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Linux Foundation CNPA Practice Test - The Key To Fast Exam

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Linux Foundation CNPA Exam Syllabus Topics:

Topic
Details

Topic 1

Platform Observability, Security, and Conformance: This part of the exam evaluates Procurement Specialists on key aspects of observability and security. It includes working with traces, metrics, logs, and events while ensuring secure service communication. Policy engines, Kubernetes security essentials, and protection in CI
CD pipelines are also assessed here.

Topic 2

Continuous Delivery & Platform Engineering: This section measures the skills of Supplier Management Consultants and focuses on continuous integration pipelines, the fundamentals of the CI
CD relationship, and GitOps basics. It also includes knowledge of workflows, incident response in platform engineering, and applying GitOps for application environments.

Topic 3

Platform Engineering Core Fundamentals: This section of the exam measures the skills of Supplier Management Consultants and covers essential foundations such as declarative resource management, DevOps practices, application environments, platform architecture, and the core goals of platform engineering. It also includes continuous integration fundamentals, delivery approaches, and GitOps principles.

Topic 4

IDPs and Developer Experience: This section of the exam measures the skills of Supplier Management Consultants and focuses on improving developer experience. It covers simplified access to platform capabilities, API-driven service catalogs, developer portals for platform adoption, and the role of AI
ML in platform automation.

Topic 5

Platform APIs and Provisioning Infrastructure: This part of the exam evaluates Procurement Specialists on the use of Kubernetes reconciliation loops, APIs for self-service platforms, and infrastructure provisioning with Kubernetes. It also assesses knowledge of the Kubernetes operator pattern for integration and platform scalability.

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Linux Foundation Certified Cloud Native Platform Engineering Associate Sample Questions (Q33-Q38):

NEW QUESTION # 33
Which of the following best represents an effective golden path implementation in platform engineering?

A. A central documentation repository listing available database services with their configuration parameters.
B. An API service catalog providing comprehensive details about available infrastructure components and their consumption patterns.
C. A templated workflow that guides developers through deploying a complete microservice with integrated testing and monitoring.
D. A monitoring dashboard system that displays the operational health metrics and alerting thresholds for all platform services.

Answer: C

Explanation:
A golden path in platform engineering refers to a curated, opinionated workflow that makes the easiest way the right way for developers. Option C is correct because a templated workflow for deploying a microservice with integrated testing and monitoring embodies the golden path concept. It provides developers with a pre-validated, secure, and efficient approach that reduces cognitive load and accelerates delivery.
Option A (documentation) provides information but lacks automation and enforced best practices. Option B (monitoring dashboards) improves observability but does not guide developers in delivery workflows. Option D (API service catalog) is useful but more about service discovery than curated workflows.
Golden paths improve adoption by embedding guardrails, automation, and organizational standards directly into workflows, making compliance seamless. They ensure consistency while allowing developers to focus on innovation rather than platform complexity.
References:- CNCF Platforms Whitepaper- Team Topologies & Platform Engineering Practices- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 34
As a platform engineer, a critical application has been deployed using Helm, but a recent update introduced a severe bug. To quickly restore the application to its previous stable version, which Helm command should be used?

A. helm upgrade --force <revision>
B. helm template <release_name>
C. helm rollback <release_name> <revision>
D. helm uninstall <release_name>

Answer: C

Explanation:
Helm provides native support for managing versioned releases, allowing easy rollback in case of issues.
Option A is correct because the helm rollback <release_name> <revision> command reverts the deployment to a previously known stable release without requiring a redeployment from scratch. This ensures fast recovery and minimizes downtime after a faulty upgrade.
Option B (helm upgrade --force) attempts to reapply an upgrade but does not restore the previous version.
Option C (helm template) only renders Kubernetes manifests from charts and does not affect running releases.
Option D (helm uninstall) removes the release entirely, which is not suitable for quick recovery.
Rollback functionality is essential in platform engineering for resilience and rapid mitigation of production issues. By using helm rollback, teams align with best practices for safe, controlled release management in Kubernetes environments.
References:- CNCF Helm Documentation- CNCF Platforms Whitepaper- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 35
In a Kubernetes environment, which component is responsible for watching the state of resources during the reconciliation process?

