100% Pass Quiz 2026 KCNA: Kubernetes and Cloud Native Associate Useful New Test Objectives

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Linux Foundation KCNA Exam Syllabus Topics:

SectionObjectives
Topic 1: Cloud Native Architecture- Microservices and distributed systems
  • 1. Scalability and resilience patterns
    • 2. Service discovery and API gateways
      Topic 2: Container Orchestration- Container lifecycle and scheduling
      • 1. Workload management concepts
        • 2. Container runtimes
          Topic 3: Kubernetes Fundamentals- Core Kubernetes concepts
          • 1. Pods, nodes, and control plane basics
            • 2. Cluster architecture overview
              Topic 4: Cloud Native Observability- Monitoring and logging
              • 1. Observability tools overview
                • 2. Metrics, logs, and tracing concepts
                  Topic 5: Cloud Security and Governance- Security fundamentals in cloud native systems
                  • 1. Identity and access concepts
                    • 2. Basic Kubernetes security principles
                      Topic 6: Cloud Native Application Delivery- CI/CD and deployment strategies
                      • 1. Release strategies (blue/green, canary)
                        • 2. GitOps concepts

                          >> New KCNA Test Objectives <<

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                          Linux Foundation Kubernetes and Cloud Native Associate Sample Questions (Q328-Q333):

                          NEW QUESTION # 328
                          In a serverless computing architecture:

                          Answer: D


                          NEW QUESTION # 329
                          What are the advantages of adopting a GitOps approach for your deployments?

                          Answer: A


                          NEW QUESTION # 330
                          Explain the concept of "service discovery" in Prometheus and how it integrates with Kubernetes.

                          Answer: A

                          Explanation:
                          Service discovery in Prometheus enables it to locate and collect metrics from dynamic Kubernetes environments. It automatically discovers and configures scraping targets based on Kubernetes service definitions. This simplifies the monitoring process and ensures that Prometheus stays up-to-date with changes in the Kubernetes cluster.


                          NEW QUESTION # 331
                          An administrator needs to ensure Pods in the test namespace follow Kubernetes Pod Security Standards to prevent unsafe configurations. The goal is to enforce the Restricted policy. Which action should be taken?

                          Answer: B

                          Explanation:
                          Applying a PodSecurityAdmission configuration with the Restricted standard at the namespace level enforces Kubernetes Pod Security Standards for all Pods in the test namespace, preventing unsafe configurations by blocking noncompliant Pod specifications at admission time.


                          NEW QUESTION # 332
                          What is the core metric type in Prometheus used to represent a single numerical value that can go up and down?

                          Answer: C

                          Explanation:
                          In Prometheus, a Gauge represents a single numerical value that can increase and decrease over time, which makes D the correct answer. Gauges are used for values like current memory usage, number of in-flight requests, queue depth, temperature, or CPU usage-anything that can move up and down.
                          This contrasts with a Counter, which is strictly monotonically increasing (it only goes up, except for resets when a process restarts). Counters are ideal for cumulative totals like total HTTP requests served, total errors, or bytes transmitted. Histograms and Summaries are used to capture distributions (often latency distributions), providing bucketed counts (histogram) or quantile approximations (summary), and are not the "single value that goes up and down" primitive the question asks for.
                          In Kubernetes observability, metrics are a primary signal for understanding system health and performance.
                          Prometheus is widely used to scrape metrics from Kubernetes components (kubelet, API server, controller- manager), cluster add-ons, and applications. Gauges are common for resource utilization metrics and for instantaneous states, such as container_memory_working_set_bytes or go_goroutines.
                          When you build alerting and dashboards, selecting the right metric type matters. For example, if you want to alert on the current memory usage, a gauge is appropriate. If you want to compute request rates, you typically use counters with Prometheus functions like rate() to derive per-second rates. Histograms and summaries are used when you need latency percentiles or distribution analysis.
                          So, for "a single numerical value that can go up and down," the correct Prometheus metric type is Gauge (D).
                          =========


                          NEW QUESTION # 333
                          ......

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