AZ-400 Question 24
Select 2Your development team uses Azure DevOps for all project planning and work item tracking. The product owner has requested detailed metrics on lead time, cycle time, and average bug resolution time to better understand and improve the development process. You need to establish a reliable way to capture and present these metrics. Which two methods should you implement?
- A
Create custom queries in Azure DevOps that measure time between state transitions (e.g., from New to Closed), leveraging 'Changed Date' and 'State' fields to calculate lead time and cycle time.
- B
Enable the Analytics service in Azure DevOps and use Analytics views or Power BI reports to visualize and track lead time, cycle time, and bug resolution metrics in near real time.
- C
Use release pipeline logs to infer when items are worked on and incorporate that data into manual calculations for lead time and cycle time.
- D
Create a custom notification that auto-closes bugs after a fixed number of days, ensuring consistent cycle time across all work items.
Show answer and explanation
Correct answers: A, B
Explanation
To design and implement appropriate metrics for project planning, you should focus on actual work item data in Azure DevOps, such as state transitions and timestamps. Combining the built-in Analytics service with custom queries or integrated Power BI reports is a recommended best practice for tracking metrics like lead time, cycle time, and bug resolution. This approach aligns with official Microsoft guidance on leveraging Azure DevOps Analytics for in-depth project planning insights. Refer to Microsoft documentation on Azure DevOps Analytics (https://learn.microsoft.com/azure/devops/report/analytics) for further details.
- A. Correct.
Option 1 is correct. Using custom queries to capture changes between states (such as New, Active, and Closed) allows you to measure the actual lead time and cycle time for each work item by calculating differences in the 'Changed Date' or 'Created Date' fields. This approach directly addresses your need for meaningful metrics.
- B. Correct.
Option 2 is correct. By enabling Analytics, you can access the Azure DevOps Analytics service to build views or Power BI dashboards. This gives you the flexibility to slice and dice data for different metrics (e.g., overall lead time, bug resolution time) and present them in visual reports for stakeholders.
- C. Incorrect.
Option 3 is incorrect. While release pipeline logs can provide insights into deployment times, they do not directly correlate with work item state changes necessary for measuring lead time or cycle time. This approach would be cumbersome and prone to error compared to using work item data.
- D. Incorrect.
Option 4 is incorrect. Automatically closing bugs after a predetermined time does not generate accurate metrics; it simply forces a uniform cycle time. This practice obscures real project data and prevents teams from understanding actual time frames for resolving defects.