Certified Kubernetes Administrator (CKA) Interview Questions

The Certified Kubernetes Administrator (CKA) program ensures that a candidate has the skills, abilities, knowledge, and competency to perform the duties of Kubernetes administrators. The Cloud Native Computing Foundation (CNCF) has built CKA as part of its ongoing efforts to help develop the Kubernetes ecosystem. The Certified Kubernetes Administrator exam is a performance-based, online, proctored exam that requires you to solve multiple tasks from a command line running Kubernetes. The exam uses Kubernetes v1.21. Therefore, in order to prepare for Certified Kubernetes Administrator (CKA) job profile, we have curated some Top CKA Interview questions and answers.

Advanced Questions

What is Kubernetes and what are its main components?

Kubernetes is an open-source platform for automating the deployment, scaling, and management of containerized applications. It provides a way to orchestrate and manage containerized workloads and services across multiple hosts in a cluster.

The main components of Kubernetes are:

The API server: the central management point for the cluster, which exposes the Kubernetes API and handles all read and write requests.
etcd: a distributed key-value store that stores the configuration data of the cluster, including the state of the objects such as pods and services.
The controller manager: a daemon that runs controllers, which are responsible for maintaining the desired state of the cluster.
The scheduler: a daemon that assigns pods to nodes based on their resource requirements and other constraints.
The kubelet: a daemon that runs on each node, responsible for starting and stopping pods, and reporting the status of the node to the API server.
The Kube proxy: a daemon that runs on each node and manages the network communication between pods and services.
The pod: the basic unit of deployment in Kubernetes, which can contain one or more containers.
The service: a logical abstraction for pods, which provides a stable endpoint for external access to the pods.
The namespace: a way to organize and divide resources in a cluster.
The volume: a way to persist data for pods, which can be backed by various storage solutions.

How does Kubernetes handle container scaling?

Kubernetes is a container orchestration system that can automatically handle the scaling of containers. It does this by monitoring the resource usage of the containers and adjusting the number of replicas (or copies) of a container as needed.

Kubernetes has several methods for scaling containers, including:

Manual Scaling: Administrators can manually increase or decrease the number of replicas for a given deployment or stateful set.
Autoscaling: Kubernetes can automatically scale the number of replicas based on CPU or memory usage. Administrators can set up autoscaling rules and thresholds, and Kubernetes will adjust the replicas as needed.
Vertical Pod Autoscaling: Kubernetes can automatically scale the resources (such as CPU and memory) allocated to a container, rather than the number of replicas.
Horizontal Pod Autoscaling: Kubernetes can automatically scale the number of replicas based on a metric other than CPU or memory usage, such as the number of requests per second to an application.

Overall, Kubernetes makes it easy to scale containers horizontally or vertically, providing an efficient way of scaling the system to handle the load.

How does Kubernetes handle container failover and self-healing?

Kubernetes handles container failover and self-healing through a combination of features. Pods, which are the basic unit of deployment in Kubernetes, can be configured with a desired number of replicas. This means that if a pod fails, another replica will automatically be created to take its place. Additionally, Kubernetes has built-in health-checking capabilities which can detect when a container is not functioning properly and take action, such as restarting the container or scaling up the number of replicas.

Furthermore, Kubernetes has a feature called “self-healing” which automatically replaces and reschedules containers that fail, or if the node they are running on fails.

How do you handle rolling updates in a Kubernetes cluster?

In Kubernetes, rolling updates can be handled using the kubectl rolling-update command or by using a Deployment resource.

The kubectl rolling-update command can be used to perform a rolling update of an application by updating the image of a ReplicationController or a Deployment. It will update the pods in the ReplicationController or Deployment one at a time, ensuring that at least the specified number of replicas are up at all times during the update.

If you are using a Deployment resource, you can update your application by modifying the container image, and then using the kubectl apply the command to apply the changes. The Deployment controller will then automatically perform a rolling update of the pods, ensuring that at least the specified number of replicas are up at all times during the update.

When a rolling update is performed, the new pods are created with the updated image, and the old pods are gradually terminated. By default, the new pods will be created one at a time, but you can configure the update strategy to create multiple pods at a time if desired.

You can also set the minReadySeconds in the deployment to ensure that a Pod has been running for at least the specified number of seconds before marking it as available during a rolling update.

It’s also possible to define the maxSurge and maxUnavailable in the deployment’s strategy. This will allow you to control the number of replicas that can be created above or below the desired number during an update.

It’s important to monitor the status of the update and ensure that the new pods are healthy and functional before terminating the old ones.

Can you describe the Kubernetes network model and how it handles communication between pods?

