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EKS Best Practices

Comprehensive guidance for designing, deploying, and operating Amazon EKS clusters. Consolidates guidance from the AWS EKS Best Practices Guide, AWS EKS HA/Resiliency Guide, and terraform-aws-modules/terraform-aws-eks examples.

When to Use This Skill

Activate this skill when:

• Designing a new EKS cluster architecture
• Choosing between EKS compute options (Fargate, MNG, Karpenter, Auto Mode)
• Configuring EKS networking (VPC CNI, ingress, service mesh)
• Implementing EKS security (IAM, pod security, secrets)
• Planning cluster upgrades or migrations
• Reviewing EKS architecture decisions
• Working with terraform-aws-modules/terraform-aws-eks examples
• Optimizing EKS cost or scaling to large clusters

Don't use this skill for:

• Generic Kubernetes concepts (Claude knows these)
• Provider-specific API reference (link to AWS docs)
• Non-EKS container orchestration (ECS, Lambda)
• Step-by-step EKS upgrade execution — this skill covers upgrade strategy and architectural decisions, not the per-version procedures themselves.

EKS Architecture Decision Framework

When to Use EKS

Requirement	EKS	ECS	Lambda
Kubernetes ecosystem	✅ Native K8s	❌ AWS-proprietary	❌
Portable across clouds	✅ Standard K8s API	❌ AWS-only	❌ AWS-only
Long-running services	✅	✅	⚠️ 15 min limit
Minimal ops overhead	Medium	Low	Lowest
GPU/ML workloads	✅ Best support	Limited	❌
Complex networking	✅ Full control	Medium	Limited
Team has K8s expertise	Required	Not required	Not required

EKS Deployment Models

Model	Description	Operational Overhead	Use When
EKS Standard	Full control over nodes, add-ons, networking	Medium-High	Need full customization
EKS Auto Mode	AWS manages nodes, add-ons, scaling	Low	Want minimal ops, standard workloads
EKS with Fargate	Serverless pods, per-pod billing	Low	Batch, low-density workloads
EKS on Outposts	Run EKS on-premises	High	Data residency, low-latency edge
EKS Anywhere	EKS on your own infrastructure	Highest	Air-gapped, custom hardware

Shared Responsibility

Component	AWS Manages	You Manage
Control plane	API server, etcd, HA, patching	RBAC, admission control, audit logging
Data plane (MNG)	AMI updates, node health	Instance type, scaling, pod scheduling
Data plane (Fargate)	Everything	Pod spec, resource requests
Data plane (Auto Mode)	Node lifecycle, OS patching	Workload definitions
Networking	ENI attachment, VPC CNI releases	Subnet design, IP planning, ingress
Security	Control plane auth	IAM, pod security, secrets, network policies

Compute Selection Matrix

Decision Table

Factor	Fargate	MNG	Karpenter	Auto Mode	Self-Managed
Best for	Batch, small scale	Stable, predictable	Dynamic, varied	Minimal ops	Custom AMI/kernel
Scaling	Per-pod	ASG-based	Fast, flexible	AWS-managed	Manual ASG
Spot support	❌	✅	✅ Native	✅	✅
GPU support	❌	✅	✅	✅	✅
DaemonSets	❌	✅	✅	✅	✅
Cost model	Per vCPU/GB/hr	Per EC2 instance	Per EC2 instance	Per EC2 instance	Per EC2 instance
Max pods/node	1	ENI-based	ENI-based	AWS-managed	ENI-based
Node SSH	❌	✅	✅	❌	✅
Operational	Lowest	Low	Low	Lowest	Highest

Quick Decision Guide

• Default choice: Karpenter — best balance of flexibility, cost, and automation
• Zero ops priority: EKS Auto Mode — AWS manages nodes, add-ons, and scaling via managed Karpenter. Best for teams that want Kubernetes benefits without operational overhead around upgrades, autoscaling, load balancing, and storage
• Serverless/batch: Fargate — no nodes to manage, per-pod billing
• Predictable, stable: MNG — familiar ASG model, managed updates
• Custom requirements: Self-managed — full control, highest overhead

✅ DO:

• Use Karpenter as the default node autoscaler for new clusters
• Run system components (CoreDNS, Karpenter) on MNG or Fargate
• Use multiple instance types for availability and cost optimization

