Quiz CNPA - Professional Certified Cloud Native Platform Engineering Associate Instant Download
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Linux Foundation Certified Cloud Native Platform Engineering Associate Sample Questions (Q32-Q37):
NEW QUESTION # 32
A software development team is struggling to adopt a new cloud native platform efficiently. How can a centralized developer portal, such as Backstage, help improve their adoption process?
Answer: D
Explanation:
Developer portals like Backstage act as the single entry point for platform services, APIs, golden paths, and documentation. Option A is correct because centralizing access greatly reduces the friction developers face when trying to adopt a new platform. Instead of searching across fragmented systems or learning low-level Kubernetes details, developers can find everything in one place, including templates, service catalogs, automated workflows, and governance policies.
Option B is irrelevant to platform adoption. Option C may foster community sharing but does not directly address adoption challenges. Option D contradicts platform engineering principles, which emphasize democratizing access and self-service rather than restricting tools to senior developers.
By providing a unified experience, portals improve discoverability, consistency, and self-service. They reduce cognitive load and support the platform engineering principle of improving developer experience, making adoption of new platforms smoother and more efficient.
References:- CNCF Platforms Whitepaper- CNCF Platform Engineering Maturity Model- Cloud Native Platform Engineering Study Guide
NEW QUESTION # 33
How can an internal platform team effectively support data scientists in leveraging complex AI/ML tools and infrastructure?
Answer: C
Explanation:
The best way for platform teams to support data scientists is by enabling easy access to specialized AI/ML workflows, tools, and compute resources. Option C is correct because it empowers data scientists to experiment, train, and deploy models without worrying about the complexities of infrastructure setup. This aligns with platform engineering's principle of self-service with guardrails.
Option A (integrating into standard CI/CD) may help, but AI/ML workflows often require specialized tools like MLflow, Kubeflow, or TensorFlow pipelines. Option B (strict quotas) ensures stability but does not improve usability or productivity. Option D (UI-driven execution only) restricts flexibility and reduces the ability of data scientists to adapt workflows to evolving needs.
By offering AI/ML-specific workflows as golden paths within an Internal Developer Platform (IDP), platform teams improve developer experience for data scientists, accelerate innovation, and ensure compliance and governance.
References:- CNCF Platforms Whitepaper- CNCF Platform Engineering Maturity Model- Cloud Native Platform Engineering Study Guide
NEW QUESTION # 34
Which approach is an effective method for securing secrets in CI/CD pipelines?
Answer: D
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 # 35
What is the primary purpose of Kubernetes runtime security?
Answer: D
Explanation:
The main purpose of Kubernetes runtime security is to protect workloads during execution. Option B is correct because runtime security focuses on monitoring active Pods, containers, and processes to detect and prevent malicious activity such as privilege escalation, anomalous network connections, or unauthorized file access.
Option A (etcd encryption) addresses data at rest, not runtime. Option C (image scanning) occurs pre- deployment, not during execution. Option D (API access control) is enforced through RBAC and IAM, not runtime security.
Runtime security solutions (e.g., Falco, Cilium, or Kyverno) continuously observe system calls, network traffic, and workload behaviors to enforce policies and detect threats in real time. This ensures compliance, strengthens defenses in zero-trust environments, and provides critical protection for cloud native workloads in production.
References:- CNCF Security TAG Guidance- CNCF Platforms Whitepaper- Cloud Native Platform Engineering Study Guide
NEW QUESTION # 36
What is the primary advantage of using a declarative approach to Infrastructure as Code (IaC) over an imperative approach?
Answer: B
Explanation:
Declarative Infrastructure as Code (IaC) is a key principle in cloud native environments because it enables platform teams to define the desired state of infrastructure rather than step-by-step procedures. Option A is correct since declarative IaC focuses on describing the "what" (e.g., the infrastructure resources needed) rather than the "how" to create them. Tools such as Terraform, Pulumi (in declarative mode), and Kubernetes manifests embody this model.
Option B is incorrect; declarative IaC is particularly well-suited for dynamic environments due to reconciliation loops. Option C is misleading-imperative methods typically provide more granular control, but declarative abstracts it for simplicity. Option D is false; declarative IaC usually reduces coding effort by relying on higher-level abstractions.
This model allows for consistent, reproducible environments, simplifies management, and integrates naturally with GitOps workflows. It reduces human error and ensures the platform continuously enforces the desired infrastructure state.
References:- CNCF GitOps Principles- Kubernetes Declarative Management Model- Cloud Native Platform Engineering Study Guide
NEW QUESTION # 37
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