[Feb-2026] Linux Foundation KCNA DUMPS WITH REAL EXAM QUESTIONS
2026 New DumpStillValid KCNA PDF Recently Updated Questions
The Kubernetes and Cloud Native Associate certification exam is designed to be challenging, and candidates are expected to have a thorough understanding of the topics covered. KCNA exam consists of multiple-choice questions and practical exercises, which test the candidate’s ability to apply their knowledge in real-world scenarios. KCNA exam is administered online, and candidates can take it from anywhere in the world.
Linux Foundation is a non-profit organization that provides support and resources for open-source software projects. One of its most popular offerings is the Kubernetes and Cloud Native Associate (KCNA) certification exam. Kubernetes and Cloud Native Associate certification is designed for professionals who want to demonstrate their expertise in managing and deploying cloud-native applications using Kubernetes.
NEW QUESTION # 67
How does service logical group set of pods?
- A. Using label and selectors
- B. Using hostname
- C. Using IP address
Answer: A
Explanation:
https://kubernetes.io/docs/concepts/services-networking/service/
NEW QUESTION # 68
Observability and monitoring are not the same?
- A. True
- B. False
Answer: A
NEW QUESTION # 69
Which control plane component is responsible for scheduling pods?
- A. kube-proxy
- B. kube scheduler
- C. kubelet
- D. kube api-server
Answer: B
Explanation:
https://kubernetes.io/docs/concepts/overview/components/
NEW QUESTION # 70
What is the command used to scale the application?
- A. kubectl scale
- B. kubectl run
- C. kubectl explain
Answer: A
Explanation:
https://kubernetes.io/docs/reference/generated/kubectl/kubectl-commands#scale
NEW QUESTION # 71
What is the purpose of the kube-proxy component in Kubernetes?
- A. Monitors and manages the health and status of Pods and other Kubernetes objects
- B. Enables communication between Pods and services within a Kubernetes cluster.
- C. Provides a secure and reliable connection between the Kubernetes control plane and nodes-
- D. Stores the configuration and state of the Kubernetes cluster
- E. Manages the Kubernetes API server and handles authentication and authorization requests.
Answer: B
Explanation:
kube-proxy acts as a network proxy that enables communication between Pods and services within a Kubernetes cluster. It handles service discovery, load balancing, and network rules for Pods.
NEW QUESTION # 72
What is the primary role of the kubelet in the Kubernetes runtime environment?
- A. Scheduling pods to nodes based on resource availability.
- B. Managing the network connectivity for pods in the cluster.
- C. Maintaining the health of the Kubernetes master node.
- D. Ensuring that pods are running as specified in their YAML files.
- E. Managing the communication between nodes in the cluster.
Answer: D
Explanation:
The kubelet is responsible for ensuring that pods are running as specified in their YAML files. It monitors the containers within a pod, restarts them if they fail, and manages the resources allocated to the pod. The kubelet is a crucial component of the Kubernetes runtime environment, ensuring that pods are running correctly and as expected.
NEW QUESTION # 73
There are three Nodes in a cluster, and want to run exactly one replica of a Pod on each Node. Pre-fer to automatically create a replica on any new Nodes when they are added. Which Kubernetes re-source should you use?
- A. StatefulSet
- B. DaemonSet
- C. Deployment
- D. NodeSet
- E. ReplicaSet
Answer: B
Explanation:
https://kubernetes.io/docs/concepts/workloads/controllers/daemonset/
A DaemonSet runs replicas on all (or just some) Nodes in the cluster.
NEW QUESTION # 74
How would you return all the pod data in the json format using kubectl command?
- A. kubectl get pods --all-namspaces
- B. kubectl get pods -o json
- C. kubectl get pods -o wide
- D. kubectl get pods -o jsonpath
Answer: B
Explanation:
https://kubernetes.io/docs/reference/generated/kubectl/kubectl-commands#get
NEW QUESTION # 75
Which role is responsible of creating service level indicator 'SLI', service level objective 'SLO', & Service Level Agreements 'SLA'
- A. DevOps
- B. Developer
- C. Security and compliance engineer
- D. GitOps
- E. Site reliability engineer 'SRE'
Answer: E
Explanation:
https://www.atlassian.com/incident-management/kpis/sla-vs-slo-vs-sli
NEW QUESTION # 76
Which organizational persona creates Service Level Agreements 'SLA', Service Level Objectives 'SLO', and Service Level Indicator 'SLI'?