❌ DON'T:

• Use self-managed nodes without a specific technical requirement
• Run Fargate for GPU or DaemonSet-dependent workloads
• Mix Karpenter and Cluster Autoscaler on the same node groups

Networking Quick Reference

VPC CNI Mode Decision

Mode	Use When	Pod Density
Secondary IP (default)	Most workloads, simple setup	Limited by ENI × IPs per ENI
Prefix Delegation	>30 pods/node, IP-constrained VPC	4-16× more pods per node
Custom Networking	Pods need different CIDR than nodes	Same as underlying mode

Ingress Pattern Selection

Pattern	Best For	Key Feature
ALB (via LBC)	HTTP/HTTPS web apps	Native WAF, Cognito auth
NLB (via LBC)	TCP/UDP, gRPC, low latency	Static IPs, source IP preservation
Gateway API	Multi-team, new deployments	✅ Recommended standard
VPC Lattice	Cross-VPC service-to-service	No sidecar, IAM auth

IPv4 vs IPv6

Factor	IPv4	IPv6
Default choice	✅ Yes	When facing IP exhaustion
AWS service support	Full	Most (check specific services)
Complexity	Standard	Requires dual-stack VPC

For detailed networking guidance, see: Networking — VPC CNI & IP | Networking — Ingress & DNS

Security Essentials

IAM Strategy

Approach	Use When	Setup
Pod Identity	✅ New workloads (EKS 1.24+)	EKS add-on + association
IRSA	Older clusters, Fargate	OIDC provider + trust policy

Key rules:

• ✅ Use Pod Identity for new workloads — simpler setup, session tags, role chaining
• ✅ Use EKS access entries (API mode) over aws-auth ConfigMap
• ✅ Move VPC CNI permissions from node role to Pod Identity/IRSA
• ❌ Don't use wildcard conditions in IRSA trust policies
• ❌ Don't attach application permissions to node IAM roles

Pod Security Baseline

Apply Pod Security Admission (PSA) labels to all namespaces:

# Minimum: enforce baseline, warn on restricted
metadata:
  labels:
    pod-security.kubernetes.io/enforce: baseline
    pod-security.kubernetes.io/warn: restricted

Secrets Management

Approach	Complexity	Best For
External Secrets Operator	Medium	✅ GitOps workflows
Secrets Store CSI	Medium	Mount secrets as volumes
KMS envelope encryption	Low	Encrypt etcd secrets

Always enable KMS envelope encryption for Kubernetes secrets.

For detailed security guidance, see: Security Reference | Runtime & Network | Supply Chain & Compliance

Reliability Essentials

Pod Disruption Budgets

Create PDBs for every production workload with >1 replica:

Workload	Recommended PDB
Stateless (3+ replicas)	minAvailable: "50%"
Stateful quorum (3)	maxUnavailable: 1
Batch/job	maxUnavailable: "50%"
Singleton	No PDB (would block all disruptions)

Health Probe Strategy

Probe	Purpose	Key Rule
Startup	Wait for slow init	Use for apps >10s startup
Readiness	Traffic routing	✅ Check dependencies here
Liveness	Detect deadlocks	❌ Never check dependencies

Critical rule: Liveness probes must NOT check external dependencies. If the database goes down and liveness checks the DB, ALL pods restart — causing cascading failure.

Graceful Shutdown Pattern

spec:
  terminationGracePeriodSeconds: 60
  containers:
  - lifecycle:
      preStop:
        exec:
          command: ["/bin/sh", "-c", "sleep 15"]

Why sleep 15: Gives kube-proxy and load balancer time to remove the pod from traffic routing before SIGTERM.

