Learn which Azure DevOps metrics to review to address issues like most bugs being reported by customers and long failure detection times. Improve your app quality with these key metrics.
Table of Contents
Question
You have an Azure DevOps project that is used to build and test an app named App1.
You need to troubleshoot the following issues:
- Most bugs are detected and reported by customers.
- It takes a long time to detect failures.
Which metric should you review for each issue? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Most bugs being detected and reported by customers:
- Application failure rates
- Bug report rates
- Defect escape rate
- Mean time to detection
- Mean time to recover
It takes a long time to etect failures:
- Application failure rates
- Bug report rates
- Defect escape rate
- Mean time to detection
- Mean time to recover
Answer
Most bugs being detected and reported by customers: Defect escape rate
It takes a long time to etect failures: Mean time to detection
Explanation
To troubleshoot the issue of most bugs being detected and reported by customers, the key metric you should review is the defect escape rate. The defect escape rate measures the percentage of defects that are not detected by the development and testing process and end up being reported by end users after the application is released. A high defect escape rate indicates that too many bugs are slipping through to production undetected. Reviewing this metric will help you assess the effectiveness of your current QA and testing processes at identifying bugs before release. You may need to expand test coverage, perform more rigorous testing, or implement additional QA checkpoints to catch more defects earlier.
For the issue of it taking a long time to detect failures, the main metric to analyze is mean time to detection (MTTD). MTTD measures the average time between when a failure occurs and when it is first discovered by the team. A higher MTTD means failures are going undetected for longer. Reviewing this metric can help identify inefficiencies or gaps in your application monitoring and alerting setup. You may need to instrument the application with more logging, set up automated failure detection rules, configure real-time alerts, or check monitoring dashboards more frequently. Detecting failures quickly is critical for being able to resolve them before they significantly impact users.
In summary, the defect escape rate and mean time to detection are two of the most important metrics to review in Azure DevOps to troubleshoot issues around bugs being reported by customers and slow failure detection time respectively. Focusing on these metrics will help you hone in on the specific areas that need improvement in your development and operations processes to deliver a higher quality, more reliable application.
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