Kubernetes uses a software-defined networking (SDN) model to handle communication between pods. In this model, each pod is assigned a unique IP address within the cluster, allowing pods to communicate with each other using standard network protocols such as TCP and UDP.

When a pod is created, Kubernetes automatically creates a virtual network interface on the node where the pod is running. This interface is connected to a virtual network that connects all pods within the cluster. This virtual network is built on top of the underlying infrastructure network and uses overlay networking to provide a consistent network experience across different environments.

In addition to pod-to-pod communication, Kubernetes also provides a number of features to help with service discovery and load balancing. For example, Kubernetes creates a virtual IP (VIP) for each service, which allows pods to access the service using a consistent IP address, regardless of which node the service is running on. Kubernetes also uses a built-in load balancer to automatically distribute incoming traffic to the pods backing a service.

How do you troubleshoot a failed deployment in Kubernetes?

There are several steps you can take to troubleshoot a failed deployment in Kubernetes:

Check the status of the deployment by running the command kubectl get deployments. This will show the current state of the deployment and any associated events.
Look at the pod status by running the command kubectl get pods. This will show the current state of the pods and any associated events.
Check the logs of the pods by running the command kubectl logs <pod-name>. This will show the logs of the container in the pod, which can help to identify any issues.
Check the environment variables of the pods by running the command kubectl exec <pod-name> env. This will show the environment variables that the container is using.
Describe the deployment by running the command kubectl describe deployment <deployment-name>. This will show detailed information about the deployment including the events, conditions, replicas, and more.
Check for resource limits or constraints by running the command kubectl describe pod <pod-name> to check for any resource limits or constraints that may be causing the deployment to fail.
Check for any error message on the status of the pod, deployment, and replicaset
Check for any network connectivity issues by running the command kubectl describe pod <pod-name>
If none of the above steps solve your issue, you can try rolling back the deployment to a previous version using the command kubectl rollout undo deployment/<deployment-name>.
If all the above steps failed, you can try debugging the pod by running the command kubectl exec -it <pod-name> — /bin/bash to access the pod and check the issue manually.

How do you configure security and access controls in a Kubernetes cluster?

There are several ways to configure security and access controls in a Kubernetes cluster:

Role-Based Access Control (RBAC): This allows you to control who can access what resources in the cluster and what actions they can perform on those resources. You can define roles and bindings that specify which users or groups have access to which resources and what actions they can perform on those resources.
Network Policies: Network policies allow you to control traffic flow within the cluster and between pods. You can use network policies to define rules for ingress and egress traffic, such as allowing only specific pods to communicate with other pods or blocking all traffic to a pod except from specific sources.
Pod Security Policies: Pod Security Policies allow you to define security-related constraints on pod creation and updates, such as specifying required privileges and capabilities for a pod, or defining allowed hostPaths for storage.
Authentication and Authorization: Kubernetes supports multiple authentication mechanisms, such as client certificates, tokens, and JSON Web Tokens (JWT). You can also use external authentication providers like OpenID Connect, or LDAP.
Encryption: Kubernetes supports several encryption options, including encrypting secrets at rest, encrypting etcd data, and encrypting network traffic.
Regular Auditing: Regularly audit the resource usage and access logs to detect any suspicious activities or misuse of resources.

It’s important to keep in mind that security is a continuous process and should be regularly reviewed and updated to meet the evolving threat landscape.

Can you describe how you would set up a multi-node Kubernetes cluster?

To set up a multi-node Kubernetes cluster, you would first need to have a basic understanding of Kubernetes and its architecture. You would then need to do the following steps:

Install and configure the Kubernetes control plane: This includes the etcd datastore, the API server, and the controller manager and scheduler.
Set up the worker nodes: These are the nodes that will run your containerized applications. You will need to install and configure the kubelet and Kube proxy on each worker node.
Configure networking: This includes setting up a network overlay such as Flannel, Calico, or Weave Net, as well as configuring communication between the control plane and worker nodes.
Join worker nodes to the cluster: Once the control plane and worker nodes are configured, you will need to join the worker nodes to the cluster by running the kubeadm join command on each node.
Deploy add-ons: Finally, you can deploy add-ons such as the Kubernetes dashboard, monitoring, and logging tools.

It’s important to note that the above steps are a high-level overview and there are many variations and additional steps that could be taken depending on your specific use case.

How do you monitor the health and performance of a Kubernetes cluster?

