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[Hardware] CNPA Pass-King Torrent - CNPA Actual Exam & CNPA Exam Torrent

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【Hardware】 CNPA Pass-King Torrent - CNPA Actual Exam & CNPA Exam Torrent

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Linux Foundation CNPA Exam Syllabus Topics:
TopicDetails
Topic 1
  • 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 2
  • 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.
Topic 3
  • 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.
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.

Linux Foundation Certified Cloud Native Platform Engineering Associate Sample Questions (Q34-Q39):NEW QUESTION # 34
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. Prometheus
  • B. ELK Stack
  • C. Grafana
  • D. OpenTelemetry
Answer: A
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 # 35
In a Kubernetes environment, what is the primary distinction between an Operator and a Helm chart?
  • A. Operators handle ongoing management of custom resources while Helm charts focus on packaging and deployment.
  • B. Helm charts use Custom Resource Definitions while Operators use static manifests.
  • C. Operators are only for deploying applications, while Helm charts manage application resources.
  • D. Both Operators and Helm charts are the same, just different names used in the community.
Answer: A
Explanation:
The key distinction is that Helm charts are packaging and deployment tools, while Operators extend Kubernetes controllers to provide ongoing lifecycle management. Option C is correct because Operators continuously reconcile the desired and actual state of custom resources, enabling advanced behaviors like upgrades, scaling, and failover. Helm charts, by contrast, define templates and values for deploying applications but do not actively manage them after deployment.
Option A oversimplifies; Operators do more than deploy, while Helm manages deployment packaging.
Option B is incorrect-Helm does not create CRDs by default; Operators often do. Option D is incorrect because Operators and Helm serve different purposes, though they may complement each other.
Operators are essential for complex workloads (e.g., databases, Kafka) that require ongoing operational knowledge codified into Kubernetes-native controllers. Helm is best suited for standard deployments and reproducibility. Together, they improve Kubernetes extensibility and automation.
References:- CNCF Kubernetes Operator Pattern Documentation- CNCF Platforms Whitepaper- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 36
In a GitOps workflow, how should application environments be managed when promoting an application from staging to production?
  • A. Use a tool to package the application and deploy it directly to production.
  • B. Create a new environment for production each time an application is updated.
  • C. Manually update the production environment configuration files.
  • D. Merge changes and let a tool handle the deployment
Answer: D
Explanation:
In GitOps workflows, the source of truth for environments is stored in Git. Promotion from staging to production is managed by merging changes into the production branch or repository. Option A is correct because once changes are merged, the GitOps operator (e.g., Argo CD, Flux) automatically detects the updated desired state in Git and reconciles it with the production environment.
Option B (creating new environments each time) is inefficient and unnecessary. Option C (manual updates) violates GitOps principles of automation and auditability. Option D (direct deployments) reverts to a push- based CI/CD model rather than GitOps' pull-based reconciliation.
By relying on Git as the single source of truth, GitOps ensures version control, auditability, and rollback capabilities. This allows consistent, reproducible promotion between environments while reducing human error.
References:- CNCF GitOps Principles- CNCF Platforms Whitepaper- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 37
In the context of observability, which telemetry signal is primarily used to record events that occur within a system and are timestamped?
  • A. Metrics
  • B. Alerts
  • C. Traces
  • D. Logs
Answer: D
Explanation:
Logs are detailed, timestamped records of discrete events that occur within a system. They provide granular insight into what has happened, making them crucial for debugging, auditing, and incident investigations.
Option A is correct because logs capture both normal and error events, often containing contextual information such as error codes, user IDs, or request payloads.
Option B (alerts) are secondary outputs generated from telemetry signals like logs or metrics and are not raw data themselves. Option C (traces) represent the flow of requests across distributed systems, showing relationships and latency between services but not arbitrary events. Option D (metrics) are numeric aggregates sampled over intervals (e.g., CPU usage, latency), not discrete, timestamped events.
Observability guidance in cloud native systems emphasizes the "three pillars" of telemetry: logs, metrics, and traces. Logs are indispensable for root cause analysis and compliance because they preserve historical event context.
References:- CNCF Observability Whitepaper- OpenTelemetry Documentation (aligned with CNCF)- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 38
In the context of Agile methodology, which principle aligns best with DevOps practices in platform engineering?
  • A. Teams should continuously gather feedback and iterate on their work to improve outcomes.
  • B. Teams should strictly adhere to initial project plans without making adjustments during development.
  • C. Development and operations teams should remain separate to maintain clear responsibilities.
  • D. Customer involvement should be limited during the development process to avoid disruptions.
Answer: A
Explanation:
Agile and DevOps share the principle of continuous improvement through rapid feedback and iteration.
Option B is correct because gathering feedback continuously and iterating aligns directly with DevOps practices such as CI/CD, observability-driven development, and platform engineering's focus on developer experience. This ensures platforms and applications evolve quickly in response to real-world conditions.
Option A contradicts Agile, which emphasizes active customer collaboration. Option C reflects rigid waterfall methodologies, not Agile or DevOps. Option D enforces silos, which is the opposite of DevOps principles of cross-functional collaboration.
By embracing continuous feedback loops, both Agile and platform engineering accelerate delivery, improve resilience, and ensure that platforms deliver real value to developers and end users. This cultural alignment ensures both speed and quality in cloud native environments.
References:- Agile Manifesto Principles- CNCF Platforms Whitepaper- Cloud Native Platform Engineering Study Guide

NEW QUESTION # 39
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