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EKS Best Practices for Production Workloads

📅 2025-11-06T23:51:50.586Z⏱️ 5 min read✍️ Robson Alves
#aws#devops#cloud
EKS Best Practices for Production Workloads

EKS Best Practices for Production Workloads

Running production workloads on Amazon Elastic Kubernetes Service (EKS) can be challenging but immensely rewarding. Imagine a scenario where your application experiences downtime due to improper scaling strategies, or costs spiral out of control because of inefficient resource management. These issues can undermine trust and profitability.

In 2025, as businesses increasingly rely on cloud-native solutions, EKS will play a crucial role in deploying scalable, secure, and cost-effective applications. By adopting best practices, you can ensure your workloads perform optimally while staying within budget.

What you'll learn in this post includes:

  • Setting up EKS with high availability
  • Implementing efficient scaling strategies
  • Securing your cluster
  • Optimizing costs
  • Monitoring and logging for production readiness

Understanding the Basics

EKS is a managed Kubernetes service that makes it easy to run Kubernetes in AWS without needing to stand up or maintain control plane infrastructure.

To get started, you need an AWS account and some basic knowledge of Kubernetes concepts.

Setting Up High Availability Clusters

Step 1: Create EKS Cluster with Multiple AZs

Creating a cluster across multiple availability zones (AZs) ensures high availability and fault tolerance.

# Create an EKS cluster in multiple AZs using eksctl
eksctl create cluster \
--name my-prod-cluster \
--region us-west-2 \
--zones us-west-2a,us-west-2b,us-west-2c \
--nodegroup-name my-node-group \
--node-type t3.medium \
--nodes 3 \
--nodes-min 1 \
--nodes-max 5

This command sets up a cluster named my-prod-cluster with node groups across three AZs in the us-west-2 region.

Step 2: Configure Networking

Proper networking setup is critical for performance and security. Use AWS-managed network policies to control traffic between pods.

# Example of an AWS CNI configuration
apiVersion: v1
kind: ConfigMap
metadata:
  name: aws-node
  namespace: kube-system
data:
  AWS_VPC_K8S_CNI_CUSTOM_NETWORK_CFG: "true"

This configuration enables a custom network setup for your EKS nodes.

Implementing Efficient Scaling Strategies

Step 1: Use Auto-Scaling Groups (ASGs)

EKS integrates well with ASGs to automatically adjust the number of worker nodes based on demand.

# Enable auto-scaling for an EKS node group
eksctl utils update-cluster-logging --enable-types all --name my-prod-cluster

# Update nodegroup to include auto-scaling
eksctl scale nodegroup \
--cluster my-prod-cluster \
--nodes-min 1 \
--nodes-max 10 \
--nodegroup my-node-group

This setup ensures your cluster can handle varying loads efficiently.

Step 2: Leverage Kubernetes Horizontal Pod Autoscaler (HPA)

HPA automatically adjusts the number of pod replicas in a deployment based on observed CPU utilization or other select metrics.

# Example HPA configuration
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: my-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: my-deployment
  minReplicas: 2
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 50

This HPA configuration keeps CPU usage around 50% by scaling the deployment named my-deployment.

Securing Your Cluster

Step 1: Enable RBAC and IAM Roles for Service Accounts

Using Role-Based Access Control (RBAC) with AWS Identity and Access Management (IAM) roles for service accounts enhances security.

# Create an OIDC provider for your EKS cluster
eksctl utils associate-iam-oidc-provider \
--cluster my-prod-cluster \
--approve

This command associates an IAM OIDC provider, enabling secure role mappings.

Step 2: Use Network Policies

Network policies define how pods communicate with each other and external systems.

# Example network policy
apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: allow-internal-access
spec:
  podSelector: {}
  policyTypes:
  - Ingress
  ingress:
  - from:
    - ipBlock:
        cidr: 192.168.0.0/16

This network policy allows internal traffic from the 192.168.0.0/16 range.

Optimizing Costs

Step 1: Use Spot Instances

Spot instances can significantly reduce costs for non-critical workloads.

# Create a node group with spot instances
eksctl create nodegroup \
--cluster my-prod-cluster \
--name spot-node-group \
--node-type t3.large \
--nodes 2 \
--nodes-min 1 \
--nodes-max 5 \
--spot

Using --spot flag in the above command creates a node group with spot instances.

Step 2: Right-Sizing Instances

Choosing the right instance type can optimize costs without compromising performance.

# List available EC2 instance types and their pricing
aws ec2 describe-instance-types --query 'InstanceTypes[*].{Type: InstanceType, Price: PlacementGroupSupported}'

This command lists available EC2 instance types along with placement group support information.

Monitoring and Logging for Production Readiness

Step 1: Set Up CloudWatch Metrics and Logs

CloudWatch provides monitoring and logging capabilities for EKS clusters.

# Enable all logs for the cluster
eksctl utils update-cluster-logging --enable-types all --name my-prod-cluster

This command enables all log types for my-prod-cluster.

Step 2: Integrate with External Tools

Consider integrating with external tools like Prometheus and Grafana for advanced monitoring.

# Example Prometheus configuration
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
  name: my-service-monitor
spec:
  selector:
    matchLabels:
      app: my-app
  endpoints:
  - port: web

This Prometheus configuration sets up a service monitor for an application labeled my-app.

Troubleshooting

Issue: Nodes Failing to Join Cluster

Check IAM roles and node group configurations.

# Verify node group status
eksctl get nodegroup --cluster my-prod-cluster

Ensure the node group has the correct IAM role attached.

Issue: Inadequate Resource Allocation

Scale up nodes or adjust resource requests/limits in your deployments.

# Example deployment with resource limits
apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-deployment
spec:
  replicas: 3
  selector:
    matchLabels:
      app: my-app
  template:
    metadata:
      labels:
        app: my-app
    spec:
      containers:
      - name: my-container
        image: nginx:latest
        resources:
          requests:
            memory: "64Mi"
            cpu: "250m"
          limits:
            memory: "128Mi"
            cpu: "500m"

Adjust requests and limits based on your application's needs.

Conclusion

By following these best practices, you can set up a robust EKS cluster that is secure, cost-effective, and scalable for production workloads.

Key Takeaways:

  1. Create clusters with multiple AZs for high availability.
  2. Use ASGs and HPA to manage scaling automatically.
  3. Implement RBAC and IAM roles for enhanced security.
  4. Leverage spot instances and right-sizing for cost optimization.
  5. Utilize CloudWatch and external tools for comprehensive monitoring.

Happy deploying!