A. Kubernetes Controller
B. Kubernetes Scheduler
C. Kubernetes API Server
D. Kubernetes Dashboard

Answer: A

Explanation:
The Kubernetes reconciliation process ensures that the actual cluster state matches the desired state defined in manifests. The Kubernetes Controller (option D) is responsible for watching the state of resources through the API Server and taking action to reconcile differences. For example, the Deployment Controller ensures that the number of Pods matches the replica count specified, while the Node Controller monitors node health.
Option A (Scheduler) is incorrect because the Scheduler's role is to assign Pods to nodes based on constraints and availability, not ongoing reconciliation. Option B (Dashboard) is simply a UI for visualization and does not manage cluster state. Option C (API Server) exposes the Kubernetes API and serves as the communication hub, but it does not perform reconciliation logic itself.
Controllers embody the core Kubernetes design principle: continuous reconciliation between declared state and observed state. This makes them fundamental to declarative infrastructure and aligns with GitOps practices where controllers continuously enforce desired configurations from source control.
References:- CNCF Kubernetes Documentation- CNCF GitOps Principles- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 36
A company is implementing a service mesh for secure service-to-service communication in their cloud native environment. What is the primary benefit of using mutual TLS (mTLS) within this context?

A. Enables logging of all service communications for audit purposes.
B. Allows services to bypass security checks for better performance.
C. Allows services to authenticate each other and secure data in transit.
D. Simplifies the deployment of microservices by automatically scaling them.

Answer: C

Explanation:
Mutual TLS (mTLS) is a core feature of service meshes, such as Istio or Linkerd, that enhances security in cloud native environments by ensuring that both communicating services authenticate each other and that the communication channel is encrypted. Option A is correct because mTLS delivers two critical benefits:
authentication (verifying the identity of both client and server services) and encryption (protecting data in transit from interception or tampering).
Option B is incorrect because mTLS does not bypass security-it enforces it. Option C is partly true in that service meshes often support observability and logging, but that is not the primary purpose of mTLS. Option D relates to scaling, which is outside the scope of mTLS.
In platform engineering, mTLS is a fundamental security mechanism that provides zero-trust networking between microservices, ensuring secure communication without requiring application-level changes. It strengthens compliance with security and data protection requirements, which are crucial in regulated industries.
References:- CNCF Service Mesh Whitepaper- CNCF Platforms Whitepaper- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 37
As a Cloud Native Platform Associate, you need to implement an observability strategy for your Kubernetes clusters. Which of the following tools is most commonly used for collecting and monitoring metrics in cloud native environments?

A. ELK Stack
B. Prometheus
C. Grafana
D. OpenTelemetry

Answer: B

Explanation:
Prometheus is the de facto standard for collecting and monitoring metrics in Kubernetes and other cloud native environments. Option D is correct because Prometheus is a CNCF graduated project designed for multi- dimensional data collection, time-series storage, and powerful querying using PromQL. It integrates seamlessly with Kubernetes, automatically discovering targets such as Pods and Services through service discovery.
Option A (Grafana) is widely used for visualization but relies on Prometheus or other data sources to collect metrics. Option B (ELK Stack) is better suited for log aggregation rather than real-time metrics. Option C (OpenTelemetry) provides standardized instrumentation but is focused on generating and exporting metrics, logs, and traces rather than storage, querying, and alerting.
Prometheus plays a central role in platform observability strategies, often paired with Alertmanager for notifications and Grafana for dashboards. Together, they enable proactive monitoring, SLO/SLI measurement, and incident detection, making Prometheus indispensable in cloud native platform engineering.
References:- CNCF Observability Whitepaper- Prometheus CNCF Project Documentation- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 38
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