There are several tools and methods for monitoring the health and performance of a Kubernetes cluster. Some commonly used tools include:

Kubernetes Dashboard: A web-based UI that allows you to view and manage the resources in your cluster, including pods, services, and replica sets.
Prometheus: An open-source monitoring system that can scrape metrics from Kubernetes clusters and alert on potential issues.
Grafana: A visualization tool that can be used in conjunction with Prometheus to display metrics in a graphical format.
kubectl: The command-line tool for interacting with a Kubernetes cluster, which can be used to view the status of pods, services, and other resources.
kubeadm: A command line tool that helps to bootstrap a minimal viable Kubernetes cluster that you can use as a foundation for your cluster.
Kubernetes API-server: Kubernetes API-server is an entry point to the Kubernetes cluster, it exposes various endpoints to access the Kubernetes objects and cluster information.

In addition to these tools, it is also important to monitor the underlying infrastructure on which the Kubernetes cluster is running, such as the network, storage, and compute resources.

Can you describe a scenario where you have used Kubernetes in a production environment?

One scenario where Kubernetes could be used in a production environment is for a large e-commerce company that has multiple microservices-based applications. These microservices are built using different languages and frameworks, and they need to be deployed, scaled and managed in a consistent and efficient manner.

The company could use Kubernetes to deploy and manage these microservices. They could create a Kubernetes cluster that runs on a set of dedicated servers, and use Kubernetes to deploy and manage the containers that run the microservices. Kubernetes would automatically handle tasks such as scaling the number of container instances based on traffic levels, load balancing requests across different instances and rolling out new versions of the microservices.

Additionally, Kubernetes could be used to create different environments such as development, staging, and production, and to manage the promotion of microservices from one environment to another. Kubernetes could also be integrated with other tools such as monitoring, logging, and security to provide a complete production-ready infrastructure.

Overall, Kubernetes provides a powerful platform for managing the deployment, scaling, and management of microservices-based applications in a production environment.

Basic Questions

1. What exactly is Kubernetes?

Kubernetes is an open-source container orchestration tool or system that is used to automate tasks such as containerized application management, monitoring, scaling, and deployment. It is used to easily manage several containers (because it can handle container grouping), allowing for the discovery and management of logical units.

2. What exactly is orchestration in the context of software and DevOps?

Orchestration is the integration of multiple services that enables them to automate processes or synchronize data in real-time. Assume you have six or seven microservices to run an application. If you put them in separate containers, communication will inevitably be hampered. In such a case, orchestration would be useful because it would allow all services in individual containers to work together to achieve a single goal.

3. What is the connection between Kubernetes and Docker?

Docker is a free and open-source platform for software development. Its main advantage is that it packages the settings and dependencies that the software/application requires to run into a container, allowing for portability and a variety of other benefits. Kubernetes enables the manual linking and orchestration of multiple containers running on multiple hosts created with Docker.

4. What are the primary distinctions between Docker Swarm and Kubernetes?

Docker Swarm is Docker’s native, open-source container orchestration platform for clustering and scheduling Docker containers. In the following ways, Swarm differs from Kubernetes:

Firstly, docker Swarm is easier to set up but lacks a robust cluster, whereas Kubernetes is more difficult to set up but provides the assurance of a robust cluster.
Secondly, docker Swarm, like Kubernetes, does not support auto-scaling; however, Docker scaling is five times faster.
Next, docker Swarm lacks a graphical user interface (GUI), whereas Kubernetes has one in the form of a dashboard.
Docker Swarm automatically balances traffic between containers in a cluster, whereas Kubernetes requires manual intervention.

5. What’s the difference between running applications on hosts and running them in containers?

Deploying Applications are made up of architecture and an operating system. The operating system will have a kernel that contains various libraries required for an application that is installed on the operating system. The container host, on the other hand, refers to the system that runs the containerized processes. Because this type is isolated from the other applications, the applications must have the necessary libraries. Because the binaries are isolated from the rest of the system, they cannot infringe on the rights of any other application.

6. What are the characteristics of Kubernetes?

Firstly, Kubernetes gives the user control over which server will host the container. It will decide how to launch. As a result, Kubernetes automates a variety of manual processes.
Secondly, Kubernetes manages multiple clusters at once.
Thirdly, It offers a variety of additional services such as container management, security, networking, and storage.
Next, Kubernetes continuously monitors the health of its nodes and containers.
Users can easily and quickly scale resources not only vertically but also horizontally with Kubernetes.

7. What are the key elements of the Kubernetes architecture?

The master node and the worker node are the two main components of Kubernetes Architecture. Each of these components contains individual components.

