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Linux Foundation Certified Cloud Native Platform Engineering Associate Sample Questions (Q70-Q75):

NEW QUESTION # 70
What is the primary goal of platform engineering?

A. To create reusable, scalable platforms that improve developer productivity and experience.
B. To limit developer access to infrastructure to enhance security and compliance.
C. To replace all DevOps practices with automated tools and well-defined processes.
D. To focus exclusively on infrastructure automation without considering developer needs

Answer: A

Explanation:
The primary goal of platform engineering is to create reusable, scalable platforms that improve both developer productivity and developer experience. Option D is correct because platform engineering treats the platform as a product, providing self-service capabilities, abstractions, and golden paths that reduce cognitive load for developers while embedding organizational guardrails.
Option A is too narrow-platform engineering is not limited to infrastructure automation but extends to developer usability, observability, and governance. Option B is incorrect because limiting access contradicts the principle of empowering developers through self-service. Option C is misleading; platform engineering complements DevOps practices but does not replace them.
By enabling developers to consume infrastructure and platform services through self-service APIs and portals, platform teams accelerate delivery cycles while maintaining compliance and security. This approach results in improved efficiency, reduced toil, and better alignment between business and engineering outcomes.
References:- CNCF Platforms Whitepaper- CNCF Platform Engineering Maturity Model- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 71
Which provisioning strategy ensures efficient resource scaling for an application on Kubernetes?

A. Manual provisioning of resources based on predicted traffic.
B. Implementing a fixed resource allocation that does not change regardless of demand.
C. Using an imperative approach to script resource changes in response to traffic spikes.
D. Using a declarative approach with Infrastructure as Code (IaC) tools to define resource requirements.

Answer: D

Explanation:
The most efficient and scalable strategy is to use a declarative approach with Infrastructure as Code (IaC)
. Option B is correct because declarative definitions specify the desired state (e.g., resource requests, limits, autoscaling policies) in code, allowing Kubernetes controllers and autoscalers to reconcile and enforce them dynamically. This ensures that applications can scale efficiently based on actual demand.
Option A (fixed allocation) is inefficient, leading to wasted resources during low usage or insufficient capacity during high demand. Option C (manual provisioning) introduces delays, risk of error, and operational overhead. Option D (imperative scripting) is not sustainable for large-scale or dynamic workloads, as it requires constant manual intervention.
Declarative IaC aligns with GitOps workflows, enabling automated, version-controlled scaling decisions.
Combined with Kubernetes' Horizontal Pod Autoscaler (HPA) and Cluster Autoscaler, this approach allows platforms to balance cost efficiency with application reliability.
References:- CNCF GitOps Principles- Kubernetes Autoscaling Documentation- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 72
In a GitOps setup, which of the following correctly describes the interaction between components when using a pull-based approach?

A. The target cluster sends updates to the git repository whenever a change is made.
B. The syncer continuously checks the git repository for changes and applies them to the target cluster.
C. The syncer uses webhooks to notify the target cluster of changes in the git repository.
D. The git repository pushes configuration changes directly to the syncer without any checks.

Answer: B

Explanation:
GitOps uses a pull-based approach, where controllers inside the cluster continuously reconcile the desired state stored in Git with the actual cluster state. Option A is correct because GitOps sync agents (e.g., Argo CD, Flux) poll or watch Git repositories for changes and automatically apply updates to the cluster.
Option B reverses the model-clusters do not send updates to Git; Git is the source of truth. Option C is partially misleading: webhooks can trigger faster syncs but reconciliation is still pull-based. Option D misrepresents GitOps-Git never pushes directly to clusters.
This pull-based approach ensures greater security (clusters pull changes rather than exposing themselves to pushes), consistency (Git as source of truth), and continuous reconciliation (drift correction).
References:- CNCF GitOps Principles- CNCF Platforms Whitepaper- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 73
For a cloud native platform handling sensitive customer data, which approach ensures compliance with data privacy regulations like GDPR and PCI DSS within a Kubernetes environment?

A. Relying on default cloud provider IAM policies with minimal Kubernetes customizations.
B. Implementing Kubernetes Role-based access control (RBAC) with basic network policies and periodic manual audits.
C. Deploying a policy engine like Open Policy Agent (OPA) with real-time data masking and audit logging.
D. Utilizing standard Kubernetes Secrets with encrypted storage and manual access reviews.

Answer: C

Explanation:
Compliance with regulations like GDPR and PCI DSS requires fine-grained control, auditing, and data protection. Option C is correct because deploying a policy engine like Open Policy Agent (OPA) enables dynamic enforcement of policies, real-time data masking, and comprehensive audit logging. This ensures sensitive data is protected while providing traceability and compliance reporting.
Option A is insufficient, as default IAM policies without Kubernetes-level governance do not provide the granularity required for compliance. Option B (Kubernetes Secrets) adds encryption but lacks auditability and runtime enforcement. Option D (RBAC and network policies) improves security posture but does not provide comprehensive compliance coverage or data privacy features like masking and logging.
OPA and similar tools integrate with Kubernetes admission control to enforce compliance policies consistently, providing the flexibility and auditability needed in regulated industries.
References:- CNCF Security TAG Best Practices- CNCF Platforms Whitepaper- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 74
During a platform engineering meeting, a team discusses the importance of automating deployment processes to enhance collaboration and efficiency. What is the primary benefit of implementing automation in DevOps practices within platform engineering?

A. It eliminates the need for any manual intervention.
B. It accelerates deployments, enabling faster iterations and continuous delivery.
C. It reduces the need for communication between team members.
D. It creates dependencies on specific tools and platforms.

Answer: B

Explanation:
Automation in DevOps practices is central to platform engineering because it enables faster, reliable, and repeatable deployments. Option D is correct: automation accelerates deployments, reduces bottlenecks, and enables continuous delivery and rapid iterations. By automating build, test, and deployment pipelines, teams can deliver new features quickly while maintaining high quality and compliance.
Option A is incorrect because automation does not reduce the need for communication-it complements collaboration by removing friction. Option B is unrealistic: some manual oversight may remain (e.g., in production approvals for sensitive workloads). Option C is not a primary benefit-while tools may be involved, the focus is on outcomes, not tool dependency.
By embedding automation, teams reduce toil, enforce consistency, and free developers to focus on value creation rather than repetitive tasks. This results in shorter lead times, higher deployment frequency, and overall improved developer experience, which aligns with DORA metrics.
References:- CNCF Platforms Whitepaper- Continuous Delivery Foundation Guidance- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 75
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Jerry Wilson Jerry Wilson

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