Multi-AZ Distribution

topologySpreadConstraints:
- maxSkew: 1
  topologyKey: topology.kubernetes.io/zone
  whenUnsatisfiable: DoNotSchedule

For detailed reliability guidance, see: Reliability & Resiliency — Core (see also reliability-advanced.md for DR, deployment strategies, and large-cluster guidance)

Cluster Upgrade Strategy

Upgrade Sequence (Strict Order)

1. Control Plane → 2. EKS Add-ons → 3. Data Plane → 4. Custom Add-ons

Pre-Upgrade Checklist

1. Check EKS Cluster Insights for upgrade readiness
2. Scan for deprecated APIs (Pluto, kube-no-trouble)
3. Verify add-on compatibility with target version
4. Test in non-prod environment first
5. Ensure PDBs are configured for graceful node drain
6. Back up cluster state (Velero or GitOps repo)

Upgrade Strategy Decision

Factor	In-Place	Blue-Green
Risk	Low-Medium	Lowest
Cost	No extra	2× during migration
Rollback	❌ No CP rollback	✅ Switch back
Use when	✅ Most upgrades	Critical workloads

Data Plane with Karpenter

Karpenter automatically replaces nodes via drift detection after control plane upgrade. Control the speed with disruption.budgets:

disruption:
  budgets:
  - nodes: "10%"  # Max 10% of nodes replaced at a time

For detailed upgrade guidance, see: Cluster Upgrades Reference

Autoscaling Quick Reference

Node Autoscaler Selection

	Karpenter	Cluster Autoscaler	Auto Mode
Default choice	✅ Yes	Legacy/Outposts	Minimal ops
Scale-up speed	~30s	~60-90s	AWS-managed
Consolidation	✅ Built-in	❌	✅
Customization	High	Medium	Low

Pod Autoscaler Selection

Scaler	Trigger	Use Case
HPA	CPU, memory, custom	Stateless services
VPA	Historical usage	Right-sizing (recommendation mode)
KEDA	External events (SQS, Kafka)	Event-driven workloads

For detailed autoscaling guidance, see: Autoscaling Reference | Karpenter Reference

Terraform Examples Quick Start

Based on terraform-aws-modules/terraform-aws-eks.

Example Selection

Starting Point	Recommended Example
General production	karpenter (MNG for system + Karpenter for workloads)
Minimal ops	eks-auto-mode
Managed nodes	eks-managed-node-group (AL2023 or Bottlerocket)
Full node control	self-managed-node-group
Platform capabilities	eks-capabilities (ArgoCD, ACK, KRO)
Hybrid/edge	eks-hybrid-nodes

Common Deployment Topologies

Private cluster with Karpenter:

VPC (3 AZs, terraform-aws-modules/vpc/aws)
├── Private subnets → EKS nodes (MNG for system, Karpenter for workloads)
├── Public subnets  → ALB (internet-facing)
├── Intra subnets   → EKS control plane ENIs
└── NAT Gateway     → 1 per AZ for production

Multi-tenant platform:

EKS Cluster (terraform-aws-modules/eks/aws)
├── kube-system         (platform: CoreDNS, kube-proxy, VPC CNI)
├── karpenter           (Karpenter controller on MNG)
├── monitoring          (shared: Prometheus, Grafana)
├── ingress             (shared: AWS LBC)
├── team-a namespace    (RBAC, NetworkPolicy, ResourceQuota)
├── team-b namespace    (RBAC, NetworkPolicy, ResourceQuota)
└── team-c namespace    (RBAC, NetworkPolicy, ResourceQuota)

For detailed examples and terraform patterns, see: Terraform Examples Reference

Cost Optimization Quick Wins

Action	Savings	Effort
Graviton (arm64)	20-40%	Low
Spot for non-critical	60-90%	Low
Karpenter consolidation	20-30%	Low
VPA right-sizing	15-30%	Medium
gp3 over gp2	20% on EBS	Low
VPC endpoints	Eliminate NAT costs	Low

For detailed cost guidance, see: Cost Optimization Reference | For scalability guidance, see: Scalability Reference

Observability Quick Reference

Pillar	AWS-Managed	Open Source
Metrics	Container Insights	AMP + Grafana
Logs	CloudWatch Logs	OpenSearch, Loki
Traces	X-Ray	ADOT + Jaeger/Tempo

Essential: Enable EKS audit logging and GuardDuty EKS Runtime Monitoring for security visibility.

For detailed observability guidance, see: Observability Reference

EKS Capabilities

EKS Capabilities are AWS-managed features installed and updated as part of the EKS platform. They run in AWS-owned infrastructure separate from your clusters, with AWS handling scaling, patching, and upgrading.

