Module 8 Lesson 3: Dashboards and Metrics

As a DevOps lead, you need to answer the question: "Are we getting better or worse?" The CI/CD Analytics dashboard provides the data to prove your success.

1. Finding the Data

Go to Analyze -> CI/CD Analytics.

Charts: You can see a graph of the "Last 30 days" of pipeline success/failure.
Duration: See which jobs are getting slower over time. (Is the "Test" job growing from 2 minutes to 20 minutes?)

2. DORA Metrics in GitLab (Review Module 1)

GitLab automatically calculates the 4 DORA metrics for you:

Deployment Frequency: How many times you push to Production.
Lead Time: Time from first commit to deployment.
Change Failure Rate: % of failed deployments.
Time to Restore: Average time the site stays red.

3. Value Stream Analytics

This is the "Whole Life" of a feature.

It tracks how long a task takes to move from Issue Created -> Code Written -> Merge Request -> Deployed.
The Goal: If code takes 1 day to write but 5 days to "Review," the problem is your team's review culture, not your CI/CD scripts!

4. Troubleshooting Slowness

Use the "Pipeline Duration" metric to see which specific job is the outlier. If "Frontend Build" takes 10x longer than "Backend Build," you know exactly where to spend your "Optimization Time."

Exercise: The Analyst's Review

Go to your project -> Analyze -> CI/CD Analytics.
Look at your "Success Rate." Is it above 90%?
Find the "Pipeline Duration" graph. What was your longest pipeline in the last week?
How would you use this data to convince your boss that you need to spend 1 day "Cleaning up the code"?
Research: What is the "GitLab Value Stream" custom stage set? Can you create your own stages?

Summary

Metrics move the conversation from "I think the pipeline is slow" to "The pipeline takes exactly 14 minutes and 30 seconds." By measuring your outcomes, you can make data-driven decisions that actually improve your team's quality of life.

Next Lesson: High stakes: Monitoring Deployment Health.