AZ-400 Question 35
Select 2You are a DevOps engineer for a financial services company that uses Azure Boards for work tracking, Azure Repos for source control, and Azure Pipelines for CI/CD. Leadership wants better visibility into how frequently new features are deployed and how often those deployments require immediate fixes or rollbacks. Which two metrics should you track to fulfill these requests?
- A
Deployment Frequency
- B
Lead Time for Changes
- C
Change Failure Rate
- D
Lines of Code Committed
- E
Number of Unit Tests
Show answer and explanation
Correct answers: A, C
Explanation
In DevOps, key delivery metrics often include the four DORA metrics: Deployment Frequency, Lead Time for Changes, Change Failure Rate, and Mean Time to Restore. In this scenario, leadership specifically asks for a measure of how often new features are deployed (Deployment Frequency) and how often those releases fail (Change Failure Rate). For more information, refer to official DevOps documentation on DORA metrics and Azure DevOps Analytics.
- A. Correct.
Option 1: Deployment Frequency is correct. It shows how often the team ships new features or changes and directly answers leadership's request for insight into how frequently deployments happen.
- B. Incorrect.
Option 2: Lead Time for Changes measures how quickly code moves from commit to production, which is a valuable metric but not explicitly requested based on the scenario. Leadership specifically wants frequency and failure/rollback rates.
- C. Correct.
Option 3: Change Failure Rate is correct. It quantifies how often deployments result in issues that require fix or rollback, aligning with leadership� need to track immediate fixes or rollbacks.
- D. Incorrect.
Option 4: Lines of Code Committed is a misleading indicator of productivity or stability. The volume of code does not necessarily correlate with successful or frequent deployments.
- E. Incorrect.
Option 5: Number of Unit Tests can indicate test coverage and quality. However, it does not directly measure deployment frequency or the rate of failed deployments.