Managing Implementation and Ensuring Solution and Operations Reliability →mediumMultiple ChoiceObjective-mapped
Google PCA Practice Question: Managing Implementation and Ensuring Solution and Operations Reliability
A team is implementing a canary deployment for a microservice on GKE using traffic splitting. They want to gradually shift 1% of traffic to a new version, monitor for errors, and then increase the percentage. Which tool or configuration should they use?
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
✓
Use Cloud Deploy with a canary deployment strategy and Istio traffic splitting
Cloud Deploy supports canary deployments with traffic splitting via Istio or other service meshes. It allows gradual rollout and automated promotion based on criteria.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Configure a GKE Ingress with weighted backend services
Why it's wrong here
GKE Ingress with weighted backends is possible but does not provide the built-in canary pipeline and monitoring integration that Cloud Deploy offers.
- ✗
Deploy the new version to a separate namespace and use DNS weighting
Why it's wrong here
DNS weighting is not accurate for traffic splitting and does not provide the control and observability needed for canary deployments.
- ✓
Use Cloud Deploy with a canary deployment strategy and Istio traffic splitting
Why this is correct
Cloud Deploy natively supports canary deployments with traffic splitting via Istio or other service mesh.
- ✗
Use Kubernetes Deployment with rolling update strategy
Why it's wrong here
Rolling update gradually replaces pods but does not support precise traffic splitting percentages (e.g., 1%).
Go deeper
Related to this question
Learn chapter
Introduction to Google Cloud Platform
Key term
Service
A service is a software component or system that performs a specific function and is available to be used by other programs or users over a network.
Key term
GKE
GKE is Google's managed Kubernetes service that automates deploying, scaling, and managing containerized applications in the cloud.
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