KCNA Cloud Native Application Delivery Practice Question
A platform team is designing a progressive delivery rollout for a new version of a service running on Kubernetes. They want to send a small percentage of live traffic to the new version, observe metrics, and automatically roll back if error rates rise. Which two components are required to implement this with a service mesh? (Choose two.)
⚠ Common exam trap
The trap here is focusing on extra infrastructure like separate clusters or autoscalers, when the essential pieces are traffic splitting and metrics-driven analysis.
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
✓
A canary or weighted routing rule in the mesh that splits traffic between the stable and new versions.
Progressive delivery with a service mesh requires two capabilities: a routing rule that splits traffic by percentage between stable and canary, and an analysis loop that reads metrics and decides whether to promote or roll back. Together they enable small, safe exposure and automatic recovery from regressions.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
A canary or weighted routing rule in the mesh that splits traffic between the stable and new versions.
Why this is correct
Progressive delivery depends on controlling the percentage of requests reaching each version. A mesh routing rule, such as an Istio VirtualService with weighted destinations, directs a small share of traffic to the canary while the rest goes to the stable version. Without this split, all traffic hits one version and no gradual exposure occurs.
- ✗
A NodePort Service exposing the canary directly to external users for manual testing.
Why it's wrong here
Exposing the canary on a separate NodePort bypasses the controlled traffic split and sends users to the new version based on URL choice, not percentage. It also breaks the automated metrics-driven decision. Progressive delivery requires mesh-level routing and analysis, not a side door for manual access.
- ✗
A separate Kubernetes cluster dedicated to canary workloads.
Why it's wrong here
Canary deployments run both versions in the same cluster and namespace, differing only by labels selected by the routing rule. A separate cluster adds cost and complexity and is not required for traffic splitting. The mesh routes between Services or Pods, so isolation at the cluster level is unnecessary for this scenario.
- ✗
A HorizontalPodAutoscaler configured to scale the canary based on CPU.
Why it's wrong here
HPA adjusts replica counts in response to resource metrics; it does not control traffic percentages or evaluate application error rates. While useful for capacity, it cannot shift traffic between versions or abort a rollout. Progressive delivery needs routing and analysis, not autoscaling, to achieve controlled exposure and rollback.
- ✓
Metrics collection and an analysis mechanism that evaluates error rates and triggers rollback.
Why this is correct
Sending a small percentage of traffic is only useful if the team can judge whether the new version is healthy. Metrics from the mesh or application feed an analysis step, such as Argo Rollouts analysis templates querying Prometheus, which promotes or aborts the rollout. This closes the loop for automated rollback on elevated errors.
Go deeper
Related to this question
Learn chapter
Kubernetes Overview and Core Components
Key term
ReplicaSet and Replication
A ReplicaSet ensures a specified number of identical pod instances are running at all times in Kubernetes, using replication to maintain availability and stability.
Key term
Service Mesh
A service mesh is a dedicated infrastructure layer that manages communication between microservices, handling tasks like service discovery, load balancing, encryption, and observability without requiring changes to application code.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CNCF exam blueprint
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