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Vendor: | Linux Foundation |
---|---|
Exam Code: | CNPA |
Exam Name: | Certified Cloud Native Platform Engineering Associate |
Exam Questions: | 85 |
Last Updated: | September 16, 2025 |
Related Certifications: | Cloud & Containers Certifications |
Exam Tags: | Associate DevOps engineersCloud Native Developers |
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Which CI/CD tool is specifically designed as a continuous delivery platform for Kubernetes that follows GitOps principles?
Argo CD is a GitOps-native continuous delivery tool specifically designed for Kubernetes. Option B is correct because Argo CD continuously monitors Git repositories for desired application state and reconciles Kubernetes clusters accordingly. It is declarative, Kubernetes-native, and aligned with GitOps principles, making it a key tool in platform engineering.
Option A (TravisCI) and Option C (CircleCI) are CI/CD systems but not Kubernetes-native or GitOps-driven. Option D (Jenkins) is a widely used CI/CD tool but operates primarily in a push-based model unless extended with plugins, and is not purpose-built for GitOps.
Argo CD provides automated deployments, drift detection, rollback, and auditability---features central to GitOps workflows. It simplifies multi-cluster management, enforces compliance, and reduces manual intervention, making it a leading choice in Kubernetes-based platform engineering.
--- CNCF GitOps Principles
--- Argo CD CNCF Project Documentation
--- Cloud Native Platform Engineering Study Guide
Which approach is effective for scalable Kubernetes infrastructure provisioning?
The most effective approach for scalable Kubernetes infrastructure provisioning is Crossplane compositions. Option D is correct because compositions let platform teams define custom CRDs (Composite Resources) that abstract infrastructure details while embedding organizational policies and guardrails. Developers then consume these abstractions through simple Kubernetes-native APIs, enabling self-service at scale.
Option A (Helm with values.yaml) is useful for application deployment but not for scalable infrastructure provisioning across multiple clouds. Option B (imperative scripts) lacks scalability, repeatability, and governance. Option C (static YAML with kubectl apply) is manual and not suited for dynamic, multi-team environments.
Crossplane compositions allow platform teams to curate golden paths while giving developers autonomy. This reduces complexity, ensures compliance, and supports multi-cloud provisioning---all key aspects of platform engineering.
--- CNCF Crossplane Project Documentation
--- CNCF Platforms Whitepaper
--- Cloud Native Platform Engineering Study Guide
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?
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.
--- CNCF Security TAG Best Practices
--- CNCF Platforms Whitepaper
--- Cloud Native Platform Engineering Study Guide
A platform engineering team is building an Internal Developer Platform (IDP). Which of the following enables application teams to manage infrastructure resources independently, without requiring direct platform team support?
The defining capability of an IDP is enabling self-service so developers can independently access infrastructure and platform resources. Option D is correct because self-service resource provisioning APIs allow developers to provision resources such as namespaces, databases, or environments without relying on manual intervention from the platform team. These APIs embed governance, compliance, and organizational guardrails while giving autonomy to development teams.
Option A (manual deployment services) defeats the purpose of self-service. Option B (knowledge centers) improve documentation but do not provide automation. Option C (logging/monitoring interfaces) are observability tools, not resource provisioning mechanisms.
Self-service APIs empower developers, reduce cognitive load, and minimize bottlenecks. They also align with the platform engineering principle of ''treating the platform as a product,'' where developers are customers, and the platform offers curated golden paths to simplify consumption of infrastructure and services.
--- CNCF Platforms Whitepaper
--- CNCF Platform Engineering Maturity Model
--- Cloud Native Platform Engineering Study Guide
In a multi-cluster Kubernetes setup, which approach effectively manages the deployment of multiple interdependent applications together as a unit?
In multi-cluster Kubernetes environments, the challenge lies in consistently deploying interdependent applications across clusters while ensuring reliability and repeatability. The Cloud Native Platform Engineering guidance stresses the importance of a declarative approach to define applications as code, which enables teams to describe the entire application system---including dependencies, configuration, and policies---in a single manifest. This ensures that applications are treated as a cohesive unit rather than isolated workloads.
Option A is correct because declarative application deployment definitions (often managed through GitOps practices) allow for consistent and automated reconciliation of desired state versus actual state across multiple clusters. This approach supports scalability, disaster recovery, and compliance by ensuring identical deployments across environments.
Option B (separate repos per application) increases fragmentation and does not inherently manage interdependencies. Option C (direct deployments from CI/CD) bypasses the GitOps model, which reduces auditability and consistency. Option D (Helm with manual deployments) partially addresses packaging but lacks the automation and governance needed in a multi-cluster setup.
--- CNCF GitOps Principles for Platforms
--- CNCF Platforms Whitepaper
--- Cloud Native Platform Engineering Study Guide
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