Production-Grade Kubernetes on AWS: Deploying EKS with Terraform
Running Kubernetes in production requires solid infrastructure that won’t break under pressure. This comprehensive guide shows DevOps engineers, cloud architects, and platform teams how to build bulletproof EKS clusters using Terraform infrastructure as code.
You’ll learn how to set up AWS EKS deployment that actually works in the real world – not just demo environments. We’ll walk through designing your Terraform EKS configuration from scratch, making sure your Kubernetes cluster management AWS setup can handle production traffic without missing a beat.
The guide covers three critical areas: building your EKS infrastructure as code with proper networking and IAM roles, implementing EKS security configuration that protects your workloads without slowing down your team, and optimizing performance while keeping costs under control. Each section includes working code examples and troubleshooting tips based on real production deployments.
By the end, you’ll have a production Kubernetes AWS environment that scales reliably and stays secure – plus the Terraform skills to maintain and improve it over time.
Setting Up Your AWS Environment for EKS Success
Configure AWS CLI with proper credentials and permissions
Start by installing the AWS CLI and configuring it with your access keys using aws configure. Create an IAM user with programmatic access and attach the necessary EKS policies including AmazonEKSClusterPolicy and AmazonEKSWorkerNodePolicy. Your credentials should have permissions to create VPCs, security groups, and manage EC2 instances for successful EKS Terraform deployment.
Create dedicated VPC with public and private subnets
Design a robust VPC architecture with both public and private subnets across multiple availability zones. Public subnets host load balancers and NAT gateways, while private subnets contain your EKS worker nodes for enhanced security. This network configuration ensures proper traffic routing and enables seamless communication between your Kubernetes cluster components and external services.
Set up IAM roles for EKS cluster and worker nodes
Create two essential IAM roles for your AWS EKS deployment: the EKS cluster service role and the worker node instance profile. The cluster role needs AmazonEKSClusterPolicy attached, while worker nodes require AmazonEKSWorkerNodePolicy, AmazonEKS_CNI_Policy, and AmazonEC2ContainerRegistryReadOnly policies. These roles enable proper authentication and authorization between AWS services and your Kubernetes infrastructure.
Install required tools: kubectl, terraform, and aws-iam-authenticator
Download and install kubectl for Kubernetes cluster management, Terraform for infrastructure as code provisioning, and aws-iam-authenticator for secure cluster authentication. Verify installations by running version commands for each tool. These components work together to enable seamless EKS cluster Terraform configuration and ongoing Kubernetes cluster management AWS operations throughout your production deployment lifecycle.
Designing Your Terraform Infrastructure Configuration
Structure your Terraform project with modules and environments
Building a robust EKS Terraform configuration starts with proper project organization. Create separate modules for core components like VPC, security groups, and the EKS cluster itself. This modular approach enables code reuse across environments and simplifies maintenance. Structure your directories with dedicated folders for modules, environments (dev/staging/prod), and shared variables. Each module should focus on a single responsibility – your VPC module handles networking, while your EKS module manages cluster resources. Use remote state management with S3 backends to enable team collaboration and maintain state consistency across deployments.
Define VPC networking components for optimal EKS performance
Your EKS infrastructure as code requires careful VPC design to support production workloads. Create public and private subnets across multiple availability zones for high availability and fault tolerance. Public subnets host load balancers and NAT gateways, while private subnets contain your worker nodes for enhanced security. Configure route tables to direct traffic appropriately – private subnet routes go through NAT gateways for outbound internet access. Enable VPC Flow Logs for network monitoring and set up VPC endpoints for AWS services to reduce data transfer costs and improve performance. Size your subnets appropriately to accommodate cluster scaling requirements.
Configure security groups with least privilege access principles
Security group configuration forms the foundation of your EKS security posture. Create dedicated security groups for different components – one for the EKS control plane, another for worker nodes, and separate groups for application load balancers. Follow least privilege principles by opening only necessary ports and restricting source IP ranges. Allow communication between control plane and worker nodes on required ports (443, 10250). Configure ingress rules carefully – worker nodes need access to container registries and AWS services, while the control plane requires specific API server access. Document security group rules clearly and regularly audit them to prevent security drift in your production Kubernetes AWS environment.
Creating Production-Ready EKS Cluster with Terraform
Deploy EKS control plane with proper version and configuration
Setting up your EKS control plane starts with choosing the right Kubernetes version for your production workload. Configure your Terraform EKS module with version 1.28 or newer to access the latest security patches and features. Enable private API server endpoint access while maintaining public access for initial setup, then gradually transition to private-only access for enhanced security. Configure your subnet placement carefully, ensuring control plane components are distributed across multiple availability zones for high availability. Set up proper VPC CNI configuration and enable envelope encryption for etcd data at rest using AWS KMS keys.
