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Linux Foundation KCNA Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Cloud Native Observability8%- Monitoring & Metrics
  • 1. Tools and standards
    • 2. Core observability signals
      - Logging & Tracing
      • 1. Distributed tracing basics
        • 2. Centralized logging
          Topic 2: Cloud Native Application Delivery8%- Delivery Models
          • 1. GitOps principles
            • 2. CI/CD pipelines
              - Deployment Strategies
              • 1. Application lifecycle management
                • 2. Rolling updates, canary releases
                  Topic 3: Container Orchestration22%- Security & Troubleshooting
                  • 1. Security fundamentals
                    • 2. Basic troubleshooting methods
                      - Orchestration Principles
                      • 1. Why orchestration matters
                        • 2. Runtime environments
                          - Networking & Storage
                          • 1. Cluster networking model
                            • 2. Persistent storage concepts
                              Topic 4: Cloud Native Architecture16%- Cloud Native Principles
                              • 1. 12-factor applications
                                • 2. Microservices design
                                  - Ecosystem & Landscape
                                  • 1. Serverless, service mesh concepts
                                    • 2. CNCF projects overview
                                      Topic 5: Kubernetes Fundamentals46%- Scheduling and Administration
                                      • 1. Basic kubectl operations
                                        • 2. Scheduler concepts
                                          - Containerization Basics
                                          • 1. Containers vs VMs
                                            • 2. Images and registries
                                              - Kubernetes Core Concepts
                                              • 1. Pods, Controllers, Services
                                                • 2. API resources and objects
                                                  • 3. Cluster architecture and components

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                                                    Linux Foundation Kubernetes and Cloud Native Associate Sample Questions (Q24-Q29):

                                                    NEW QUESTION # 24
                                                    In a cloud native environment, what is OpenTelemetry primarily used for?

                                                    Answer: D

                                                    Explanation:
                                                    OpenTelemetry is an open-source observability framework for generating, collecting, processing, and exporting telemetry data such as traces, metrics, and logs to compatible analysis and monitoring backends.


                                                    NEW QUESTION # 25
                                                    In Kubernetes, if the API version of feature is v2beta3, it means that:

                                                    Answer: C

                                                    Explanation:
                                                    The correct answer is B. In Kubernetes API versioning, the stability level is encoded in the version string:
                                                    alpha, beta, and stable (v1). A version like v2beta3 indicates the API is in a beta stage. Beta APIs are more mature than alpha, but they are not fully guaranteed stable in perpetuity the way v1 stable APIs are intended to be. The key implication is that while beta APIs are generally usable, they can still undergo incompatible changes in future releases as the API design evolves.
                                                    Option B captures that meaning: a beta API may change in ways that break compatibility. This is why teams should treat beta APIs with some caution in production: verify upgrade plans, monitor deprecation notices, and be prepared to adjust manifests or client code when moving between Kubernetes versions.
                                                    Why the other options are incorrect:
                                                    * A implies permanence across all future releases in a major version, which is not a beta guarantee.
                                                    Kubernetes has deprecation and graduation processes, but beta does not equal "forever."
                                                    * C overstates safety; beta is typically "tested and enabled by default" for some features, but it's not the same as stable API guarantees.
                                                    * D is too vague and misaligned. While any software may contain bugs, the defining point of "beta API" is about stability/compatibility guarantees, not merely "bugs." In practice, Kubernetes communicates API lifecycle clearly: alpha is experimental and may be disabled by default; beta is feature-complete-ish but may change; stable v1 is strongly compatibility-focused with formal deprecation policies. So, a v2beta3 API signals: usable, but not fully locked-hence B.
                                                    =========


                                                    NEW QUESTION # 26
                                                    What is CloudEvents?

                                                    Answer: B


                                                    NEW QUESTION # 27
                                                    You need to deploy a pod that requires access to a specific GPU device. How can you ensure that
                                                    the pod is scheduled on a node with the required GPU?

                                                    Answer: A

                                                    Explanation:
                                                    You can use both the •nodeselector• and •resources' fields to achieve this: 'nodeselector•: Targets nodes with a label indicating the presence of GPUs (e.g., •gpu: true). •resources': Specify the GPU resource requirements within the container's definition. This provides a more precise way to request specific GPUs and their capabilities. While •tolerations' and 'affinity' can be used for other scheduling needs, they are not directly designed for GPU resource allocation.


                                                    NEW QUESTION # 28
                                                    You are implementing a continuous integration and continuous deployment (CI/CD) pipeline for a cloud native application running in Kubernetes. Which of the following tools can be used for building, testing, and deploying the application to the cluster?

                                                    Answer: A,B,C,D,E

                                                    Explanation:
                                                    All of the listed tools are widely used for CI/CD pipelines and can be integrated with Kubernetes. Each tool has its own strengths and weaknesses depending on your specific needs. Here's a brief overview: Jenkins: Open-source, highly customizable, and supports a wide range of plugins. CircleCl: Cloud-based, user-friendly, and well-suited for smaller teams and projects. Travis Cl: Also cloud-based, popular for open-source projects and known for its simple setup. GitHub Actions: Native to GitHub, allows you to build, test, and deploy directly within your repository. GitLab CI/CD: Integrated with GitLab, provides a complete CI/CD solution with features for building, testing, and deploying applications.


                                                    NEW QUESTION # 29
                                                    ......

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