We have given a list of top Kubernetes interview questions to help you take your career to the next level. We have included the benefits of Kubernetes, comparison with Docker Swarm, Kubernetes pod, node, Heapster, container cluster, kubelet, GKE, kube-proxy, and more in this blog. Learn Kubernetes from Intellipaat's DevOps Course and fast-track your career!
First, let us compare Kubernetes with Docker Swarm:
Kubernetes is a container orchestration tool that is used for automating the tasks of managing, monitoring, scaling, and deploying containerized applications. It creates groups of containers that can be logically discovered and managed for easy operations on containers.
With the container orchestration tool Kubernetes, it becomes extremely easy to handle containers. We can respond to customer demands by deploying the applications faster and in a more predictable manner.
Here, we will list some of the benefits of Kubernetes:
• Automatic scheduling • Automated rollback • Horizontal scaling • Auto-healing capabilities
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Docker Swarm is a default container orchestration tool that comes with Docker. Docker Swarm can only orchestrate simple Docker containers. Kubernetes, on the other hand, helps manage much more complex software application containers. Kubernetes offers support for larger demand production environment.
Application orchestration in the software process means that we can integrate two or more applications. We will be able to automate arrangement, coordination, and management of computer software. The goal of any orchestration process is to streamline and optimize frequent repeatable processes.
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The Kubernetes namespace is used in the environment wherein we have multiple users spread in the geographically vast areas and working on multiple projects. What the namespace does is dividing the cluster resources between multiple users.
We can think of Kubernetes pod as a group of containers that are run on the same host. So, if we regularly deploy single containers, then our container and the pod will be one and the same.
A node in Kubernetes is a worker machine which is also known as a minion. This node could be a physical machine or a virtual machine. For each node, there is a service to run pods, and it is managed by master components. The node services could include kubelet, kube-proxy, and so on.
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The Heapster lets us do the container cluster monitoring. It lets us do cluster-wide monitoring and event data aggregation. It has native support for Kubernetes.
A container cluster lets us place and manage containers in a dynamic setup. It can be considered as a set of nodes or Compute Engine instances. The API server of Kubernetes does not run on cluster nodes, instead the Container Engine hosts the API server.
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We can think of a kubelet as the lowest level component in a Kubernetes. The kubelet is responsible for making the individual machines run. The sole purpose of a kubelet is that in a given set of containers, it has to ensure that they are all running.
The Minikube makes it easy for the local running of Kubernetes. Within a virtual machine, the Minikube runs a single-node Kubernetes cluster.
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Kubectl is a Kubernetes command-line tool that is used for deploying and managing applications on Kubernetes. Kubectl is especially useful for inspecting the cluster resources, and for creating, updating, and deleting the components.
GKE is Google Kubernetes Engine which is used for managing and orchestrating systems for Docker containers. GKE also lets us orchestrate container clusters within the Google Public Cloud.
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The kube-proxy runs on each of the nodes. It can do simple tasks such as TCP, UDP, forwarding, and so on. It shows the services in the Kubernetes API on each node.
The components of the Kubernetes Master include the API server, the controller manager, the Scheduler, and the etcd components. The Kubernetes Master components are responsible for running and managing the Kubernetes cluster.
It is the Kubernetes Controller Manager. The kube-controller-manager is a daemon that embeds the core control loops which regulates the system state, and it is a non-terminating loop.
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The process of load balancing will let us expose services. There are two types of load balancing when it comes to Kubernetes:
The kube-scheduler has the job of assigning the nodes to the newly created pods.
The primary data store of Kubernetes is etcd, which is responsible for storing all Kubernetes cluster data.
Kubernetes Master assigns a new IP address.
We can set a static IP for Kubernetes load balancer by changing the DNS records whenever Kubernetes Master assigns a new IP address.
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