- A. Security and Compliance Engineer
- B. Site Reliability Engineer (SRE)
- C. DevOps
- D. DevSecOps
- E. Developer
Answer: B
Explanation:
SREs create SLAs, SLOs, and SLIs to define and implement standards for application and infra-structure reliability.
NEW QUESTION # 77
You're running a stateful application in Kubernetes with a HorizontalPodAutoscaler (HPA) configured. You want to ensure that scaling does not disrupt the application's state. What approach would you take to address this concern?
- A. Use a StatefulSet to manage the deployment of the application.
- B. Use a persistent volume claim (PVC) to store the application's state.
- C. Disable scaling for the application to maintain state consistency.
- D. Implement a custom scaling logic that ensures state persistence during scaling events.
- E. Configure the HPA to scale up and down only when the application is idle.
Answer: A,B,D
Explanation:
Several approaches can help maintain state during scaling for stateful applications: StatefulSets (A) manage stateful applications by providing persistent storage and stable network identities for Pods- Custom scaling logic (C) allows you to implement specific scaling strategies that preserve state, such as graceful shutdowns and data synchronization. Persistent volume claims (PVCs) (D) ensure that the application's data is stored on persistent volumes, preserving it even during scaling events. While options B and E might seem appealing, they are not practical solutions. Scaling during idle periods might not cover all scenarios, and disabling scaling altogether eliminates the benefits of autoscaling.
NEW QUESTION # 78
You are building a cloud-native application that uses a combination of Kubernetes, Istio, and Prometheus. You want to ensure that your application's logs, metrics, and traces are correlated for easy troubleshooting. What approach would you take to achieve this correlation?
- A. Use a custom logging agent to collect logs and forward them to Prometheus.
- B. Integrate Jaeger with Istio and Prometheus using the Istio Mixer to enrich tracing data with metrics and log information.
- C. Use the •kubectl logs* command to retrieve logs from individual pods and manually correlate them with metrics and traces.
- D. Use a centralized logging system like Fluentd to collect logs from Kubernetes and forward them to Prometheus.
- E. Configure Istio to capture logs from pods and forward them to Prometheus.
Answer: B
Explanation:
The correct answer is B . Istio's Mixer allows you to integrate Jaeger with Istio and Prometheus. This integration enables you to enrich tracing data with relevant metrics and log information captured from Istio's traffic management capabilities. This approach provides a unified platform for correlating logs, metrics, and traces. The other options are not as effective for achieving correlation: A : This approach focuses only on logs and does not provide a way to link logs to metrics or traces. C : While Istio can capture logs, sending them to Prometheus is not an ideal solution for correlation. D : A centralized logging system like Fluentd can collect logs, but it does not inherently provide mechanisms to correlate them with metrics or traces. E : Manually correlating logs, metrics, and traces using 'kubectl logs is tedious and prone to errors, especially in a dynamic environment like Kubernetes.
NEW QUESTION # 79
You are using a Kubernetes deployment to run a web application. You want to roll out a new version of the application with minimal downtime. Which strategy can be used to achieve this?
- A. Recreate
- B. Canary
- C. RollingUpdate
- D. Immutable
- E. BlueGreen
Answer: B,C,E
Explanation:
RollingUpdate, BlueGreen, and Canary are all strategies that can be used to roll out new application versions with minimal downtime. RollingUpdate updates Pods one by one, ensuring that there are always healthy Pods running. BlueGreen creates two separate environments, one for the old version and one for the new version, and then switches traffic over to the new environment. Canary gradually rolls out the new version to a small subset of users before making it available to everyone. Option 'A' (Recreate) would completely stop the old Pods before creating new ones, which could lead to downtime. Option 'E' (Immutable) is not a deployment strategy for rolling out updates.
NEW QUESTION # 80
What command can you use to get documentation about a resource type from the command line?
