a label or adding it to a milestone.
- Plan: Time from planning an issue to creating a corresponding branch or merge request.
- Code: Time between the first commit and creating the merge request.
- Test: Pipeline duration running your automated test suites.
- Review: Time from creating the merge request to merging the branch.
- Staging: Time from merging the code to deploying it to staging/production.
- Total Lead Time: The total duration from planning to deployment!
By auditing these metrics, management can identify key team bottlenecks, such as a lengthy code review process or slow automated testing pipelines.
Understanding DORA Metrics
DevOps Research and Assessment (DORA) metrics are the gold standard for measuring a team's software delivery performance. GitLab tracks these four core DORA metrics natively:
| DORA Metric | What does it measure? | Why is it important? |
|---|---|---|
| Deployment Frequency | How often code is successfully deployed to production (daily, weekly, monthly). | Indicates team agility, small release batches, and high deployment confidence. |
| Lead Time for Changes | The amount of time it takes for a commit to go from source code to production. | Measures overall development throughput and pipeline execution efficiency. |
| Change Failure Rate | The percentage of deployments to production that fail or require rollbacks. | Indicates the quality of your testing suites, code reviews, and release processes. |
| Time to Restore Service | How long it takes the team to recover from a production outage or regression. | Measures infrastructure resilience, alerting speed, and rollback capabilities. |
Accessing Pipeline Analytics
For individual developers and DevOps engineering leads, GitLab offers specialized pipeline analytics. Under Analyze > CI/CD Analytics in your project sidebar, you can view:
- Pipeline Success Rate: Chart showing successful vs failed pipelines over time.
- Pipeline Duration: Average time pipelines take to execute, helping you spot when build steps start bloating.
- Runner Usage: Audit lists showing which runners are executing the most jobs, preventing executor queues from clogging.
