EKS interview question

10 Steps to Mastering AWS EKS Interview Questions and Answers

Interview, AWS By Jan 09, 2023 No Comments

Get prepared for your AWS EKS interview with these top 10 frequently asked questions and answers. Learn about the key components of an EKS cluster, how updates are managed, how to deploy containers, how to store and manage secrets, and more. Understand the differences between EKS, ECS, and EC2, and how EKS can be used with other AWS services to build and deploy applications in the cloud.

Also Read : Looking for AWS Interview Question and Answers

What is EKS and why is it used? or What is Amazon EKS, and why is it important?

EKS is a fully managed service that makes it easy to deploy and run Kubernetes on AWS. It allows developers to use Kubernetes to manage their applications, without the need to install and maintain their own Kubernetes clusters.

How does EKS compare to other container orchestration platforms like ECS and Fargate?

EKS is a fully managed service that runs the open-source Kubernetes software, while ECS (Elastic Container Service) is a proprietary container orchestration platform developed by AWS. ECS and Fargate are both good choices for running containers in the AWS cloud, but EKS offers the ability to use the popular and widely-adopted Kubernetes platform, which can be useful if you have an existing investment in Kubernetes or want to use tools and technologies that are compatible with Kubernetes.

Also Read: AWS Skill Builder

How is EKS different from EC2 Container Service (ECS)?

ECS is a container orchestration service that allows you to run and manage containers on EC2 instances. EKS, on the other hand, is a fully managed Kubernetes service that runs on top of EC2 instances. EKS is based on the open-source Kubernetes software, while ECS is a proprietary container orchestration platform developed by AWS.

Also Read this : AWS Ec2 Interview Question And Answer

What are the key components of an EKS cluster?

An EKS cluster consists of three main components:

  • The Kubernetes control plane, which consists of one or more master nodes that run the Kubernetes control plane processes
  • Worker nodes, which are the EC2 instances that run your applications and workloads
  • Add-ons, which are optional components that provide additional functionality to your cluster, such as the Kubernetes dashboard or the Amazon Virtual Private Cloud (VPC) CNI plugin

How are updates to the Kubernetes control plane managed in EKS?

EKS handles updates to the Kubernetes control plane automatically, without requiring any downtime or manual intervention. You can choose to receive email notifications when updates are available, and you can also use the AWS Management Console or the AWS CLI to specify the desired Kubernetes version and upgrade the control plane when desired.

How are worker nodes added to an EKS cluster?

You can add worker nodes to an EKS cluster using the AWS Management Console, the AWS CLI, or the AWS SDKs. You can specify the desired instance type, the number of instances to launch, and the Amazon Machine Image (AMI) to use. You can also use autoscaling to automatically add worker nodes to your cluster based on demand.

How are containers deployed on EKS?

You can deploy containers on EKS using Kubernetes manifest files, which define the desired state of your application. You can use the kubectl command-line tool to apply these manifest files to your cluster, or you can use continuous integration/continuous deployment (CI/CD) tools such as AWS CodePipeline to automate the deployment process.

How are secrets and other sensitive data stored and managed in EKS?

EKS integrates with AWS Secrets Manager, which allows you to store and manage secrets such as database passwords, API keys, and other sensitive data. You can use Secrets Manager to store your secrets and then reference them in your Kubernetes manifest files.

How does EKS handle high availability and fault tolerance?

EKS is designed to be highly available and fault-tolerant. The Kubernetes control plane is automatically distributed across multiple availability zones (AZs) to ensure that it is always available. EKS also provides built-in support for autoscaling worker nodes, which can help ensure that your applications are able to handle changes in demand.

Can EKS be used to run applications that require GPU acceleration?

Yes, EKS supports the use of GPU-powered instances for applications that require GPU acceleration. You can launch worker nodes with GPU-powered instances such as P2 or P3 instances, and then use the Kubernetes resource limits and resource requests feature to ensure that your GPU-accelerated applications are scheduled on these instances.

Also Read this: Master Amazon EKS: Top 20 Expert Interview Questions & Optimization Strategies for Cloud Professionals

How is security managed in EKS?

EKS integrates with various AWS security features and services to help you secure your applications and workloads. For example, you can use IAM to control access to your EKS cluster and resources, and you can use security groups and network ACLs to control inbound and outbound traffic to your cluster. EKS also integrates with AWS Identity and Access Management (IAM) for Kubernetes, which allows you to use IAM policies to fine-tune access control for your cluster resources.

How is monitoring and logging handled in EKS?

EKS integrates with various AWS monitoring and logging services to help you monitor and troubleshoot your applications. For example, you can use Amazon CloudWatch to monitor the performance of your EKS cluster and worker nodes, and you can use CloudWatch Logs to view log data generated by your applications and the Kubernetes control plane. You can also use third-party monitoring and logging tools such as Prometheus and Fluentd, which can be deployed as Kubernetes add-ons in your EKS cluster.