Configure managed node groups with auto-scaling capabilities
Managed node groups provide the backbone of your EKS cluster Terraform configuration, offering automated patching and scaling capabilities. Create multiple node groups with different instance types to handle diverse workload requirements – use compute-optimized instances for CPU-intensive tasks and memory-optimized for data processing workloads. Configure cluster autoscaler with proper scaling policies, setting minimum nodes to 2 and maximum based on your capacity planning. Enable spot instances for development environments and mix spot with on-demand instances for production to optimize costs while maintaining reliability. Implement node group versioning strategy to enable rolling updates without service disruption.
Set up OIDC identity provider for service account integration
OIDC integration enables secure service-to-service communication within your production Kubernetes AWS environment. Configure the OIDC identity provider through Terraform to establish trust relationships between AWS IAM and Kubernetes service accounts. Create IAM roles with specific permissions for each service, following the principle of least privilege. Map these roles to Kubernetes service accounts using annotations, eliminating the need for long-lived AWS credentials in your pods. This setup enables seamless integration with AWS services like S3, RDS, and Parameter Store while maintaining security best practices.
Implement cluster logging and monitoring from day one
Production EKS clusters require comprehensive observability from deployment. Enable CloudWatch Container Insights through your EKS infrastructure as code to capture cluster-level metrics and performance data. Configure EKS control plane logging for all log types including API server, audit, authenticator, controller manager, and scheduler logs. Set up log retention policies to manage costs while maintaining compliance requirements. Deploy Prometheus and Grafana for application-level monitoring, or integrate with AWS Managed Prometheus for a fully managed solution. Create custom dashboards and alerts for key performance indicators like node utilization, pod restart rates, and API server response times.
Securing Your EKS Cluster for Production Workloads
Enable network policies for pod-to-pod communication control
Network policies act as your EKS cluster’s internal firewall, controlling which pods can communicate with each other. By default, all pods can talk to any other pod, creating potential security gaps. Installing a Container Network Interface (CNI) like Calico or Cilium gives you granular control over pod-to-pod traffic. You can create policies that block communication between different namespaces, restrict database access to specific application tiers, or isolate sensitive workloads. This micro-segmentation approach significantly reduces your attack surface and prevents lateral movement if one pod gets compromised.
Configure RBAC permissions for users and service accounts
Role-Based Access Control (RBAC) determines who can do what in your EKS cluster. Start by creating specific roles for different user groups – developers might need read access to certain namespaces while operations teams need broader cluster management permissions. Service accounts need equally careful attention since they handle automated processes. Create dedicated service accounts for each application with minimal required permissions. Avoid using the default service account, which often has excessive privileges. Link these service accounts to IAM roles using IRSA (IAM Roles for Service Accounts) to inherit AWS permissions securely.
Implement secrets management with AWS Secrets Manager
Hardcoded secrets in container images or environment variables create massive security risks. AWS Secrets Manager integration with EKS lets you store sensitive data like database passwords, API keys, and certificates securely. The AWS Load Balancer Controller and CSI driver can automatically mount secrets as files or environment variables into your pods. Set up automatic rotation for database credentials and API keys to minimize exposure from compromised secrets. This approach also helps with compliance requirements since you get detailed audit logs of secret access patterns.
Set up Pod Security Standards for workload protection
Pod Security Standards replace the deprecated Pod Security Policies with a more straightforward approach to securing pod specifications. The three standard levels – Privileged, Baseline, and Restricted – give you flexibility in balancing security and functionality. Most production workloads should run under the Restricted standard, which blocks privileged containers, requires non-root users, and prevents dangerous capabilities. You can enforce these standards at the namespace level using labels, making it easy to apply different security policies to development and production environments.
Enable audit logging for compliance requirements
EKS audit logging captures detailed records of all API server activity, including who made requests, what resources were accessed, and when changes occurred. Enable audit logging through your Terraform EKS configuration and send logs to CloudWatch for analysis. This creates an immutable record of cluster activity that’s essential for compliance frameworks like SOC 2 or PCI DSS. Set up CloudWatch alerts for suspicious activities like failed authentication attempts, privilege escalation attempts, or unusual resource access patterns to catch potential security incidents early.
Optimizing EKS Performance and Cost Management
Configure Cluster Autoscaler for Dynamic Node Scaling
The cluster autoscaler automatically adjusts your EKS node groups based on pod resource demands, preventing over-provisioning while ensuring workloads have sufficient capacity. Deploy the autoscaler using Terraform by creating a service account with IAM roles for service accounts (IRSA), then install the autoscaler via Helm or kubectl. Configure node group tags like k8s.io/cluster-autoscaler/enabled and k8s.io/cluster-autoscaler/your-cluster-name to enable discovery. Set minimum and maximum node counts in your Terraform EKS configuration to control scaling boundaries. The autoscaler monitors pending pods and scales up nodes when resources are insufficient, while scaling down occurs when nodes remain underutilized for extended periods.