Capability	What It Does	When to Use Managed	When to Self-Manage
ArgoCD	GitOps continuous delivery	Multi-account hub-and-spoke, IAM IDC integration, minimal ops	Custom plugins, air-gapped, existing ArgoCD investment
ACK	Manage AWS resources via K8s CRDs (S3, RDS, IAM, etc.)	Standard AWS resource management	Specific controller version pinning, custom config
KRO	Platform abstractions via ResourceGroupDefinitions	Golden path templates, multi-resource compositions	Early adoption risk concerns, custom reconciliation logic

Combined pattern: ArgoCD deploys ACK resources + KRO compositions via GitOps, providing a single workflow for both infrastructure and applications.

For detailed ArgoCD patterns, see: ArgoCD Patterns Reference

Sources:

• EKS Capabilities Documentation
• AWS Blog — Deep dive: Simplifying resource orchestration with Amazon EKS Capabilities

Detailed References

This skill uses progressive disclosure — essential guidance is in this main file, detailed reference material is loaded on demand:

• Security — IAM, Cluster Access Manager, Pod Identity, IRSA, pod security standards, multi-tenancy, secrets management, data encryption
• Security — Runtime & Network — Runtime threat detection (GuardDuty, seccomp, AppArmor, Falco), network policies, SG for pods, encryption in transit, detective controls
• Security — Supply Chain & Compliance — Image security (SBOMs, attestations, ECR hardening), infrastructure hardening (Bottlerocket, CIS benchmarks), regulatory compliance, incident response
• Networking — VPC CNI modes (secondary IP, prefix delegation, custom networking), subnet/CIDR planning, IPv4 vs IPv6, Security Groups for Pods, IP address management
• Networking — Ingress & DNS — Ingress patterns (ALB, NLB, Gateway API), AWS Load Balancer Controller, service mesh, DNS/CoreDNS tuning, private cluster connectivity
• Reliability & Resiliency — Core — HA patterns, PDBs, health probes, load balancer health checks, lifecycle hooks, topology spread, resource management
• Reliability & Resiliency — Advanced — disaster recovery, zonal shift, deployment strategies, large cluster guidance, chaos engineering, admission-controller topology enforcement
• Autoscaling — Autoscaler selection, Cluster Autoscaler (IAM, Spot, overprovisioning, parameter tuning), HPA, VPA, KEDA, CoreDNS autoscaling
• Karpenter — Operational best practices, NodePools, EC2NodeClass, Spot/interruption handling, consolidation, multiple NodePool strategy, cost controls, resource management, private clusters, CoreDNS with Karpenter
• Cluster Upgrades — In-place and blue-green upgrades, pre-upgrade validation, add-on management, API deprecation detection, version skew policy, Bottlerocket updates, rollback procedures
• Cost Optimization — CFM framework, compute/networking/storage cost strategies, observability cost management, Spot, Graviton, tagging, Kubecost
• Scalability — Scaling theory (churn rate, QPS), control plane (APF, monitoring), data plane (node sizing, diversity), cluster services (CoreDNS, Metrics Server), workload patterns, IPVS, large-cluster guidance
• Observability — Observability strategy, CloudWatch Container Insights & Application Signals, Prometheus/Grafana, control plane monitoring, network performance monitoring, logging architecture, distributed tracing, GPU/AI-ML observability, detective controls, alerting patterns
• Terraform Examples — terraform-aws-modules/terraform-aws-eks examples, submodules, add-on management, Provisioned Control Plane, EFA, VPC patterns, deployment topologies
• ArgoCD Patterns — ArgoCD architecture, App of Apps, ApplicationSets, GitOps Bridge, multi-cluster patterns (hub-and-spoke, decentralized, hybrid), EKS ArgoCD Capability (managed vs self-managed, migration), ACK/KRO integration, multi-tenant RBAC
• Container Registry — ECR architecture, operating models, image promotion, vulnerability scanning, base image curation, lifecycle policies, pull-through cache, repository creation templates, managed signing (AWS Signer), archival storage class, registry configuration
• EKS Auto Mode — Auto Mode architecture, managed NodePools/NodeClasses, migration from standard EKS, comparison with self-managed Karpenter, limitations and FAQ

How to use: When you need detailed information on a topic, reference the appropriate guide. Claude will load it on demand.

Sources

• AWS EKS Best Practices Guide
• terraform-aws-modules/terraform-aws-eks