KCNA Cloud Native Application Delivery Practice Question
A team wants to use feature flags to control the rollout of a new feature in a Kubernetes-deployed microservice. Which tool is specifically designed for managing feature flags in cloud-native applications?
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
✓
LaunchDarkly
LaunchDarkly is a feature management platform specifically designed for managing feature flags in cloud-native applications. It allows for controlled rollouts and A/B testing. Argo Rollouts focuses on progressive delivery (canary, blue-green deployments), not feature flags. Helm is a package manager for Kubernetes. Kustomize is for configuration management. Therefore, option B (LaunchDarkly) is correct.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Helm
Why it's wrong here
Helm templates and versions Kubernetes manifests; it has no runtime flag evaluation or targeting rules. It tempts because chart values can toggle configuration per release, which suits deployment-time variation, but flags must change without redeploying, which Helm cannot do.
- ✓
LaunchDarkly
Why this is correct
LaunchDarkly is a dedicated feature-management platform, streaming flag evaluations to SDKs so toggles update without redeploying pods. It satisfies the stem's cloud-native rollout constraint directly, whereas general CI/CD or service-mesh tooling lacks native flag targeting, percentage rollouts and audit trails.
- ✗
Kustomize
Why it's wrong here
Kustomize overlays patch Kubernetes manifests per environment; it cannot evaluate flags at runtime or target individual users. It tempts because overlays vary configuration between deployments, which suits environment-specific settings, but feature-flag evaluation requires a dedicated flag management service.
- ✗
Argo Rollouts
Why it's wrong here
Argo Rollouts automates progressive delivery through canary and blue-green strategies, shifting traffic by percentage, but it exposes no user-targeting flag SDK. It tempts because gradual rollout resembles flagging, and it would be correct for automated canary analysis, not runtime toggles.
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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.