- A. kubectl api-resources
- B. kubectl get
- C. kubectl explain
- D. kubeadm get-resource
Answer: C
Explanation:
https://kubernetes.io/docs/reference/generated/kubectl/kubectl-commands#explain
NEW QUESTION # 81
Which of the following is NOT a key characteristic of a serverless architecture?
- A. Automatic scaling based on workload demand
- B. Pre-provisioned and managed servers-
- C. Focus on business logic rather than infrastructure management
- D. Pay-per-use pricing model.
- E. Event-driven execution model.
Answer: B
Explanation:
Serverless architectures are designed to abstract away the need for managing servers. They rely on cloud providers to handle provisioning, scaling, and infrastructure maintenance. Option C, Pre-provisioned and managed servers, contradicts the core principle of serverless computing, which is to avoid managing server infrastructure.
NEW QUESTION # 82
What kubectl command is used to edit a resource on the server?
- A. kubectl resource edit
- B. kubectl edit
- C. kubectl resource modify
- D. kubectl update resource
Answer: B
Explanation:
https://kubernetes.io/docs/reference/generated/kubectl/kubectl-commands#edit
NEW QUESTION # 83
Consider a serverless application on AWS Lambda that needs to read data from an Amazon S3 bucket. Which of the following is the most efficient way to access data from the S3 bucket within the Lambda function?
- A. Download the entire S3 object into the Lambda function's memory.
- B. Use the AWS SDK for Python (Bot03) to access S3 objects directly.
- C. Utilize AWS Kinesis to stream data from S3 to the Lambda function.
- D. Stream data directly from S3 to the Lambda function using the S3 API.
- E. Use AWS Lambda's built-in S3 client to read data from the bucket.
Answer: D
Explanation:
Streaming data directly from S3 to the Lambda function using the S3 API is the most efficient approach. It avoids downloading the entire object into memory reduces memory usage, and minimizes latency Option A is inefficient for large objects. Option B and C are valid methods but might introduce unnecessary overhead. Option E uses Kinesis for streaming but is overkill for a simple S3-to-Lambda data access scenario.
NEW QUESTION # 84
You are migrating a monolithic application to a microservices architecture on Kubernetes. You choose to use Istio to manage the communication between these new services. Which of the following is NOT a benefit of adopting Istio in this scenario?
- A. Istio simplifies the process of migrating existing code to a microservices architecture
- B. Istio allows for easier debugging and troubleshooting of complex microservice interactions
- C. Istio helps in achieving better scalability and fault tolerance for microservices
- D. Istio provides a consistent way to handle network calls and security across all microservices
- E. Istio's control plane simplifies the deployment and management of microservices
Answer: A
Explanation:
While Istio provides benefits like centralized traffic management, security, and observability for microservices, it doesn't automatically simplify the process of migrating existing monolithic code. The migration itself requires careful refactoring and architectural changes, which Istio complements but doesn't replace. Options B, C, D, and E are all valid benefits of using Istio for microservices.
NEW QUESTION # 85
Your CI/CD pipeline needs to test a new feature before deploying to production. Which of the following Kubernetes features best supports this scenario?
- A. Secrets
- B. ConfigMaps
- C. Namespaces
- D. Services
- E. Deployments
Answer: C
Explanation:
Namespaces provide isolated environments within a Kubernetes cluster. By creating separate namespaces for development, testing, and production, you can test new features in a controlled environment without impacting production.
NEW QUESTION # 86
You have a Kubernetes cluster with multiple applications deployed. Each application is instrumented to emit logs, metrics, and traces. You want to use a single dashboard to visualize the performance of all applications in a unified view. What are the possible approaches to achieve this?
- A. Configure Kubernetes to forward logs, metrics, and traces to a centralized observability platform like CloudWatch or Stackdriver.
- B. Use Prometheus to aggregate metrics from all applications and create a single dashboard.
- C. Use Grafana to create a single dashboard that queries data from Prometheus and Jaeger.
- D. Use a custom application to collect and aggregate data from Prometheus, Jaeger, and Loki, and then visualize the data on a custom dashboard.
- E. Use Loki for log aggregation and create a single dashboard in Grafana to visualize logs, metrics, and traces.
