👉 How to deploy a Kubernetes cluster on AWS EKS: Ultimate Guide

👉 How to deploy a Kubernetes cluster on AWS EKS

👉 Did you know that Kubernetes is the most popular container orchestration tool, with over 91% adoption among enterprises? (Source: CNCF) Are you struggling to deploy Kubernetes on AWS EKS? You're not alone. In this comprehensive guide, we'll walk through every step of the process, from setup to optimization, catering to beginners, advanced users, DevOps, and engineers. Let's dive in!

What is Kubernetes?

Kubernetes, often abbreviated as K8s, is an open-source container orchestration platform designed to automate deploying, scaling, and managing containerized applications. It groups containers that make up an application into logical units for easy management and discovery.

What is AWS EKS?

AWS EKS (Elastic Kubernetes Service) is a fully managed Kubernetes service provided by Amazon Web Services. It eliminates the need for users to install, operate, and maintain their Kubernetes clusters, offering scalability, high availability, and security out of the box.

Components of Kubernetes:

👉 Master Node: Controls the Kubernetes cluster and manages its state.

👉 Worker Node: Executes tasks as directed by the master node.

👉 Pods: Basic units that run one or more containers.

👉 Deployments: Manage the lifecycle of Pods.

👉 Services: Enable communication between different parts of an application.

How the System Works:

Kubernetes follows a client-server architecture, where the master node acts as the control plane and the worker nodes run the actual application workloads. The master node communicates with the worker nodes to schedule and manage containers based on the desired state specified by the user through manifests or API calls. This declarative approach ensures that the cluster maintains the desired state even in the face of failures or changes.

Understanding the Important Keywords and Terminologies:

👉 Containerization: Containerization is a lightweight alternative to full machine virtualization that involves encapsulating an application in a container with its own runtime environment.

👉 Amazon Web Services (AWS): AWS is a comprehensive, evolving cloud computing platform provided by Amazon that includes a mixture of infrastructure as a service (IaaS), platform as a service (PaaS), and packaged software as a service (SaaS) offerings.

👉 Orchestration: Orchestration refers to the automated arrangement, coordination, and management of complex computer systems, middleware, and services.

👉 Cluster: A cluster is a group of interconnected computers that work together as a single system to ensure that high availability, load balancing, and scalability are achieved.

👉 Scalability: Scalability refers to the ability of a system to handle a growing amount of work by adding resources or nodes to the system.

👉 High Availability: High availability is a characteristic of a system that aims to ensure an agreed level of operational performance, usually uptime, for a higher than normal period.

👉 Container Orchestration: Container orchestration is the process of automating the deployment, scaling, and management of containerized applications.

👉 Infrastructure as Code (IaC): Infrastructure as Code is the practice of managing and provisioning computing infrastructure through machine-readable definition files, rather than physical hardware configuration or interactive configuration tools.

Pre-Requisites and Required Resources:

Before diving into deploying a Kubernetes cluster on AWS EKS, ensure you have the following prerequisites and required resources:

Pre-Requisites:

An AWS account with the necessary permissions to create resources like EKS clusters, IAM roles, and networking components.
Basic knowledge of Kubernetes concepts such as Pods, Deployments, and Services.
Familiarity with AWS services like EC2, IAM, and VPC.

Required Resources:

Resource	Description
👉 AWS Account	Access to AWS services and resources.
👉 AWS CLI	Command-line interface for AWS operations.
👉 IAM Role	Role with necessary permissions for EKS.
👉 VPC	Virtual Private Cloud for networking.
👉 Subnets	Subnets for deploying EKS resources.
👉 Security Groups	Security configurations for EKS resources.
👉 EC2 Instances	Worker nodes for the EKS cluster.
👉 Kubernetes Configuration (kubectl)	Command-line tool for Kubernetes.
👉 Container Registry	Repository for storing Docker images.
👉 SSH Key Pair	Secure key pair for EC2 instance access.
👉 Route 53 (Optional)	DNS service for domain name resolution.
👉 CloudWatch (Optional)	Monitoring and logging for EKS resources.

Ensure you have access to these resources before proceeding with the deployment process.

