AZ-400 Implement an instrumentation strategy Practice Question
Which TWO metrics should you monitor to evaluate the reliability of a web application according to the DORA metrics?
⚠ Common exam trap
Many exam-takers confuse throughput metrics (Deployment Frequency, Lead Time for Changes) with reliability metrics, but DORA specifically separates them into 'throughput' and 'stability' categories, and the question explicitly asks for reliability.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Change Failure Rate
The DORA metrics define four key measures for software delivery performance: Deployment Frequency, Lead Time for Changes, Mean Time to Restore (MTTR), and Change Failure Rate. For evaluating the reliability of a web application, the two most directly relevant metrics are Change Failure Rate (B), which measures the percentage of deployments causing a failure in production, and Mean Time to Restore (MTTR) (C), which measures the time it takes to recover from a failure. These two metrics directly quantify stability and resilience, whereas Deployment Frequency and Lead Time for Changes focus on throughput and speed.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Lead Time for Changes
Why it's wrong here
Lead Time for Changes measures the time from code commit to production deployment, which reflects delivery speed and pipeline efficiency. It does not directly measure reliability, as a short lead time can coexist with frequent failures, so it is a velocity metric rather than a reliability indicator.
- ✓
Change Failure Rate
Why this is correct
Change Failure Rate is the percentage of deployments that cause a failure in production, such as a service impairment or rollback. It is a core DORA reliability metric because it directly quantifies how often changes disrupt service, making it essential for evaluating system stability.
- ✓
Mean Time to Restore (MTTR)
Why this is correct
Mean Time to Restore (MTTR) measures the average time it takes to recover from a production failure, from detection to full service restoration. It is a key reliability metric because it indicates how quickly a team can respond to incidents and minimize downtime, complementing failure rate by assessing recovery effectiveness.
- ✗
CPU Usage
Why it's wrong here
CPU Usage is an infrastructure performance metric that tracks resource utilization, not an indicator of deployment reliability or service quality. It may be relevant for capacity planning or detecting performance bottlenecks, but it does not align with DORA's four key metrics for measuring software delivery reliability.
- ✗
Deployment Frequency
Why it's wrong here
Deployment Frequency measures how often a team successfully releases new features or fixes to production, reflecting delivery throughput and agility. High deployment frequency is a sign of efficient DevOps practices but does not directly assess the stability or reliability of those releases, so it is a velocity metric rather than a reliability metric.
Visual reference
Go deeper
Related to this question
About these practice questions
This AZ-400 question is part of Courseiva's 823-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AZ-400 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AZ-400 exam.