Can EKS be used to run applications across multiple regions and availability zones?

Yes, you can use EKS to run applications across multiple regions and availability zones to achieve greater scalability, availability, and disaster recovery. You can use the AWS Global Accelerator to improve the performance of your applications running in multiple regions, and you can use the AWS App Mesh service to manage traffic between your applications running in different regions.

Can EKS be used with other AWS services?

Yes, EKS can be used with many other AWS services to build and deploy applications in the cloud. For example, you can use EKS with Amazon ECR (Elastic Container Registry) to store and manage your Docker images, with AWS Fargate to run your containers without the need to manage EC2 instances, and with AWS CodePipeline to automate your CI/CD workflow. You can also use EKS with other services such as Amazon RDS (Relational Database Service) and Amazon S3 (Simple Storage Service) to build scalable and reliable applications.

How does Amazon EKS work?

Amazon EKS runs Kubernetes control plane instances across multiple Availability Zones to provide high availability and fault tolerance. It automatically manages the control plane, including API servers and etcd, so you don’t have to worry about the operational aspects. As a user, you only need to provision and manage the worker nodes for your clusters, which run your containerized applications.

What is the role of the Kubernetes control plane in Amazon EKS?

The Kubernetes control plane is responsible for managing the overall state of the cluster, including the API server, etcd datastore, and other essential components. In Amazon EKS, AWS manages the control plane for you, ensuring high availability, reliability, and security.

How do you create and manage a Kubernetes cluster in Amazon EKS?

To create a Kubernetes cluster in Amazon EKS, you can use the AWS Management Console, the AWS CLI, or the AWS SDKs. You will need to provide a unique name for the cluster, specify the Kubernetes version, and choose a VPC and subnet configuration. After the cluster is created, you can manage the worker nodes, deploy applications, and monitor the cluster using Kubernetes tools such as kubectl.

What is the significance of Amazon VPC CNI (Container Network Interface) in Amazon EKS?

Amazon VPC CNI is the default CNI plugin provided by AWS for networking in EKS clusters. It allows Kubernetes pods to have native Amazon VPC IP addresses, enabling seamless communication with other AWS services, and providing better network performance and security. It also supports VPC-native features like VPC Flow Logs, VPC security groups, and network ACLs.

How do you secure your Amazon EKS cluster?

Securing an Amazon EKS cluster involves multiple aspects, such as:

  • Ensuring that the control plane is in a private VPC or using appropriate security groups.
  • Implementing proper IAM policies and roles for users and worker nodes.
  • Using Kubernetes RBAC to restrict access to cluster resources.
  • Implementing network policies to limit communication between pods.
  • Encrypting data at rest and in transit.
  • Regularly scanning container images for vulnerabilities.
  • Implementing proper pod security policies.

What is the difference between Amazon EKS and other managed Kubernetes services like Google Kubernetes Engine (GKE) and Azure Kubernetes Service (AKS)?

While all three services are managed Kubernetes offerings, they have differences in terms of features, integrations, and pricing. Amazon EKS integrates seamlessly with AWS services and provides better support for AWS-specific features, whereas GKE and AKS have better integration with Google Cloud Platform and Microsoft Azure, respectively. Pricing structures and additional features may also vary among the three services.

What is Amazon ECR and how does it relate to Amazon EKS?

Amazon Elastic Container Registry (ECR) is a fully managed Docker container registry service that makes it easy to store, manage, and deploy container images. It integrates with Amazon EKS, allowing you to pull container images from ECR to run on your EKS clusters. ECR provides a secure and scalable solution for storing container images, and it integrates with AWS Identity and Access Management (IAM) for access control.

How do you monitor and troubleshoot an Amazon EKS cluster?

Monitoring and troubleshooting an Amazon EKS cluster can be done using various tools and services:

  • Amazon CloudWatch: Collects and stores metrics, logs, and events from your EKS cluster and its resources, enabling you to monitor performance and set up alarms for specific conditions.
  • AWS X-Ray: Provides distributed tracing for your applications running on EKS, helping you identify performance bottlenecks and issues.
  • Kubernetes Dashboard: Offers a web-based user interface for managing and troubleshooting your cluster.
  • kubectl: A command-line tool for interacting with your cluster, which can be used for debugging and inspecting cluster resources.
  • Prometheus and Grafana: Open-source monitoring tools that can be deployed on your EKS cluster to collect and visualize cluster and application metrics.

What are the supported storage options for Amazon EKS?