Importance:

Deploying Kubernetes on AWS EKS is crucial for modern cloud-native application development and deployment. Here's why it matters:

Scalability: EKS offers seamless scalability, allowing your applications to grow with your business needs without worrying about infrastructure constraints.
High Availability: With EKS, you benefit from AWS's high availability infrastructure, ensuring your applications are always accessible to users.
Managed Service: EKS is a fully managed service, reducing the operational overhead of managing Kubernetes clusters, allowing you to focus on building and deploying applications.
Integration with AWS Services: EKS integrates seamlessly with other AWS services, enabling you to leverage services like AWS Fargate, Amazon RDS, and Amazon S3 for building robust and scalable applications.
Industry Standard: Kubernetes has become the industry standard for container orchestration, ensuring compatibility and interoperability with other cloud providers and tools.
Cost-Efficiency: By leveraging AWS's pay-as-you-go pricing model, you can optimize costs and only pay for the resources you consume, making EKS a cost-effective solution for running containerized workloads.

Benefits:

Benefit	Description
👉 Simplified Operations	EKS automates cluster management tasks, reducing the operational overhead of managing Kubernetes.
👉 Elastic Scalability	Scale your applications effortlessly by adding or removing worker nodes based on demand.
👉 High Availability	Benefit from AWS's robust infrastructure to ensure high availability and reliability of your applications.
👉 Seamless Integration	Integrate with other AWS services like IAM, VPC, and CloudWatch for enhanced functionality and monitoring.
👉 Security and Compliance	Leverage AWS's security features and compliance certifications to ensure the security of your applications and data.
👉 Cost Optimization	Optimize costs by only paying for the resources you use, with no upfront costs or long-term commitments.
👉 Rapid Deployment	Accelerate time-to-market by leveraging EKS's streamlined deployment process for containerized applications.
👉 Horizontal Autoscaling	Automatically scale your applications based on metrics like CPU and memory utilization.
👉 Self-Healing Infrastructure	EKS ensures the health and availability of your applications by automatically replacing unhealthy instances.
👉 Global Reach	Deploy your applications globally using AWS's global infrastructure, ensuring low latency and high performance.

Use Cases:

Use Case	Description
👉 Microservices Architecture	EKS is ideal for building and managing microservices-based applications, providing agility and scalability.
👉 Continuous Integration/Continuous Deployment (CI/CD)	Streamline your CI/CD pipelines by integrating with tools like Jenkins, GitLab, and AWS CodePipeline.
👉 Hybrid Cloud Deployments	EKS allows you to deploy applications seamlessly across on-premises and cloud environments, enabling hybrid cloud architectures.
👉 Machine Learning Workloads	Run machine learning workloads on EKS with services like Amazon SageMaker for scalable and cost-effective model training and inference.
👉 Web Applications	Deploy web applications on EKS to ensure high availability, scalability, and performance for your users.
👉 Dev/Test Environments	Provision ephemeral Kubernetes clusters for development and testing purposes, reducing infrastructure costs.
👉 IoT and Edge Computing	Use EKS to manage containerized workloads for IoT and edge computing scenarios, ensuring reliability and scalability.
👉 Big Data Analytics	Run big data analytics workloads on EKS with services like Amazon EMR and Amazon Redshift for scalable data processing.
👉 Gaming Applications	Deploy gaming applications on EKS for global reach and scalability, ensuring a seamless gaming experience for players.
👉 Content Management Systems	Manage content management systems (CMS) like WordPress and Drupal on EKS for improved scalability and performance.

Deploying Kubernetes on AWS EKS opens up a world of possibilities for building, deploying, and scaling modern applications. Whether you're building microservices, running machine learning workloads, or deploying web applications, EKS provides the scalability, reliability, and integration with AWS services you need to succeed.

Step-by-Step Guide:

Follow these steps to deploy a Kubernetes cluster on AWS EKS:

👉 Step 1: Set Up AWS CLI

Install and configure the AWS CLI on your local machine.
Use aws configure to set up your AWS credentials.

Pro-tip: Ensure your IAM user has the necessary permissions to create EKS clusters.

👉 Step 2: Create an IAM Role

Create an IAM role with permissions for EKS, EC2, and CloudFormation.
Attach policies like AmazonEKSClusterPolicy and AmazonEKSServicePolicy.

Pro-tip: Use the AWS Management Console to create the IAM role.

👉 Step 3: Set Up Networking

Create a VPC with public and private subnets.
Configure route tables, internet gateways, and NAT gateways.
Enable DNS resolution and DNS hostnames.

