¶ EKS (Elastic Kubernetes Service)
¶ Dev Ops
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¶ Introduction to Amazon EKS: Navigating the Future of Cloud-Native Kubernetes
In the early days of Kubernetes adoption, teams faced a familiar fork in the road: either take on the challenge of hosting and managing their own clusters or step into the world of managed services that promised to handle the heavy lifting. As Kubernetes grew from an experimental container orchestrator into the backbone of modern cloud-native architecture, it quickly became clear that most organizations needed something more dependable, scalable, and well-integrated than a cluster they had to babysit themselves.
This is where Amazon Elastic Kubernetes Service—EKS—began carving its place in the DevOps world. EKS isn’t just a managed Kubernetes service. It’s an entire ecosystem built on top of AWS’s global infrastructure, designed to help teams run containerized workloads without drowning in operational overhead. In a sense, EKS represents AWS’s promise: “We’ll take care of Kubernetes control-plane complexity—just focus on building your applications.”
This course of 100 articles will walk you through that world, from foundational concepts to advanced cluster networking, autoscaling, observability, and production-grade design patterns. Before we begin that journey, it’s worth grounding ourselves in what EKS really is, why it matters, and how it fits into the broader evolution of DevOps and cloud-native engineering.
¶ Why Kubernetes—and Why EKS?
Kubernetes took the industry by storm not because it was the easiest technology to learn, but because it solved one of the biggest problems DevOps teams faced: how to run containers at scale, consistently, reliably, and across countless environments.
Instead of scattering containers across machines and managing them manually, Kubernetes offered:
- A way to declare your application’s desired state
- Automated scheduling and placement
- Built-in mechanisms for scaling, healing, and rolling updates
- A universal model that works on any infrastructure
But with that power came complexity. Running Kubernetes yourself means maintaining control-plane components like etcd, API servers, schedulers, controllers, and networking layers—all while keeping them secure, up to date, and properly configured.
EKS removes that burden. It gives you a Kubernetes environment where the control plane is fully managed by AWS. No patching, no cluster upgrades on your own, no worrying about restoring etcd or diagnosing API-server failures.
You focus on your workloads. AWS handles the rest.
This division of responsibility, simple as it sounds, has been a game-changer for countless engineering teams.
¶ The Philosophy Behind EKS
Every design decision in EKS reflects a certain philosophy: Kubernetes should feel powerful, but not painful.
If you look closely, EKS leans on a few guiding principles:
-
Reduce operational overhead without limiting flexibility
Unlike some platforms that simplify Kubernetes by heavily abstracting it, EKS sticks close to upstream Kubernetes. There’s very little vendor lock-in. -
Integrate deeply with AWS services
Identity, networking, storage, observability, security—EKS is built to work with tools that teams already rely on inside AWS. -
Make scaling predictable and cost-efficient
From managed node groups to autoscaling mechanisms, EKS offers ways to grow or shrink workloads gracefully. -
Handle reliability at massive scale
EKS clusters run on top of AWS’s globally distributed, battle-tested cloud infrastructure.
Because of these principles, organizations rarely outgrow EKS. Small teams adopt it because it simplifies cluster management. Large enterprises use it because it supports even the most demanding workloads.
¶ Why EKS Has Become a DevOps Essential
Today’s DevOps teams operate in an environment where agility matters as much as stability. Deployments need to be frequent, failures need to be contained, and infrastructure needs to scale with demand. EKS enables all of this by giving teams a platform where workloads are:
- Containerized
- Declaratively managed
- Dynamically scheduled
- Automatically healed
- Horizontally scalable
- Infrastructure-agnostic in design
Several real-world scenarios show why EKS fits so naturally into this picture:
- Microservices architectures: Dozens or hundreds of services require orchestration, security boundaries, and rolling deployments.
- High-traffic APIs: Auto-scaling ensures that traffic spikes don’t overwhelm systems.
- Data processing workloads: Stateful sets, persistent volumes, and custom operators make it easier to handle pipelines.