Amazon EKS supports various storage options for persistent storage of application data. Some of the supported storage options are:

  • Amazon EBS (Elastic Block Store): Provides block-level storage volumes for use with EC2 instances and can be attached to your EKS worker nodes. EBS volumes support features such as snapshots, encryption, and various performance characteristics.
  • Amazon EFS (Elastic File System): A managed file storage service that can be used with Kubernetes applications through the EFS CSI driver. EFS provides a shared, scalable, and elastic file system, making it suitable for applications that require a shared file storage.
  • Amazon FSx for Lustre: A fully managed, high-performance file system optimized for compute-intensive workloads, such as machine learning and high-performance computing.

What is the role of AWS Fargate in the context of Amazon EKS?

AWS Fargate is a serverless compute engine for containers that allows you to run containers without managing the underlying infrastructure. With Amazon EKS, you can use Fargate to run your Kubernetes pods, eliminating the need to manage and scale worker nodes. Fargate simplifies cluster management and improves security by providing isolation between pods, allowing you to focus on application development and deployment.

What is the significance of Horizontal Pod Autoscaler (HPA) in Amazon EKS?

Horizontal Pod Autoscaler (HPA) is a Kubernetes feature that automatically adjusts the number of pods in a deployment, replicaset, or statefulset based on observed CPU utilization or custom metrics. In Amazon EKS, you can use HPA to ensure that your applications scale up or down based on demand, improving resource utilization and availability. HPA helps maintain the desired performance levels while minimizing infrastructure costs.

How do you implement a multi-tenant Amazon EKS cluster?

Implementing a multi-tenant EKS cluster involves isolating resources and workloads for different tenants (teams, departments, or customers) within a single cluster. Here are some strategies for achieving multi-tenancy in an Amazon EKS cluster:

  • Namespaces: Create separate Kubernetes namespaces for each tenant, providing a logical isolation of resources and workloads.
  • Resource Quotas: Use Kubernetes resource quotas to limit the amount of resources each tenant can consume within their namespace.
  • Network Policies: Implement Kubernetes network policies to restrict traffic between namespaces and control communication between tenant workloads.
  • RBAC: Use Kubernetes Role-Based Access Control (RBAC) to define and enforce granular permissions for each tenant, ensuring they can only access resources within their namespace.
  • Pod Security Policies: Implement Pod Security Policies to enforce security best practices and prevent tenants from running privileged containers or accessing sensitive host resources.

What is the Cluster Autoscaler in Amazon EKS, and why is it important?

The Cluster Autoscaler is a Kubernetes component that automatically adjusts the size of a worker node group based on the demands of your workloads. It monitors the cluster’s resource utilization and adds or removes worker nodes as needed to maintain the desired performance levels.

In Amazon EKS, the Cluster Autoscaler is important for the following reasons:

  • Cost Efficiency: It helps optimize infrastructure costs by ensuring that you only use the required number of worker nodes.
  • Resource Utilization: It improves resource utilization by distributing workloads evenly across the available worker nodes.
  • High Availability: It ensures that your applications have enough resources to run efficiently and maintain high availability, even during peak demand or unexpected traffic spikes.

How do you implement a service mesh in an Amazon EKS cluster?

A service mesh is a dedicated infrastructure layer for handling service-to-service communication within a microservices architecture. It provides features such as load balancing, traffic routing, observability, and security. To implement a service mesh in an Amazon EKS cluster, you can use AWS App Mesh or a third-party service mesh solution like Istio or Linkerd.

  • AWS App Mesh: A fully managed service mesh provided by AWS, which integrates with other AWS services and uses the open-source Envoy proxy for data plane components.
  • Istio: An open-source service mesh that provides traffic management, observability, and security features for microservices. It can be deployed in Amazon EKS clusters using the official Istio Kubernetes operator or Helm charts.
  • Linkerd: Another open-source service mesh focused on simplicity and performance. It can be deployed in Amazon EKS clusters using the Linkerd CLI or Helm charts.

To implement a service mesh, you’ll need to deploy the control plane components, configure the data plane proxies (sidecars), and define the required traffic management, security, and observability configurations according to your application requirements.

What are Amazon EKS Add-ons, and how do they help in managing an EKS cluster?

Amazon EKS Add-ons are a feature that simplifies the deployment and lifecycle management of common Kubernetes operational software. EKS Add-ons allow you to easily install, manage, and update Kubernetes extensions directly from the Amazon EKS console, CLI, or SDKs. They help in managing an EKS cluster by reducing the operational overhead associated with manually managing and updating Kubernetes extensions.

Examples of EKS Add-ons include the Kubernetes Dashboard, Cluster Autoscaler, CoreDNS, and the Amazon VPC CNI plugin.

How do you set up and configure ingress in an Amazon EKS cluster?

