In the world of DevOps and on-premises software development, Kubernetes has emerged as a powerful solution for scaling and managing server setups seamlessly. Derived from a Greek word meaning ‘captain’ or ‘governor,’ Kubernetes empowers operations engineers with a comprehensive toolkit. Whether you are preparing for an interview or a certification exam after completing Kubernetes training, this article will equip you with the top Kubernetes interview questions and their answers. Let’s dive in and explore the essentials.
We are going to cover the Docker & Kubernetes Interview Questions and Answers.
1. Basic Interview Questions
2. Architecture Based Questions
3. Scenario-Based Questions
4. Technical Questions
5. Conclusion
Kubernetes Basic Interview Questions
1. What are the features of Kubernetes?
The features of Kubernetes, are as follows:
Read More: Kubernetes for Beginners
2. How is Kubernetes different from Docker Swarm?
Docker Swarm is Docker’s native, open-source container orchestration platform that is used to cluster and schedule Docker containers. Swarm differs from Kubernetes in the following ways:
- Docker Swarm is more convenient to set up but doesn’t have a robust cluster, while Kubernetes is more complicated to set up but the benefit of having the assurance of a robust cluster
- Docker Swarm can’t do auto-scaling (as can Kubernetes); however, Docker scaling is five times faster than Kubernetes
- Docker Swarm doesn’t have a GUI; Kubernetes has a GUI in the form of a dashboard
- Docker Swarm does automatic load balancing of traffic between containers in a cluster, while Kubernetes requires manual intervention for load balancing such traffic.
- Docker requires third-party tools like ELK stack for logging and monitoring, while Kubernetes has integrated tools for the same
- Docker Swarm can share storage volumes with any container easily, while Kubernetes can only share storage volumes with containers in the same pod
- Docker can deploy rolling updates but can’t deploy automatic rollbacks; Kubernetes can deploy rolling updates as well as automatic rollbacks
Read More: Docker Swarm
3. How are Kubernetes and Docker related?
Docker is an open-source platform used to handle software development. Its main benefit is that it packages the settings and dependencies that the software/application needs to run into a container, which allows for portability and several other advantages. Kubernetes allows for the manual linking and orchestration of several containers, running on multiple hosts that have been created using Docker.
Read More: Kubernetes vs Docker
4. What is the difference between deploying applications on hosts and containers?
Refer to the above diagram. The left-side architecture represents deploying applications on hosts. So, this kind of architecture will have an operating system and then the operating system will have a kernel that will have various libraries installed on the operating system needed for the application. So, in this kind of framework you can have n number of applications and all the applications will share the libraries present in that operating system whereas while deploying applications in containers the architecture is a little different.
This kind of architecture will have a kernel and that is the only thing that’s going to be the only thing common between all the applications. So, if there’s a particular application that needs Java then that particular application we’ll get access to Java and if there’s another application that needs Python then only that particular application will have access to Python.
The individual blocks that you can see on the right side of the diagram are basically containerized and these are isolated from other applications. So, the applications have the necessary libraries and binaries isolated from the rest of the system, and cannot be encroached by any other application.
Read More: Containers for Beginners
5. What is a headless service?
A headless service is used to interface with service discovery mechanisms without being tied to a ClusterIP, therefore allowing you to directly reach pods without having to access them through a proxy. It is useful when neither load balancing nor a single Service IP is required.
Kubernetes Architecture-Based Questions
6. What are the different components of Kubernetes Architecture?
The Kubernetes Architecture has mainly 2 components – the master node and the worker node. As you can see in the below diagram, the master and the worker nodes have many inbuilt components within them. The master node has the kube-controller-manager, kube-apiserver, kube-scheduler, etcd. Whereas the worker node has kubelet and kube-proxy running on each node.
7. What is Kube-proxy?
Kube-proxy is an implementation of a load balancer and network proxy used to support service abstraction with other networking operations. Kube-proxy is responsible for directing traffic to the right container based on IP and the port number of incoming requests.
8. What is the role of kube-apiserver and kube-scheduler?
The kube – apiserver follows the scale-out architecture and, is the front-end of the master node control panel. This exposes all the APIs of the Kubernetes Master node components and is responsible for establishing communication between Kubernetes Node and the Kubernetes master components.
