Last updated 19/06/2020
What are the tools you need to know about when you are applying for a DevOps interview?
Just few days back, we spoke about Docker. But what else?
In our blog “8 best DevOps tools in 2020 to bridge the two worlds”, we mentioned that Kubernetes is the most talked-about tool of DevOps world. But why exactly? Well, there is a lot of reasons for that. Kubernetes provide a platform for automating deployment, scaling, and operations of application containers across clusters of hosts. It works with a range of container tools, including Docker. Many cloud services offer a Kubernetes-based platform or infrastructure as a service (PaaS or IaaS) on which Kubernetes can be deployed as a platform-providing service. Many vendors also provide their own branded Kubernetes distributions.
Currently, 9,507 organizations across the world are using Kubernetes. You can understand, if your CV is shining with the Kubernetes skills, you will have an added advantage for obvious reasons in your next DevOps interview. Hence, we have picked up a few mostly asked Kubernetes interview questions for you. Have a look!
Kubernetes is an open-source container management tool that is responsible for container deployment, scaling & descaling of containers & load balancing. Being introduced by Google, Kubernetes offers an excellent community and is capable of working with all the cloud providers. It’s not just a containerization platform, but it is a multi-container management solution.
Docker is the source of the lifecycle management of containers. In fact, the Docker image builds runtime containers. And when these individual containers need to communicate, Kubernetes come in the scene. In a nutshell, Docker builds the containers and these containers communicate with each other via Kubernetes.
When all the services in a container work together to fulfill the needs of a single server, that is called container orchestration.
The interesting features of Kubernetes are:
Being a cloud-agnostic tool that can run on any public/private providers, Kubernetes can load balance, scale & monitor the containers. This way, it becomes your best choice to simplify containerized deployment.
Google Container Engine (GKE) is an open-source management platform for Docker containers and the clusters. This Kubernetes based engine supports only those clusters that run within Google’s public cloud services.
Heapster is a cluster-wide aggregator of data provided by Kubelet running on each node. It’s a container management tool that is supported natively on the Kubernetes cluster and runs as a pod, like other pods in the cluster. It is capable of discovering all nodes in the cluster and queries usage information from the Kubernetes nodes in the cluster.
Minikube is a tool that helps in running Kubernetes locally in a smooth way. It runs a single-node Kubernetes cluster inside a virtual machine.
Kubectl is the platform to pass commands to the cluster. It provides the CLI to run commands against the Kubernetes cluster in several ways to create and manage the Kubernetes component.
Kubelet is an agent service that runs on each node and works on the description of containers provided to it in the PodSpec and ensures that the containers described in the PodSpec are running properly.
Kube-proxy is a network proxy that can run on each and every node and is capable of simple TCP/UDP packet forwarding across backend network service.
Etcd is written in Go programming language and is a distributed key-value store used for coordinating between distributed work. So, Etcd stores the configuration data of the Kubernetes cluster, representing the state of the cluster at any given point in time.
A load balancer is one of the most common and standard ways of exposing service. You can see two kinds of load balancers based on the working environment i.e. Internal Load Balancer and External Load Balancer. The Internal Load Balancer balances load and allocates the pods with the demanded configuration. External Load Balancer directs the traffic from the external load to the backend pods.
Headless Service is similar to a ‘Normal’ service but it does not have a Cluster IP. This service guides you to reach the pods without accessing it through a proxy.
Replica Set and Replication Controller are not very different from each other, as both of them make sure that a specified number of pod replicas are running at any given time. The only difference between them is Replica Set use Set-Based selectors, and on the other hand replication controllers use Equity-Based selectors.
Federated clusters are clusters that can help in managing multiple Kubernetes clusters as a single cluster with the help of federated clusters. Hence, users can create multiple Kubernetes clusters within a data center/cloud and use the federation to control/manage them all in one place.
A Kubernetes cluster is a set of node machines for running containerized applications. At a minimum, a cluster contains a worker node and a master node. The master node is responsible for maintaining the desired state of the cluster, such as which applications are running and which container images they use. Worker nodes actually run the applications and workloads.
There are 2 main components of Kubernetes Architecture
The master node has components like kube-controller-manager, kube-apiserver, kube-scheduler.
The kube – apiserver is based on a scale-out architecture. It is the front-end of the master node control panel. It exposes all the APIs of the Kubernetes Master node components and establishes communication between the Kubernetes Node and the Kubernetes master components.
The kube-scheduler distributes and manages workload on the worker nodes. 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 nodes that are already full.
So that was all about the important Kubernet interview questions. Want to know more about Kubernetes? Join DevOps Training Sessions, and get to know about it in details!
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