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2026 CNPA: Marvelous Certified Cloud Native Platform Engineering Associate Examcollection Questions Answers

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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

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 4

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 5

Measuring your Platform: This part of the exam assesses Procurement Specialists on how to measure platform efficiency and team productivity. It includes knowledge of applying DORA metrics for platform initiatives and monitoring outcomes to align with organizational goals.

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Linux Foundation Certified Cloud Native Platform Engineering Associate Sample Questions (Q27-Q32):

NEW QUESTION # 27
A platform engineering team needs to provide comprehensive cost visibility for Kubernetes workloads to optimize infrastructure utilization. Which tool is recommended to achieve this goal?

A. Application performance monitoring tools with limited resource cost tracking.
B. Cloud provider cost estimation tools with basic Kubernetes integration.
C. OpenCost for real-time, granular Kubernetes cost allocation and analysis.
D. Kubernetes resource usage metrics paired with cloud provider billing data.

Answer: C

Explanation:
OpenCost is the CNCF-supported open-source project designed specifically for Kubernetes cost visibility and optimization. Option B is correct because OpenCost provides granular, real-time allocation of Kubernetes costs across namespaces, workloads, and teams. This allows organizations to understand true cost drivers and optimize resource utilization effectively.
Option A (APM tools) may track performance but usually lack deep integration with Kubernetes cost allocation. Option C provides partial visibility but requires complex manual correlation of resource usage with billing data. Option D (cloud provider estimators) typically offer limited or high-level insights and do not map costs down to Kubernetes workloads.
By adopting OpenCost, platform teams can align financial accountability with engineering usage, a practice known as FinOps. This supports sustainable scaling, cost efficiency, and transparency-critical aspects of measuring platform success.
References:- CNCF OpenCost Project- CNCF Platforms Whitepaper- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 28
Which approach is an effective method for securing secrets in CI/CD pipelines?

A. Storing secrets as plain-text environment variables managed through config files.
B. Storing secrets in configuration files with restricted access.
C. Storing secrets and encrypting them in a secrets manager.
D. Encoding secrets in the source code using base64.

Answer: C

Explanation:
The most secure and scalable method for handling secrets in CI/CD pipelines is to use a secrets manager with encryption. Option B is correct because solutions like HashiCorp Vault, AWS Secrets Manager, or Kubernetes Secrets (backed by KMS) securely store, encrypt, and control access to sensitive values such as API keys, tokens, or credentials.
Option A (restricted config files) may protect secrets but lacks auditability and rotation capabilities. Option C (plain-text environment variables) exposes secrets to accidental leaks through logs or misconfigurations.
Option D (base64 encoding) is insecure because base64 is an encoding, not encryption, and secrets can be trivially decoded.
Using a secrets manager ensures secure retrieval, audit trails, access policies, and secret rotation. This aligns with supply chain security and zero-trust practices, reducing risks of credential leakage in CI/CD pipelines.
References:- CNCF Security TAG Best Practices- CNCF Platforms Whitepaper- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 29
What is a key cultural aspect that drives successful platform adoption in an organization?

A. Keeping platform development separate from application teams.
B. Mandating that all teams must use the platform without exceptions
C. Prioritizing platform security over usability.
D. Encouraging platform feedback loops from developers to improve usability.

Answer: D

Explanation:
Successful platform adoption depends heavily on cultural practices that foster collaboration and continuous improvement. Option D is correct because feedback loops between developers and platform teams ensure that the platform evolves to meet developer needs while balancing security and governance. This aligns with the principle of treating the platform as a product, where developer experience is central.
Option A (mandates) often lead to resistance and shadow IT. Option B isolates platform teams, creating silos and reducing alignment with developer workflows. Option C is misleading-security is important, but overemphasizing it at the expense of usability hinders adoption.
Feedback-driven iteration creates trust, improves usability, and drives organic adoption. It transforms the platform into a valuable product that developers want to use, rather than one they are forced to adopt.
References:- CNCF Platforms Whitepaper- Team Topologies (Platform as a Product model)- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 30
In the context of observability for cloud native platforms, which of the following best describes the role of OpenTelemetry?

A. OpenTelemetry is solely focused on infrastructure monitoring.
B. OpenTelemetry is primarily used for logging data only.
C. OpenTelemetry is a proprietary solution that limits its use to specific cloud providers.
D. OpenTelemetry provides a standardized way to collect and transmit observability data.

Answer: D

Explanation:
OpenTelemetry is an open-source CNCF project that provides vendor-neutral, standardized APIs, SDKs, and agents for collecting and exporting observability data such as metrics, logs, and traces. Option C is correct because OpenTelemetry's purpose is to unify how telemetry data is generated, transmitted, and consumed, regardless of which backend (e.g., Prometheus, Jaeger, Elastic, commercial APM tools) is used.
Option A is incorrect because OpenTelemetry supports all three signal types (metrics, logs, traces), not just logs. Option B is incorrect because it is an open, community-driven standard and not tied to a single vendor or cloud provider. Option D is misleading because OpenTelemetry covers distributed applications, services, and infrastructure-far beyond just infrastructure monitoring.
OpenTelemetry reduces vendor lock-in and promotes interoperability, making it a cornerstone of cloud native observability strategies. Platform engineering teams rely on it to ensure consistent data collection, enabling better insights, faster debugging, and improved reliability of cloud native platforms.
References:- CNCF Observability Whitepaper- OpenTelemetry CNCF Project Documentation- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 31
As a platform engineer, how do you automate application deployments across multiple Kubernetes clusters using GitOps, Helm, and Crossplane, ensuring a consistent application state?

A. Leverage Git for configuration storage, with manual application of Helm and Crossplane.
B. Use Helm and Crossplane, with manual GUI-based configuration updates.
C. Employ a GitOps controller to synchronize Git-stored Helm and Crossplane configurations.
D. Integrate Helm and Crossplane into a GitOps-enabled CI/CD pipeline.

Answer: C

Explanation:
The most effective way to achieve consistent, automated deployments across multiple Kubernetes clusters is to combine GitOps controllers (e.g., Argo CD, Flux) with declarative configurations managed by Helm and Crossplane. Option A is correct because the GitOps controller continuously reconciles the desired state stored in Git-Helm charts for applications and Crossplane manifests for infrastructure-ensuring consistency across clusters.
Option B and D rely on manual updates, which are error-prone and not scalable. Option C mischaracterizes GitOps by suggesting push-based pipelines rather than the core GitOps model of pull-based reconciliation.
This combination leverages Helm for application packaging, Crossplane for cloud infrastructure provisioning, and GitOps for declarative, version-controlled delivery. It ensures applications remain in sync with Git, providing auditability, automation, and resilience in multi-cluster environments.
References:- CNCF GitOps Principles- CNCF Platforms Whitepaper- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 32
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