- ML/AI models: GPU-backed nodes can join EKS clusters to accelerate inference.
- Hybrid cloud environments: EKS Anywhere allows clusters to run outside AWS while still offering a consistent experience.
EKS is not just for cloud-native pioneers; it’s for anyone who wants predictable, automated infrastructure without sacrificing the flexibility of standard Kubernetes.
¶ What Learning EKS Really Means
EKS is not a single tool—it is the intersection of Kubernetes, AWS networking, infrastructure security, containerization best practices, and observability. Learning it deeply means learning how all these layers interact.
At first, the surface may feel familiar: pods, deployments, services, ingresses, ConfigMaps. But as you dig deeper, you see how AWS shapes the cluster’s behavior.
You start exploring:
- VPC networking models for Kubernetes pods and services
- Node groups—both managed and self-managed
- Fargate profiles for serverless containers
- IAM roles for service accounts (IRSA) to fine-tune security
- Cluster autoscaler and Karpenter for dynamic node provisioning
- Load balancer integration using AWS ALB, NLB, and Gateway API
- Persistent volume management using EBS, EFS, and FSx
- Observability stacks with CloudWatch, Prometheus, Grafana, and OpenTelemetry
Even though EKS simplifies Kubernetes, it does not hide it. You’re still working with real Kubernetes clusters—not a watered-down version—so the knowledge you build here is transferable across clouds.
¶ EKS and the Evolution of DevOps Thinking
DevOps has always been about breaking down silos between development and operations. Kubernetes further pushed that philosophy by giving teams one unified platform for running everything from microservices to background jobs.
EKS amplifies this shift. It encourages:
- Infrastructure-as-code with tools like Terraform, eksctl, and CloudFormation
- GitOps deployments using Argo CD or Flux
- Continuous integration and delivery pipelines built around containerized workflows
- Automation-first operations, where human intervention becomes the exception, not the rule
- Observability as a core requirement, not an afterthought
Over time, adopting EKS often leads to an organizational transformation. Teams begin designing services differently, thinking more about resilience, and relying on automation for tasks that used to require manual intervention.
¶ How EKS Fits Into the Broader AWS Ecosystem
One of the reasons EKS has gained such traction is that it feels deeply “native” to AWS. You can assemble entire architectures where everything fits seamlessly together:
- Load balancing through Application Load Balancers or Network Load Balancers
- Secrets management through AWS Secrets Manager or SSM Parameter Store
- Logging and metrics through CloudWatch, OpenSearch, and Grafana
- Autoscaling via EC2 Auto Scaling Groups, Karpenter, or HPA/VPA
- Security through IAM, Security Groups, and Network Policies
- Storage through EBS, EFS, FSx, or S3-based gateways
Because EKS doesn’t abstract away Kubernetes, you still get full flexibility. But because it integrates into AWS, you also get intuitive mechanisms for handling everything happening outside the cluster.
It’s this blend of openness and integration that sets EKS apart.
¶ Who This Course Is For
This course is built for anyone who wants to understand cloud-native engineering through the lens of one of the most widely adopted managed Kubernetes platforms.
It’s perfect for:
- DevOps engineers automating cluster operations
- Cloud engineers who want to master Kubernetes on AWS
- Application developers deploying microservices and APIs
- SREs managing reliability and scaling
- Architects designing cloud-native systems
- Students and enthusiasts stepping into container orchestration
- Teams migrating legacy applications to containerized platforms
No matter your background, the aim of this course is to bring clarity to a space often filled with jargon, complexity, and overwhelming documentation.
¶ A Future Powered by Kubernetes—and Strengthened by EKS
Kubernetes has already proven that it’s here to stay. It has reshaped how we build, deploy, and run applications. What services like EKS add to that picture is trust—a sense that you can build ambitious architectures without being crushed by operational burden.
Throughout this course, you’ll gradually see how EKS becomes the anchor for modern DevOps work:
- Applications scale effortlessly.