The Kube-scheduler is responsible for distribution and management of workload on the worker nodes. So, it selects the most suitable node to run the unscheduled pod based on resource requirement and keeps a track of resource utilization. It ensures that the workload is not scheduled on already full nodes.
9. Can you explain about the Kubernetes controller manager?
Multiple controller processes run on the master node but are compiled together to run as a single process which is the Kubernetes Controller Manager. So, Controller Manager is a daemon that embeds controllers and does namespace creation and garbage collection. It owns the responsibility and communicates with the API server to manage the end-points.
So, the different types of controller manager running on the master node are :
10. What do you understand by load balancer in Kubernetes?
A load balancer is one of the most common and standard ways of exposing service. There are two types of load balancer used based on the working environment i.e. either the Internal Load Balancer or the External Load Balancer. The Internal Load Balancer automatically balances load and allocates the pods with the required configuration whereas the External Load Balancer directs the traffic from the external load to the backend pods.
Read More: Kubernetes Networking and Services
Kubernetes Scenario-Based Questions
These scenario-based questions and answers provide a glimpse into how candidates would approach real-world challenges in Kubernetes environments. Remember to adapt the answers to your specific experience and knowledge.
1. Suppose a company built on monolithic architecture handles numerous products. Now, as the company expands in today’s scaling industry, their monolithic architecture started causing problems.
How do you think the company shifted from monolithic to microservices and deploy their services containers?
As the company’s goal is to shift from their monolithic application to microservices, they can end up building piece by piece, in parallel and just switch configurations in the background. Then they can put each of these built-in microservices on the Kubernetes platform. So, they can start by migrating their services once or twice and monitor them to make sure everything is running stable. Once they feel everything is going well, then they can migrate the rest of the application into their Kubernetes cluster.
2. Consider a multinational company with a very much distributed system, with a large number of data centers, virtual machines, and many employees working on various tasks.
How do you think can such a company manage all the tasks in a consistent way with Kubernetes?
As all of us know that I.T. departments launch thousands of containers, with tasks running across a numerous number of nodes across the world in a distributed system.
In such a situation the company can use something that offers them agility, scale-out capability, and DevOps practice to the cloud-based applications.
So, the company can, therefore, use Kubernetes to customize their scheduling architecture and support multiple container formats. This makes it possible for the affinity between container tasks that gives greater efficiency with extensive support for various container networking solutions and container storage.
3. Consider a situation, where a company wants to increase its efficiency and the speed of its technical operations by maintaining minimal costs.
How do you think the company will try to achieve this?
The company can implement the DevOps methodology, by building a CI/CD pipeline, but one problem that may occur here is the configurations may take time to go up and running. So, after implementing the CI/CD pipeline the company’s next step should be to work in the cloud environment. Once they start working on the cloud environment, they can schedule containers on a cluster and can orchestrate with the help of Kubernetes. This kind of approach will help the company reduce their deployment time, and also get faster across various environments.
4. Suppose a company wants to revise it’s deployment methods and wants to build a platform which is much more scalable and responsive.
How do you think this company can achieve this to satisfy their customers?
In order to give millions of clients the digital experience they would expect, the company needs a platform that is scalable, and responsive, so that they could quickly get data to the client website. Now, to do this the company should move from their private data centers (if they are using any) to any cloud environment such as AWS. Not only this, but they should also implement the microservice architecture so that they can start using Docker containers. Once they have the base framework ready, then they can start using the best orchestration platform available i.e. Kubernetes. This would enable the teams to be autonomous in building applications and delivering them very quickly.
5. Consider a multinational company with a very much distributed system, looking forward to solving the monolithic code base problem.
How do you think the company can solve their problem?
Well, to solve the problem, they can shift their monolithic code base to a microservice design and then each and every microservices can be considered as a container. So, all these containers can be deployed and orchestrated with the help of Kubernetes.
6. You have an application deployed on Kubernetes that is experiencing increased traffic. How would you scale the application to handle the increased load?
