Kubernetes - Interview Question Set-6

 

Question-51: Your company is deploying a mission-critical application that requires high availability. What measures can you take to ensure that the application is highly available in a Kubernetes cluster?

Answer: To ensure high availability of the application, you can take the following measures:

Deploy the application across multiple nodes in the cluster to handle node failures.

Use a load balancer to distribute traffic across multiple replicas of the application.

Use Kubernetes resource primitives like ReplicaSets, DaemonSets, and StatefulSets to manage the scaling and availability of the application.

Use readiness and liveness probes to monitor the health of the application and automatically restart failed instances.

Use network policies to control network access to the application and prevent network outages.

Use Kubernetes storage solutions like Persistent Volumes and Persistent Volume Claims to provide durable storage for the application data.

Question-52: Your company has decided to adopt microservices architecture and wants to deploy the services on a Kubernetes cluster. What considerations do you need to keep in mind while deploying the services on a cluster?

Answer: When deploying microservices on a Kubernetes cluster, you need to consider the following:

Networking: Ensure that the network policies allow communication between the services and provide secure communication between the services and external systems.

Service discovery: Use Kubernetes service discovery mechanisms like environment variables, DNS, or a service registry to allow the services to locate each other.

Scaling: Use Kubernetes resource primitives like ReplicaSets and Horizontal Pod Autoscaler to scale the services based on demand.

Resource Management: Ensure that each service has the necessary resources (CPU, memory, and storage) to operate efficiently and that the services can share resources fairly.

Deployment strategy: Choose a deployment strategy that meets the availability and reliability requirements of each service, such as rolling updates, blue/green deployments, or canary releases.

Question-53: Your company is planning to adopt a multi-cloud strategy and wants to deploy its applications on multiple cloud platforms. How can you use Kubernetes to manage the deployment and operations of the applications on multiple cloud platforms?

Answer: You can use Kubernetes to manage the deployment and operations of the applications on multiple cloud platforms by using the following tools and techniques:

Kubernetes multi-cluster management solutions: Tools like cluster federation and kubefed can help manage multiple Kubernetes clusters deployed on different cloud platforms.

Cluster portability: Use Kubernetes cluster APIs and manifests to ensure that the applications can be easily moved between cloud platforms.

Multi-cloud network solutions: Use network solutions that can span multiple cloud platforms to provide network connectivity between the applications and ensure that they can communicate with each other.

Cloud-agnostic storage solutions: Use storage solutions that can work across multiple cloud platforms to provide durable storage for the application data.

Cloud-native CI/CD pipelines: Use cloud-native CI/CD pipelines to automate the deployment and operations of the applications on different cloud platforms.

Question-54: Your company is deploying a legacy application that is not designed to run in a containerized environment. How can you run this application in a Kubernetes cluster?

Answer: You can run a legacy application in a Kubernetes cluster by using the following approaches:

Wrapper scripts: Write wrapper scripts that launch the legacy application as a foreground process in a container and pass any required command-line arguments or environment variables.

Virtual Machines: Deploy the legacy application in a virtual machine (VM) and use Kubernetes to manage the VMs as if they were containers.

Process managers: Use a process manager like supervisord to run the legacy application as a background process in a container and monitor its health and restart it if it fails

Question-55: Your company wants to implement an autoscaling solution for its Kubernetes cluster. What are the different ways to implement autoscaling in a Kubernetes cluster and what are the benefits and drawbacks of each approach?

Answer: There are several ways to implement autoscaling in a Kubernetes cluster:

Horizontal Pod Autoscaler: This is a built-in Kubernetes resource that can automatically scale the number of replicas of a deployment based on resource utilization or custom metrics. The benefits of this approach include ease of use and integration with other Kubernetes resources. The drawback is that it only scales the number of replicas, not the resources of individual pods.

Custom Autoscaler: This involves writing custom code that implements an autoscaling algorithm and integrates with the Kubernetes API. The benefits of this approach include more control over the scaling algorithm and the ability to scale based on custom metrics. The drawback is the added complexity of writing and maintaining custom code.

Third-party Autoscaler: This involves using a third-party solution that integrates with Kubernetes to provide autoscaling functionality. The benefits of this approach include pre-built functionality and integration with other tools and services. The drawback is the potential for vendor lock-in and the added complexity of integrating with a third-party solution.