Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. It’s a standard these days to use Kubernetes clusters in companies.
If you are about to apply for junior positions as a cloud engineer, devops engineer or other position that requires you to know Kubernetes then this article is for you.
You will find top 10 interview questions about this topic with short answers.
What are the key components of Kubernetes architecture?
The key components of Kubernetes architecture include:
- Master node: Controls the cluster and manages its state.
- Worker node: Runs the application containers and communicates with the master node.
- Pod: The basic unit of deployment, which encapsulates one or more containers.
- ReplicaSet: Ensures a specified number of pod replicas are running at all times.
- Service: Provides network connectivity to pods and load balances traffic.
How do you define a Pod in Kubernetes?
A Pod is the smallest and simplest unit in the Kubernetes object model. It represents a single instance of a running process in the cluster. A Pod can contain one or more containers that are tightly coupled and share the same resources, such as network namespace and persistent storage volumes.
What is a Deployment in Kubernetes?
A Deployment is a higher-level Kubernetes object that manages the lifecycle of pods and replica sets. It enables rolling updates, scaling, and rollback of applications. Deployments provide declarative configuration, making it easier to manage and maintain application deployments.
How does Kubernetes handle container networking?
Kubernetes uses a networking model where each Pod gets its own unique IP address.
Containers within a Pod can communicate with each other using localhost. To enable communication between Pods in different nodes, Kubernetes assigns an internal IP address to each Pod and provides network routing.
Explain the concept of scaling in Kubernetes.
Kubernetes supports two types of scaling: horizontal and vertical scaling.
Horizontal scaling, also known as replica scaling, involves increasing or decreasing the number of pod replicas to match the application demand.
Vertical scaling, on the other hand, involves adjusting the resources allocated to individual pods, such as CPU and memory.
How can you expose a Kubernetes service to external traffic?
Kubernetes provides different ways to expose a service to external traffic:
- NodePort: Exposes the service on a static port on each node’s IP address.
- LoadBalancer: Creates an external load balancer to distribute traffic to the service.
- Ingress: Routes external requests to services based on rules defined in an Ingress resource.
What is a StatefulSet in Kubernetes?
A StatefulSet is a Kubernetes object used for managing stateful applications. It provides guarantees about the ordering and uniqueness of pod creation and enables stable network identities and persistent storage for each pod.
StatefulSets are suitable for applications that require stable network identifiers or persistent storage.
How does Kubernetes handle storage?
Kubernetes supports various storage options, such as:
- Volumes: Provides storage that exists as long as the pod exists.
- Persistent Volumes: Allows data to persist beyond the lifecycle of a pod.
- Persistent Volume Claims: Requests and binds to a specific Persistent Volume.
- Storage Classes: Provides dynamic provisioning of storage based on predefined policies.
- What are some common strategies for troubleshooting issues in a Kubernetes cluster? Troubleshooting Kubernetes cluster issues requires a systematic approach, including:
- Analyzing logs and events from various Kubernetes components to identify potential errors or failures.
- Using kubectl commands to inspect and gather information about pods, services, and nodes.
- Checking the status and health of cluster components, such as etcd, API server, and controllers.
- Examining network configurations, including ingress controllers, load balancers, and DNS.
- Utilizing monitoring and observability tools to identify performance bottlenecks or resource constraints.
- Collaborating with development teams to analyze application-specific logs or metrics.
Pythonistka 