To scale the application, I would follow these steps:
- Identify the bottleneck: Analyze resource utilization, including CPU, memory, and network, to determine the limiting factor.
- Horizontal scaling: If the bottleneck is CPU or memory, I would scale the application horizontally by increasing the number of replicas using a Horizontal Pod Autoscaler (HPA).
- Vertical scaling: If the bottleneck is resource-specific, I would vertically scale the application by upgrading the resources allocated to each pod.
- Monitor and validate: Monitor the application’s performance after scaling to ensure the desired scalability is achieved without impacting stability.
7. You have a Kubernetes deployment running a web application and need to perform a rolling update with zero downtime. How would you accomplish this?
To achieve zero-downtime rolling updates, I would follow these steps:
- Create a new version of the container image with the required changes.
- Update the deployment’s image tag to the new version while keeping the replica count unchanged.
- Monitor the rollout progress using the Kubernetes rollout status command to ensure the update proceeds smoothly.
- Configure the deployment with a readiness probe to verify the availability and stability of the updated pods before considering them ready.
- If any issues occur, use Kubernetes’ rollback feature to revert to the previous version.
- Monitor the application’s logs and metrics to confirm that the rolling update was successful without any disruptions.
8. A critical pod in your Kubernetes cluster fails. How would you identify the issue and recover the application?
To identify the issue and recover the application, I would follow these steps:
- Check the pod’s status and events using the kubectl command to identify any error messages or crash loop errors.
- Inspect the pod’s logs to gather more information about the failure and identify any application-specific errors or exceptions.
- If the issue is related to resource constraints, adjust the resource allocations for the pod or the cluster.
- If the pod is stuck in a crash loop, review the pod’s configuration and ensure any required dependencies or configurations are correctly set up.
- If necessary, delete and recreate the pod to restart the application.
- Monitor the pod’s logs and metrics to verify that the application recovers successfully.
Technical Questions
These technical questions and answers provide a glimpse into various aspects of Kubernetes. Remember to adapt the answers to your specific knowledge and experience.
1. What is the difference between config map and secret? (Differentiate the answers as with examples)
Config maps ideally stores application configuration in a plain text format whereas Secrets store sensitive data like password in an encrypted format. Both config maps and secrets can be used as volume and mounted inside a pod through a pod definition file.
Config map:
kubectl create configmap myconfigmap --from-literal=env=dev
Secret:
echo -n ‘admin’ > ./username.txt echo -n ‘abcd1234’ ./password.txt kubectl create secret generic mysecret --from-file=./username.txt --from-file=./password.txt
2. If a node is tainted, is there a way to still schedule the pods to that node?
When a node is tainted, the pods don’t get scheduled by default, however, if we have to still schedule a pod to a tainted node we can start applying tolerations to the pod spec.
Apply a taint to a node:
kubectl taint nodes node1 key=value:NoSchedul
Apply toleration to a pod:
spec: tolerations: - key: "key" operator: "Equal" value: "value" effect: "NoSchedule"
3. Can we use many claims out of a persistent volume? Explain?
The mapping between persistent volume and persistent volume claim is always one-to-one. Even When you delete the claim, PersistentVolume still remains as we set persistentVolumeReclaimPolicy is set to Retain and Any other claims will not reuse it. Below is the spec to create the Persistent Volume.
apiVersion: v1 kind: PersistentVolume metadata: name: mypv spec: capacity: storage: 5Gi volumeMode: Filesystem accessModes: - ReadWriteOnce persistentVolumeReclaimPolicy: Retain
4. What kind of object do you create, when your dashboard like application, queries the Kubernetes API to get some data?
You should be creating serviceAccount. A service account creates a token and tokens are stored inside a secret object. By default Kubernetes automatically mounts the default service account. However, we can disable this property by setting automountServiceAccountToken: false in our spec. Also, note each namespace will have a service account
apiVersion: v1 kind: ServiceAccount metadata: name: my-sa automountServiceAccountToken: false
5. What is the difference between a Pod and a Job? Differentiate the answers as with examples)
A Pod always ensure that a container is running whereas the Job ensures that the pods run to its completion. Job is to do a finite task.