Pro-tip: Use the AWS VPC wizard for a quick setup.

👉 Step 4: Install and Configure kubectl

Install kubectl on your local machine.
Configure kubectl to communicate with your EKS cluster.

Pro-tip: Use the aws eks update-kubeconfig command to configure kubectl.

👉 Step 5: Create the EKS Cluster

Use the AWS Management Console or AWS CLI to create the EKS cluster.
Specify the IAM role, VPC, subnets, and cluster name.

Pro-tip: Review the cluster configuration before creation.

👉 Step 6: Deploy Worker Nodes

Create a CloudFormation stack to deploy worker nodes.
Use the AWS CloudFormation template provided by AWS.

Pro-tip: Adjust the instance type and desired capacity according to your requirements.

👉 Step 7: Verify Cluster Setup

Use kubectl get nodes to verify that worker nodes are connected to the cluster.
Ensure that all nodes are in the Ready state.

Pro-tip: Monitor cluster events using kubectl get events.

👉 Step 8: Configure Cluster Autoscaler

Install and configure the Kubernetes Cluster Autoscaler.
Define autoscaling policies based on CPU and memory utilization.

Pro-tip: Use horizontal pod autoscaling to scale application pods.

👉 Step 9: Set Up Logging and Monitoring

Configure CloudWatch Container Insights for logging and monitoring.
Create CloudWatch Alarms to alert on cluster and node health.

Pro-tip: Integrate with AWS X-Ray for distributed tracing.

👉 Step 10: Implement Security Best Practices

Enable encryption at rest and in transit for EKS resources.
Implement network policies to control traffic flow between pods.

Pro-tip: Use AWS Security Hub to centrally manage security compliance.

👉 Step 11: Deploy Applications

Use Kubernetes manifests or Helm charts to deploy applications.
Monitor application performance and resource utilization.

Pro-tip: Leverage AWS App Mesh for service mesh capabilities.

👉 Step 12: Implement CI/CD Pipelines

Integrate EKS with CI/CD tools like AWS CodePipeline or Jenkins.
Automate application deployments and updates.

Pro-tip: Use GitOps practices for declarative infrastructure management.

👉 Step 13: Backup and Disaster Recovery

Implement backup and disaster recovery strategies for EKS clusters.
Use tools like Velero for cluster backup and restore.

Pro-tip: Test your disaster recovery plan regularly.

👉 Step 14: Optimize Cost and Resources

Right-size EC2 instances and worker nodes based on workload requirements.
Use AWS Cost Explorer to analyze and optimize costs.

Pro-tip: Leverage spot instances for cost-effective compute capacity.

👉 Step 15: Stay Updated

Keep EKS and Kubernetes versions up to date.
Monitor AWS announcements and best practices for new features and updates.

Pro-tip: Subscribe to AWS newsletters and forums for the latest updates and tips.

Follow these steps carefully to deploy and manage a Kubernetes cluster on AWS EKS efficiently. Each step is crucial for ensuring the reliability, scalability, and security of your containerized workloads.

Step-by-Step Setup Template:

Here's a template for the step-by-step setup process:

Step	Task	Action
👉 Step 1	Set Up AWS CLI	Install AWS CLI on your local machine.
		Configure AWS CLI with your AWS credentials.
👉 Step 2	Create an IAM Role	Create an IAM role with permissions for EKS, EC2, and CloudFormation.
		Attach policies like AmazonEKSClusterPolicy and AmazonEKSServicePolicy.
👉 Step 3	Set Up Networking	Create a VPC with public and private subnets.
		Configure route tables, internet gateways, and NAT gateways.
		Enable DNS resolution and DNS hostnames.
👉 Step 4	Install and Configure kubectl	Install kubectl on your local machine.
		Configure kubectl to communicate with your EKS cluster.
👉 Step 5	Create the EKS Cluster	Use the AWS Management Console or AWS CLI to create the EKS cluster.
		Specify the IAM role, VPC, subnets, and cluster name.
👉 Step 6	Deploy Worker Nodes	Create a CloudFormation stack to deploy worker nodes.
		Use the AWS CloudFormation template provided by AWS.
👉 Step 7	Verify Cluster Setup	Use kubectl get nodes to verify worker nodes are connected.
		Ensure all nodes are in the Ready state.
👉 Step 8	Configure Cluster Autoscaler	Install and configure Kubernetes Cluster Autoscaler.
		Define autoscaling policies based on CPU and memory utilization.
👉 Step 9	Set Up Logging and Monitoring	Configure CloudWatch Container Insights for logging and monitoring.
		Create CloudWatch Alarms to alert on cluster and node health.
👉 Step 10	Implement Security Best Practices	Enable encryption at rest and in transit for EKS resources.
		Implement network policies to control traffic flow between pods.
👉 Step 11	Deploy Applications	Use Kubernetes manifests or Helm charts to deploy applications.
		Monitor application performance and resource utilization.
👉 Step 12	Implement CI/CD Pipelines	Integrate EKS with CI/CD tools like AWS CodePipeline or Jenkins.
		Automate application deployments and updates.
👉 Step 13	Backup and Disaster Recovery	Implement backup and disaster recovery strategies for EKS clusters.
		Use tools like Velero for cluster backup and restore.
👉 Step 14	Optimize Cost and Resources	Right-size EC2 instances and worker nodes based on workload requirements.
		Use AWS Cost Explorer to analyze and optimize costs.
👉 Step 15	Stay Updated	Keep EKS and Kubernetes versions up to date.
		Monitor AWS announcements and best practices for new features and updates.

Follow this template for a structured and organized approach to setting up your Kubernetes cluster on AWS EKS. Each task is essential for ensuring the successful deployment and management of your containerized workloads.

Pro-Tips and Advanced Optimization Strategies:

Enhance your Kubernetes deployment on AWS EKS with these pro-tips and advanced optimization strategies:

Pro-Tip	Description
👉 Use Managed Node Groups	Utilize EKS managed node groups to automatically provision and manage EC2 instances for your cluster. This simplifies node management and scaling.
👉 Implement Horizontal Pod Autoscaling	Configure Horizontal Pod Autoscaling to automatically adjust the number of pod replicas based on CPU or memory utilization, ensuring optimal resource usage.
👉 Enable Cluster Logging	Enable cluster-level logging with Amazon CloudWatch Container Insights to gain insights into application and system logs for troubleshooting and monitoring.
👉 Implement Service Mesh	Implement a service mesh like AWS App Mesh or Istio to manage and monitor communications between services, improving reliability and observability.
👉 Utilize Spot Instances	Leverage EC2 spot instances for cost-effective compute capacity, especially for non-production workloads or batch processing tasks with flexible resource requirements.
👉 Implement Node Termination Handler	Implement a node termination handler to gracefully handle EC2 instance terminations, ensuring that Kubernetes pods are gracefully evacuated before node termination.
👉 Optimize Networking	Optimize networking performance by configuring AWS VPC CNI (Container Network Interface) for improved throughput and reduced latency between pods.
👉 Implement Pod Disruption Budgets	Define Pod Disruption Budgets (PDBs) to limit the number of pods that can be simultaneously disrupted during maintenance or node failures, ensuring application availability.
👉 Utilize AWS Fargate	Consider using AWS Fargate for serverless container management, eliminating the need to manage underlying EC2 instances and scaling based on application demand.
👉 Implement Cluster Autoscaler	Configure the Kubernetes Cluster Autoscaler to automatically adjust the size of your EKS cluster based on resource utilization, optimizing costs and performance.
👉 Secure Container Images	Secure container images by scanning for vulnerabilities and implementing image signing and verification processes to prevent security threats in production environments.
👉 Implement Canary Deployments	Implement Canary deployments with tools like AWS CodeDeploy or Flagger to gradually roll out new application versions and validate changes before full deployment.
👉 Monitor Resource Utilization	Monitor resource utilization metrics such as CPU, memory, and network usage using CloudWatch metrics and alarms to proactively identify and address performance issues.
👉 Implement Multi-AZ Deployment	Deploy EKS clusters across multiple Availability Zones (AZs) for high availability and fault tolerance, ensuring that your applications remain resilient to AZ failures.
👉 Use Managed Services	Leverage managed services like Amazon RDS, Amazon ElastiCache, and Amazon S3 for databases, caching, and storage needs to offload operational overhead and ensure scalability.

Implementing these pro-tips and advanced optimization strategies will help you maximize the performance, reliability, and cost-efficiency of your Kubernetes deployment on AWS EKS. Continuously evaluate and refine your deployment practices to stay ahead of evolving requirements and industry best practices.