8. What is the function of the master node in Kubernetes?

The master node is the node that controls and manages the group of worker nodes. This type is similar to a Kubernetes cluster. The nodes are in charge of cluster management as well as the API used to configure and manage the collection’s resources. The asset of dedicated pods allows Kubernetes master nodes to run alongside Kubernetes itself.

9. What is the function of Kube-apiserver?

This type validates API objects and provides configuration data. It consists of pods, services, and replication controllers. It also serves as the cluster’s frontend and provides REST operations. This frontend cluster state is share by all components that interact with it.

10. What is a Kubernetes node?

A node is the most basic unit of computing hardware. It is a single machine in a cluster, which could be a physical machine in a data centre or a virtual machine from a cloud provider. Each machine in a Kubernetes cluster can take the place of any other machine. In Kubernetes, the master manages the containers on the nodes.

11. What information is contained in the node status?

Address, Condition, Capacity, and Info are the four main components of node status.

12. What is the process that runs on the Kubernetes Master Node?

The Kube-API server process is run on the master node and is use to scale the deployment of additional instances.

13. What exactly is a pod in Kubernetes?

Pods are multi-story structures that encircle one or more containers. This is due to the fact that Kubernetes does not directly run containers. Containers in the same pod share the same local network and resources, allowing them to communicate with other containers in the same pod as if they were on the same machine while maintaining a degree of isolation.

14. What is a Kubernetes container cluster?

A container cluster is a collection of machine elements known as nodes. Clusters set up specific routes for containers running on nodes to communicate with one another. The container engine (rather than the Kubernetes API server) hosts the API server in Kubernetes.

15. What exactly is Google Container Engine?

The Google Container Engine is an open-source management platform design specifically for Docker containers and clusters, with support for clusters running in Google public cloud services.

16. Define Daemon sets.

A Daemon set is a collection of pods that only run once on a host. They are use for host layer attributes such as a network or for network monitoring, which you may not need to run more than once on a host.

17. What exactly is a ‘Heapster’ in Kubernetes?

You can explain what it is and how it has benefited you (if you have used it in your previous work!). A Heapster is a performance monitoring and metrics collection system for Kublet data. This aggregator is natively support and runs like any other pod in a Kubernetes cluster, allowing it to discover and manage other pods.

18. What exactly is Minikube?

Users can run Kubernetes locally with the help of Minikube. This procedure allows you to run a single-node Kubernetes cluster on your personal computer, which can run Windows, macOS, or Linux. Users can use this to experiment with Kubernetes for daily development work.

19. What is a Kubernetes Namespace?

Namespaces are used to allocate cluster resources to multiple users. They are intend for environments with a large number of users spread across projects or teams, and they provide a wide range of resources.

20. What exactly is a Kubernetes controller manager?

The controller manager is a daemon that is responsible for implementing core control loops, garbage collection, and Namespace creation. It allows multiple processes to run on the master node even though they are compile to run as a single process.

21. What are the different kinds of controller managers?

The endpoints controller, service accounts controller, namespace controller, node controller, token controller, and replication controller are the primary controller managers that can run on the master node.

22. Define ClusterIP.

The ClusterIP service is the default Kubernetes service that provides a service within a cluster (with no external access) that other apps within your cluster can use.

23. Explain NodePort.

The NodePort service is the most basic way to direct external traffic to your service. It opens a specific port on each Node and routes any traffic sent to this port to the service.

24. What exactly is the LoadBalancer?

The LoadBalancer service is use to make services available on the internet. For example, a network load balancer generates a single IP address that directs all traffic to your service.

25. What exactly is the Ingress network, and how does it operate?

Ingress is a container object that enables users to access your Kubernetes services from outside the Kubernetes cluster. Users can customise their access by creating rules that specify which inbound connections can reach which services.

26. What do you understand by container resource management?

This activity collects metrics and monitors the health of containerized applications and microservices environments. It helps to improve health and performance while also ensuring that they run smoothly.

27. What exactly is a headless service?

A headless service is use to interact with service discovery mechanisms without being tied to a ClusterIP, allowing you to reach pods directly without having to go through a proxy. It comes in handy when neither load balancing nor a single Service IP address are require.

28. Explain Daemon sets.

29. What do you understand by ‘Heapster’?

A Heapster is a performance monitoring and metrics collection system for Kublet data. This aggregator is natively supporting and runs like any other pod in a Kubernetes cluster, allowing it to discover and manage other pods.

30. What exactly are federated clusters?

Cluster federation is the aggregation of multiple clusters that treat them as a single logical cluster. Multiple clusters can be manage as a single cluster in this case. They are able to remain with the assistance of federated groups. Users can also create multiple clusters within the data center or cloud and use the federation to control or manage them all from a single location.

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