Examples:
$ kubectl run mypod1 --image=nginx --restart=Never $ kubectl run mypod2 --image=nginx --restart=onFailure $ kubectl get pods NAME READY STATUS RESTARTS AGE mypod1 1/1 Running 0 59s $ kubectl get job NAME DESIRED SUCCESSFUL AGE mypod1 1 0 19s
6. How does Kubernetes handle service discovery and load balancing?
Kubernetes uses two primary components for service discovery and load balancing:
- Services: Kubernetes services provide a stable network endpoint to access a group of pods. Services act as an abstraction layer, allowing clients to connect to the service without needing to know the individual pod’s IP addresses. Kubernetes assigns a virtual IP address and a DNS name to the service, which load balances traffic to the underlying pods.
- kube-proxy: kube-proxy is a network proxy that runs on each node in the Kubernetes cluster. It manages the network routing and load balancing for services. It ensures that traffic sent to a service’s virtual IP address is distributed to the corresponding pods.
7. Explain the difference between a deployment and a statefulset in Kubernetes.
A deployment and a statefulset are two different controllers in Kubernetes with distinct use cases:
- Deployment: A deployment manages stateless applications or microservices. It provides declarative updates, scaling, and rollback capabilities. Deployments are suitable for applications that don’t require stable, unique network identities or stable storage.
- StatefulSet: A statefulset manages stateful applications that require stable network identities and stable storage. It ensures that each pod in the set has a stable hostname, network identity, and persistent storage. StatefulSets are typically used for databases, distributed systems, and applications that require ordered deployment and scaling.
8. How does Kubernetes handle persistent storage for stateful applications?
Kubernetes provides persistent storage through Persistent Volumes (PVs) and Persistent Volume Claims (PVCs):
- Persistent Volume (PV): A PV is a cluster-wide resource that represents a piece of networked storage in the cluster, such as a physical disk or a network-attached storage (NAS). Administrators provision and manage PVs.
- Persistent Volume Claim (PVC): A PVC is a request for a specific amount of storage resources by a user or application. It binds to a suitable PV with matching capacity and access modes. PVCs are used by developers to request and consume storage resources in a more abstracted manner.
Conclusion
Kubernetes is the leading technology, and companies always look for skilled employees. To help you secure a job, we put some effort and listed some preferred topics in Kubernetes Interview Questions.
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Frequently Asked Questions
What is the job market like for Kubernetes professionals?
The job market for Kubernetes professionals is highly promising and continues to grow rapidly. With the increasing adoption of containerization and the need for efficient application deployment and management, organizations across industries are seeking skilled Kubernetes professionals. Job opportunities range from DevOps engineers and Kubernetes administrators to cloud infrastructure engineers and site reliability engineers.
What are the typical job roles and titles in the Kubernetes job market?
The Kubernetes job market offers a variety of roles and titles, including: Kubernetes Administrator, DevOps Engineer, Cloud Infrastructure Engineer, Site Reliability Engineer (SRE), Kubernetes Developer, Kubernetes Architect, Kubernetes Consultant, Containerization Specialist, Cloud Engineer, Platform Engineer
How can I stand out in the competitive Kubernetes job market?
To stand out in the competitive Kubernetes job market, consider the following strategies: Gain practical, Obtain relevant certifications like Certified Kubernetes Administrator (CKA) or Certified Kubernetes Application Developer (CKAD), Build a strong online presence by sharing your projects, Stay up to date with the latest Kubernetes trends.
Related/References
- Visit our YouTube channel “K21Academy”
- Certified Kubernetes Administrator (CKA) Certification Exam
- (CKA) Certification: Step By Step Activity Guides/Hands-On Lab Exercise & Learning Path
- Certified Kubernetes Application Developer (CKAD) Certification Exam
- (CKAD) Certification: Step By Step Activity Guides/Hands-On Lab Exercise & Learning Path
- Create AKS Cluster: A Complete Step-by-Step Guide
- Container (Docker) vs Virtual Machines (VM): What Is The Difference?
- How To Setup A Three Node Kubernetes Cluster For CKA: Step By Step
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