Common Mistakes to Avoid:

Avoid these common mistakes to ensure a successful deployment of Kubernetes on AWS EKS:

Mistake	Description
👉 Neglecting IAM Role Permissions	Failing to assign the correct IAM role permissions can lead to authentication and authorization errors during cluster creation and operation.
👉 Ignoring Networking Configuration	Improperly configuring VPC, subnets, and security groups can result in communication issues between cluster components and external services.
👉 Oversizing or Undersizing Nodes	Incorrectly sizing EC2 instances for worker nodes can result in wasted resources (oversizing) or insufficient capacity (undersizing) for your workload.
👉 Skipping Cluster Logging	Neglecting to enable cluster-level logging can hinder troubleshooting efforts and monitoring capabilities, making it challenging to identify issues.
👉 Lack of Disaster Recovery Plan	Not having a robust disaster recovery plan in place can leave your cluster vulnerable to data loss and downtime in the event of failures or disasters.
👉 Poor Security Practices	Ignoring security best practices such as encrypting data at rest and implementing network policies can expose your cluster to potential security threats.
👉 Manual Scaling and Management	Manually scaling and managing cluster resources without leveraging automation tools can lead to inefficiencies and increased operational overhead.
👉 Overlooking Monitoring and Alerts	Failing to set up proper monitoring and alerting mechanisms can result in missed performance issues or outages, impacting application availability.
👉 Not Implementing CI/CD Pipelines	Neglecting to implement CI/CD pipelines for automated application deployment and updates can lead to manual errors and slower release cycles.
👉 Lack of Regular Updates	Delaying updates and patches for Kubernetes and AWS services can expose your cluster to vulnerabilities and compatibility issues over time.

Best Practices for Best Results:

Follow these best practices to achieve optimal results with your Kubernetes deployment on AWS EKS:

Best Practice	Description
👉 Infrastructure as Code (IaC)	Use Infrastructure as Code (IaC) tools like AWS CloudFormation or Terraform to automate cluster provisioning and configuration.
👉 Tagging Resources	Tag AWS resources with appropriate metadata to organize and track resources, simplify management, and enable cost allocation.
👉 Implement Backup and Restore	Implement automated backup and restore procedures for EKS clusters and application data to ensure data integrity and availability.
👉 Regular Security Audits	Conduct regular security audits and vulnerability scans to identify and address security risks in your EKS environment proactively.
👉 Continuous Learning and Training	Invest in ongoing training and skill development for your team to stay updated on the latest Kubernetes and AWS best practices.
👉 Performance Optimization	Continuously monitor and optimize cluster performance by analyzing resource utilization metrics and adjusting configurations as needed.
👉 Documentation and Runbooks	Maintain detailed documentation and runbooks for cluster setup, configuration, and operational procedures to ensure consistency and reliability.
👉 Peer Reviews and Code Reviews	Conduct peer reviews and code reviews for infrastructure changes and application deployments to catch errors and ensure quality.
👉 Regular Testing and Validation	Perform regular testing and validation of cluster configurations, application deployments, and disaster recovery procedures to mitigate risks.
👉 Transparent Communication	Foster transparent communication and collaboration among team members to share knowledge, address issues, and drive continuous improvement.
👉 Cloud Cost Optimization	Continuously monitor and optimize cloud costs by rightsizing resources, leveraging reserved instances, and adopting cost-saving strategies.

By following these best practices and avoiding common mistakes, you can achieve a secure, reliable, and efficient Kubernetes deployment on AWS EKS, empowering your organization to innovate and deliver value to your customers seamlessly.

Most Popular Tools:

Explore these popular tools that complement Kubernetes deployment on AWS EKS:

Tool	Pros	Cons	Best For
👉 Terraform	- Infrastructure as Code (IaC) tool for automating provisioning and management of AWS resources.	- Learning curve for beginners.	Automation and Infrastructure Management
👉 Helm	- Package manager for Kubernetes that simplifies deployment and management of applications.	- Limited support for versioning and dependency management.	Application Deployment and Management
👉 Prometheus	- Open-source monitoring and alerting toolkit for Kubernetes, providing rich metrics and visualization.	- Requires additional setup and configuration for production-grade monitoring.	Monitoring and Alerting
👉 Grafana	- Data visualization tool that integrates with Prometheus to create customizable dashboards and charts.	- Steeper learning curve for complex dashboard configurations.	Metrics Visualization and Dashboarding
👉 AWS CloudFormation	- AWS-native IaC service for provisioning and managing AWS resources using declarative templates.	- Limited support for non-AWS resources and integrations.	AWS Resource Management and Provisioning
👉 AWS CodePipeline	- Fully managed CI/CD service for building, testing, and deploying applications on AWS.	- Limited support for non-AWS tools and environments.	Continuous Integration and Continuous Delivery
👉 Fluentd	- Open-source data collector for logging and data processing, compatible with various log management systems.	- Requires additional configuration for log aggregation and routing.	Log Collection and Centralized Logging
👉 AWS CloudWatch	- Monitoring and observability service for AWS resources, providing metrics, logs, and alarms.	- Limited support for custom metrics and advanced analytics.	AWS Resource Monitoring and Alerting
👉 AWS Fargate	- Serverless compute engine for running containers without managing underlying EC2 instances.	- Limited control over underlying infrastructure and networking.	Serverless Container Management
👉 KubeDB	- Kubernetes operator for managing production-grade databases on Kubernetes, supporting various database engines.	- Requires additional setup and configuration for database deployment and management.	Database Management on Kubernetes
👉 Prometheus Operator	- Kubernetes operator for managing Prometheus instances and resources on Kubernetes clusters.	- Requires familiarity with Kubernetes custom resources and operators.	Monitoring and Alerting Automation

These tools offer various capabilities for managing, monitoring, and deploying applications on Kubernetes clusters running on AWS EKS. Choose the ones that best fit your requirements and workflow preferences to enhance your Kubernetes experience on AWS.

Conclusion:

Deploying a Kubernetes cluster on AWS EKS is a crucial step for organizations looking to leverage the power of containerized applications in the cloud. Throughout this guide, we've explored the step-by-step process, benefits, use cases, best practices, and popular tools for achieving success with Kubernetes on AWS EKS.

By following the comprehensive guide provided here, you can deploy, manage, and optimize Kubernetes clusters on AWS EKS with confidence. Whether you're a beginner exploring container orchestration or an experienced DevOps engineer seeking to enhance your cloud-native infrastructure, this guide has something for everyone.

Frequently Asked Questions (FAQs):

👉 Q1: What is the difference between AWS ECS and AWS EKS?

A: AWS ECS (Elastic Container Service) is a fully managed container orchestration service provided by AWS, while AWS EKS (Elastic Kubernetes Service) is a managed Kubernetes service. ECS uses its own orchestration engine, whereas EKS is compatible with the Kubernetes ecosystem.

👉 Q2: How does AWS EKS pricing work?

A: AWS EKS pricing is based on the resources consumed by the EKS cluster, including EC2 instances, EBS volumes, and network data transfer. There are no upfront costs for using EKS, and you only pay for the resources you use.

👉 Q3: Can I use AWS EKS for production workloads?

A: Yes, AWS EKS is suitable for production workloads and is used by organizations of all sizes for running mission-critical applications. EKS offers high availability, scalability, and security features necessary for production environments.

👉 Q4: How do I scale my Kubernetes cluster on AWS EKS?

A: You can scale your Kubernetes cluster on AWS EKS manually by adjusting the number of worker nodes or automatically by configuring horizontal pod autoscaling and cluster autoscaling based on resource utilization metrics.

👉 Q5: What are some best practices for securing Kubernetes on AWS EKS?

A: Some best practices for securing Kubernetes on AWS EKS include enabling encryption at rest and in transit, implementing network policies, regularly updating Kubernetes and AWS services, and conducting security audits and vulnerability scans.

👉 Q6: Can I use AWS Fargate with AWS EKS?

A: Yes, you can use AWS Fargate with AWS EKS to run Kubernetes pods without managing underlying EC2 instances. Fargate allows you to focus on deploying and managing your applications without worrying about server infrastructure.

👉 Q7: How do I troubleshoot issues with my Kubernetes cluster on AWS EKS?

A: You can troubleshoot issues with your Kubernetes cluster on AWS EKS by examining logs, metrics, and events using tools like CloudWatch, Prometheus, and kubectl. Additionally, you can seek support from AWS support forums and documentation.

👉 How to deploy a Kubernetes cluster on AWS EKS: Ultimate Guide