- Deployments become predictable.
- Infrastructure becomes traceable.
- Failures become manageable.
- Teams become more productive.
EKS may look like “just a managed Kubernetes service,” but for many teams, it becomes the backbone of a new era of engineering—one where automation, resilience, and cloud-native principles become the standard, not the exception.
By the time you finish the full set of 100 articles, you’ll not only understand EKS technically—you’ll understand how to design, operate, and evolve robust Kubernetes environments on AWS with confidence and clarity.
¶ EKS (Elastic Kubernetes Service)
¶ Beginner Level
1. Introduction to Kubernetes and Amazon EKS: What You Need to Know
2. Setting Up Your First Amazon EKS Cluster
3. Understanding the Key Components of EKS: Clusters, Nodes, and Pods
4. Getting Started with kubectl for Managing Your EKS Cluster
5. Creating Your First EKS Cluster Using the AWS Management Console
6. Introduction to AWS IAM and Permissions for EKS Access
7. Exploring the EKS Dashboard: Key Features and Metrics
8. Installing and Configuring kubectl for EKS Management
9. Scaling Kubernetes Clusters in Amazon EKS
10. Deploying a Simple Web Application to Amazon EKS
11. Amazon EKS Networking Basics: VPC, Subnets, and Security Groups
12. Configuring EKS Nodes with EC2 Instances
13. Understanding EKS Managed Node Groups
14. Introduction to Pods and Deployments in Kubernetes on EKS
15. Exposing Applications on EKS Using Services and Load Balancers
16. Managing Kubernetes Configurations with ConfigMaps and Secrets in EKS
17. Setting Up Kubernetes Volumes for Persistent Storage on EKS
18. Exploring Auto Scaling for EKS Worker Nodes
19. EKS and Container Images: Building and Pushing Images to ECR
20. How to Use AWS CloudFormation to Create and Manage EKS Clusters
21. Understanding EKS Security: Identity and Access Management (IAM)
22. Kubernetes Namespace Management on Amazon EKS
23. Monitoring Amazon EKS Clusters with CloudWatch and Prometheus
24. Best Practices for Deploying and Managing Microservices on EKS
25. Introduction to Helm for Managing Kubernetes Applications on EKS
¶ Intermediate Level
26. Automating EKS Cluster Provisioning with Terraform
27. Understanding the EKS Control Plane Architecture
28. Integrating EKS with AWS RDS and DynamoDB for Database Management
29. Configuring Horizontal Pod Autoscaling in EKS
30. Managing Networking in Amazon EKS with VPC CNI
31. Setting Up EKS for CI/CD with Jenkins
32. Using Amazon EKS with Amazon ECR for Container Image Storage
33. How to Manage Kubernetes Secrets and ConfigMaps on EKS
34. Setting Up Multi-AZ Deployments in Amazon EKS for High Availability
35. Creating and Managing Amazon EKS Fargate Profiles
36. Deploying Stateful Applications on Amazon EKS with StatefulSets
37. Implementing Blue-Green Deployments on EKS
38. Using Helm to Simplify Kubernetes Application Deployment on EKS
39. Integrating EKS with Amazon Route 53 for DNS Management
40. Using Amazon EKS with AWS Lambda for Serverless Workflows
41. How to Set Up EKS with the Kubernetes Dashboard for Cluster Management
42. Managing Ingress Controllers in EKS for HTTP/HTTPS Traffic Routing
43. Setting Up Application Monitoring with Prometheus and Grafana on EKS
44. Managing Kubernetes Jobs and CronJobs on EKS
45. Exploring EKS with AWS App Mesh for Microservices Communication
46. How to Set Up Continuous Integration with EKS and GitLab CI
47. Configuring AWS Identity and Access Management (IAM) Roles for Service Accounts
48. Integrating AWS CloudTrail with EKS for Security Auditing
49. Managing Kubernetes Resources with kubectl and EKS CLI