Setting up and configuring ingress in an Amazon EKS cluster involves the following steps:

  1. Deploy an Ingress Controller: Choose an Ingress Controller, such as NGINX, ALB (Application Load Balancer), or Traefik, and deploy it in your EKS cluster. The Ingress Controller watches for Ingress resources and provisions the necessary AWS resources (e.g., ALB or Classic Load Balancer) to route external traffic to your cluster.
  2. Create an Ingress Resource: Define an Ingress resource in your Kubernetes manifests, specifying the desired routing rules, hostnames, and backend services. The Ingress Controller will use this configuration to route external traffic to the appropriate services within your cluster.
  3. Configure DNS: Set up a DNS record that maps your desired domain name to the Load Balancer created by the Ingress Controller.
  4. Configure TLS: If you require secure communication (HTTPS), configure TLS certificates for your Ingress resource. You can use AWS Certificate Manager (ACM) to create or import certificates and attach them to your Ingress Controller or Load Balancer.
  5. How do you perform a rolling update of a deployment in Amazon EKS?

Performing a rolling update of a deployment in Amazon EKS involves updating the container image or configuration of a Kubernetes Deployment resource. To do this, you can use the kubectl command-line tool or update the Deployment manifest and apply it using kubectl apply. Here’s an example using kubectl:

kubectl set image deployment/my-deployment my-container=my-repo/my-image:v2

This command updates the container image for the “my-container” container within the “my-deployment” Deployment resource to version “v2”. Kubernetes will automatically perform a rolling update, creating new pods with the updated image and gradually terminating the old pods while maintaining the desired replica count.

How do you implement disaster recovery for an Amazon EKS cluster?

Implementing disaster recovery for an Amazon EKS cluster involves planning and configuring your infrastructure, data, and applications to minimize downtime and data loss in case of a disaster. Here are some strategies to consider:

  • Multi-AZ Deployment: Deploy your EKS control plane and worker nodes across multiple Availability Zones to ensure high availability and fault tolerance.
  • Backups: Regularly back up your cluster’s etcd data, Kubernetes resources, and application data (e.g., using EBS snapshots, EFS backups, or custom backup solutions).
  • Replication: Replicate your critical application data across different regions or accounts to minimize data loss in case of a regional failure.
  • Version Control: Keep your Kubernetes manifests and application code in version control systems (like Git) to ensure a reliable source for restoring your infrastructure and applications.
  • Monitoring and Alerting: Set up monitoring and alerting tools to identify and respond to incidents quickly, minimizing downtime.
  • Runbooks: Create and maintain runbooks with step-by-step instructions for recovering your infrastructure, applications, and data after a disaster.

What are some best practices for optimizing the performance and cost of your Amazon EKS cluster?

Here are some best practices for optimizing the performance and cost of your Amazon EKS cluster:

  1. Right-size worker nodes: Choose the right instance type and size for your worker nodes based on your application requirements, balancing cost and performance. Regularly analyze resource utilization to identify opportunities for resizing your worker nodes.
  2. Use Spot Instances: Leverage AWS Spot Instances for worker nodes to reduce costs significantly compared to On-Demand Instances. Design your applications to be fault-tolerant and handle the potential termination of Spot Instances.
  3. Implement autoscaling: Use the Horizontal Pod Autoscaler (HPA) and Cluster Autoscaler to automatically scale your application pods and worker nodes based on demand. This helps maintain optimal resource utilization and cost efficiency.
  4. Optimize container images: Minimize container image size by using lightweight base images, removing unnecessary files, and leveraging multi-stage builds. Smaller images reduce startup times and save on storage and data transfer costs.
  5. Use persistent storage wisely: Choose the appropriate storage class for your application’s data, considering factors like performance, durability, and cost. Regularly analyze storage usage and delete unused resources to optimize costs.
  6. Implement caching: Use caching mechanisms to store frequently accessed data, reducing the load on your backend services, and improving application performance.
  7. Network optimization: Use VPC peering, AWS PrivateLink, or AWS Transit Gateway to optimize network performance and minimize data transfer costs between your EKS cluster and other AWS services or on-premises infrastructure.
  8. Monitor and analyze: Regularly monitor and analyze your cluster’s resource usage, performance, and cost with tools like Amazon CloudWatch, AWS Cost Explorer, and third-party monitoring solutions. Identify patterns and opportunities for optimization.
  9. Implement resource quotas and limits: Set resource quotas and limits for Kubernetes namespaces to ensure that tenants or applications do not consume excessive resources, impacting the performance and cost of your EKS cluster.
  10. Use AWS Savings Plans or Reserved Instances: If you have a predictable workload and long-term commitment to EKS, consider using AWS Savings Plans or Reserved Instances to reduce your overall compute costs.

By following these best practices, you can optimize the performance and cost of your Amazon EKS cluster, ensuring that your applications run efficiently and cost-effectively.


I'm Abhay Singh, an Architect with 9 Years of It experience. AWS Certified Solutions Architect.

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