KCNA Cloud Native Application Delivery Practice Question
Which THREE of the following are DORA metrics?
⚠ Common exam trap
CNCF often tests candidates by including plausible but non-DORA metrics like code coverage or deployment counts, exploiting the misconception that any useful DevOps metric qualifies as a DORA metric, when in fact only the four specific metrics (deployment frequency, lead time for changes, mean time to restore, and change failure rate) are officially defined.
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
✓
Mean time to restore (MTTR)
Mean time to restore (MTTR) is one of the four key DORA metrics defined by the DevOps Research and Assessment (DORA) team. It measures the average time it takes to recover from a failure in a production environment, directly reflecting the resilience and incident response capability of a cloud-native system. In Kubernetes, this often involves automated rollback strategies, pod rescheduling, or canary deployments to minimize downtime.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Mean time to restore (MTTR)
Why this is correct
It measures the time to recover from a failure.
- ✓
Lead time for changes
Why this is correct
It measures the time from code commit to production.
- ✓
Deployment frequency
Why this is correct
It measures how often deployments occur.
- ✗
Code coverage
Why it's wrong here
Code coverage is a testing metric, not a DORA metric.
- ✗
Number of deployments per developer
Why it's wrong here
This is not a standard DORA metric.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This KCNA practice question is part of Courseiva's free CNCF 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 KCNA exam.