50. How to Use AWS X-Ray for Distributed Tracing on EKS
51. EKS Networking Policies: Securing Communication Between Pods
52. Using Amazon EKS to Build a Multi-Cloud Kubernetes Architecture
53. Managing Resource Requests and Limits in Amazon EKS
54. Setting Up and Managing Kubernetes Role-Based Access Control (RBAC) on EKS
55. Using EKS with AWS CloudWatch Logs for Kubernetes Log Management
56. Automating EKS Cluster Updates and Maintenance with AWS Managed Updates
57. Integrating EKS with CloudFormation for Automated Infrastructure Deployment
58. Securing Amazon EKS Clusters: Best Practices for Authentication and Authorization
59. Managing Deployments with Helm Charts on Amazon EKS
60. Using EKS with Karpenter for Autoscaling Kubernetes Nodes
¶ Advanced Level
61. Advanced EKS Cluster Networking: Using CNI Plugins for VPC and VPC Peering
62. Implementing Zero-Downtime Deployments with Kubernetes on EKS
63. How to Set Up EKS Cluster Federation for Multi-Cluster Management
64. Managing Cluster Scaling with Cluster Autoscaler on Amazon EKS
65. Integrating AWS KMS for Encryption of Kubernetes Secrets in EKS
66. Multi-Region and Multi-AZ Architecture for EKS High Availability
67. Implementing Serverless Kubernetes Workloads with EKS and AWS Fargate
68. Advanced Security Measures: Securing EKS with Private Clusters
69. Managing and Deploying Helm 3 on Amazon EKS
70. How to Integrate Amazon EKS with AWS Secrets Manager for Secure Secrets Handling
71. Automating Continuous Delivery Pipelines with EKS and AWS CodePipeline
72. Running Large-Scale Machine Learning Workloads on Amazon EKS
73. Scaling EKS Clusters Automatically with AWS Auto Scaling Groups
74. Running Stateful Applications in Kubernetes on EKS with Persistent Storage
75. Configuring Amazon EKS with ECR to Automate Image Scanning and Security
76. Advanced Observability: Using EKS with Fluentd, Elasticsearch, and Kibana (EFK Stack)
77. Building and Managing Multi-Tenant EKS Clusters
78. Implementing GitOps on EKS with ArgoCD for Continuous Deployment
79. Managing Kubernetes Cluster Security with Aqua Security and Amazon EKS
80. Advanced Kubernetes Scheduling Techniques for EKS
81. Running EKS in a Multi-Tenant Environment with Network Policies
82. Customizing and Extending Kubernetes with CRDs on Amazon EKS
83. Using EKS with AWS Elastic File System (EFS) for Persistent Shared Storage
84. Continuous Security Monitoring and Compliance with EKS and AWS Config
85. Implementing Load Balancer Management for Microservices on Amazon EKS
86. Using EKS with Cloud-Native Tools: Kafka, Redis, and MongoDB
87. Integrating EKS with Kubernetes Operators for Custom Resource Management
88. Best Practices for Backup and Disaster Recovery on EKS
89. Building High-Performance Kubernetes Workloads on Amazon EKS
90. Exploring Cross-Cluster Communication and Service Discovery in EKS
91. Automating Kubernetes Cluster Management and Infrastructure as Code (IaC) on EKS
92. Securing Kubernetes Clusters with AWS WAF and EKS
93. Monitoring Kubernetes Pods and Nodes with AWS CloudWatch Container Insights
94. Building a Serverless Data Pipeline with EKS, AWS Lambda, and S3
95. Multi-Cluster Management: EKS with Amazon Elastic Kubernetes Service (EKS) Anywhere
96. Using EKS with ExternalDNS for Dynamic DNS Updates
97. Implementing Event-Driven Architecture with Amazon EventBridge on EKS
98. Advanced Kubernetes Resource Management: Scaling Jobs and CronJobs on EKS
99. Deploying and Managing Complex Applications with EKS and Istio
100. Future of Kubernetes with EKS: AI/ML Integration and Serverless Trends