Answer: A,B,C,D,E
Explanation:
All of the provided options can contribute to achieving a unified dashboard for visualizing the performance of multiple applications. Each option has its strengths and weaknesses: A: Use Prometheus to aggregate metrics from all applications and create a single dashboard. Prometheus is a powerful tool for collecting and aggregating metrics. You can use Prometheus's query language to fetch data from multiple applications and create a centralized dashboard in Grafana or a custom application. B: Use Grafana to create a single dashboard that queries data from Prometheus and Jaeger. Grafana is a popular dashboarding tool that can visualize data from multiple sources. It can query metrics from Prometheus and tracing data from Jaeger to create a unified view. C: Use Loki for log aggregation and create a single dashboard in Grafana to visualize logs, metrics, and traces. Loki is a log aggregation system that can collect logs from various sources, including Kubernetes. By integrating Loki with Grafana, you can visualize logs, metrics, and traces on a single dashboard. D: Use a custom application to collect and aggregate data from Prometheus, Jaeger, and Loki, and then visualize the data on a custom dashboard. You can build a custom application to collect data from Prometheus, Jaeger, and Loki and then create a custom dashboard using a framework like React or Vue.js. This allows you to have full control over the data aggregation and visualization process. E: Configure Kubernetes to forward logs, metrics, and traces to a centralized observability platform like CloudWatch or Stackdriver. Cloud-based observability platforms like Amazon CloudWatch or Google Stackdriver provide a centralized platform for collecting, aggregating, and visualizing data from multiple applications. These platforms often have pre- built dashboards and alerting capabilities, making it easy to monitor and analyze data from different applications in a unified view. The best approach depends on your specific needs, resources, and preferred tools. You can choose a combination of these options to meet your requirements.
NEW QUESTION # 87
You have a CI/CD pipeline that builds and deploys a new version of your application to Kubernetes. After deployment, you notice performance issues and need to roll back to the previous version. Which of the following strategies can be used to achieve a smooth rollback?
- A. Edit the Deployment configuration to change the container image to the previous version.
- B. Use Kubernetes Deployments with rollback capabilities to revert to a previous deployment revision.
- C. Use a canary deployment strategy to gradually roll back the traffic.
- D. Redeploy the previous version of the application manually.
- E. Manually delete the new pods and restart the old pods.
Answer: B
Explanation:
Kubernetes Deployments track historical revisions. By leveraging rollback capabilities within Deployments, you can easily revert to a previous successful deployment revision, ensuring a smooth transition without manual intervention.
NEW QUESTION # 88
You are running a stateful application on Kubernetes that requires persistent data storage. Which of the following Kubernetes storage classes would be most suitable for this scenario?
- A. Persistent Volumes
- B. Local Persistent Volumes
- C. HostPath
- D. Standard
- E. Ephemeral
Answer: A
Explanation:
Persistent Volumes (PVs) are the most suitable storage class for stateful applications- They guarantee persistent data storage across pod restarts and provide a consistent interface for accessing the data
NEW QUESTION # 89
What is FinOps?
- A. The first step in any cloud transformation
- B. Specialized cloud features used by financial industries (example: banks, insurance, etc)
- C. Using data to make cost savings decisions about cloud usage
- D. Stage beyond DevOps or DevSecOps, where organization transition to serverless tech-nologies
Answer: C
Explanation:
https://www.servicenow.com/products/it-asset-management/what-is-finops.html
NEW QUESTION # 90
You are working on a Kubernetes deployment for a microservices-based application. You need to enforce consistent configuration across different environments (development, staging, production). Which of the following approaches is most appropriate?
- A. Hardcoding configuration values within the application code
- B. Using a third-party configuration management tool like Chef or Puppet
- C. Deploying the application using Docker Compose
- D. Manually configuring each pod with environment-specific values
- E. Using Kubernetes ConfigMaps to store and manage configuration data
Answer: E
Explanation:
Kubernetes ConfigMaps provide a native mechanism for storing and managing configuration data in a central location. This allows for consistent configuration across different environments and simplifies the process of updating configurations without modifying the application code.
NEW QUESTION # 91
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