Implement Resource Quotas and Limits for Namespace Isolation
Resource quotas and limits prevent individual namespaces from consuming excessive cluster resources, ensuring fair allocation across teams and applications. Create Terraform resources to define namespace-level quotas for CPU, memory, persistent volume claims, and object counts. Implement LimitRanges to enforce default and maximum resource requests per container, preventing resource starvation scenarios. Use Terraform’s Kubernetes provider to deploy these policies as code, maintaining consistency across environments. Configure requests and limits in your deployment manifests to work effectively with the quota system. This approach enables multi-tenant EKS clusters while maintaining performance isolation and cost predictability for different workloads and development teams.
Set Up Monitoring with CloudWatch Container Insights
CloudWatch Container Insights provides comprehensive monitoring for your EKS infrastructure as code deployment, offering cluster-level and pod-level metrics without manual configuration. Enable Container Insights through Terraform by deploying the CloudWatch agent as a DaemonSet with proper IAM permissions. The integration automatically collects CPU, memory, network, and disk metrics from your Kubernetes cluster management AWS setup. Create custom dashboards to visualize node utilization, pod performance, and namespace resource consumption. Set up CloudWatch alarms for critical thresholds like node CPU usage, memory pressure, and failed pod deployments. This monitoring foundation supports your production Kubernetes AWS environment by providing actionable insights for capacity planning and troubleshooting performance issues.
Deploying and Managing Applications on Your EKS Cluster
Configure ingress controllers for external traffic management
Setting up ingress controllers is crucial for managing external traffic to your EKS applications. The AWS Load Balancer Controller integrates seamlessly with your EKS Terraform configuration, automatically provisioning Application Load Balancers (ALBs) and Network Load Balancers (NLBs) based on Kubernetes ingress resources. Install the controller using Helm charts and configure it with proper IAM service accounts through IRSA (IAM Roles for Service Accounts). This setup enables automatic SSL termination, path-based routing, and integration with AWS Certificate Manager for production-grade HTTPS traffic management across your Kubernetes cluster management AWS infrastructure.
Set up persistent storage with EBS CSI driver
The Amazon EBS CSI driver provides reliable persistent storage for stateful applications running on your EKS infrastructure as code setup. Deploy the CSI driver through Terraform by creating the necessary IAM roles and installing the driver via Helm. Configure storage classes for different performance requirements like gp3 for general purpose or io2 for high IOPS workloads. The CSI driver enables dynamic volume provisioning, snapshotting, and volume expansion capabilities. Properly configured persistent volumes ensure your databases and stateful applications maintain data persistence across pod restarts and node replacements in your production Kubernetes AWS environment.
Implement CI/CD pipelines for automated deployments
Building robust CI/CD pipelines streamlines application deployments to your EKS cluster Terraform configuration. Use AWS CodePipeline with CodeBuild to create automated workflows that build container images, push them to Amazon ECR, and deploy to EKS using kubectl or Helm. Integrate GitOps tools like ArgoCD or Flux for declarative deployments that sync your Git repositories with cluster state. Implement blue-green or canary deployment strategies using tools like Flagger or native Kubernetes deployment strategies. Configure proper RBAC permissions and use service accounts with minimal required permissions for secure automated deployments across your AWS EKS deployment pipeline.
Configure service mesh for advanced traffic management
Service mesh architecture provides sophisticated traffic management, security, and observability for microservices running on your EKS setup. AWS App Mesh integrates natively with EKS, offering traffic routing, load balancing, and circuit breaking capabilities. Alternatively, deploy Istio for more advanced features like mutual TLS, sophisticated routing rules, and comprehensive telemetry collection. Configure service mesh through Terraform by defining virtual services, destination rules, and traffic policies. The mesh enables canary deployments, A/B testing, and fault injection for resilient application architecture. Implement distributed tracing and metrics collection to monitor service-to-service communication across your production Kubernetes AWS infrastructure.
Setting up a production-grade EKS cluster on AWS using Terraform gives you the foundation for scalable, secure container orchestration. From configuring your AWS environment to designing robust infrastructure code, each step builds toward a cluster that can handle real-world workloads. The security configurations, performance optimizations, and cost management strategies we covered help ensure your cluster runs efficiently while staying within budget.
Ready to take your Kubernetes deployment to the next level? Start by implementing these Terraform configurations in a development environment first, then gradually move to production with proper testing and monitoring in place. Your containerized applications will thank you for the solid infrastructure foundation, and your team will appreciate the consistent, repeatable deployment process that Terraform brings to the table.