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Keep shoppingDevOps with Claude Code: Terraform, EKS, ArgoCD & Helm
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DevOps with Claude Code: Terraform, EKS, ArgoCD & Helm
Build & deploy 8 microservices to production on AWS — Karpenter, GitOps, CI/CD, Observability + Resume Prep
Last updated 6/2026
English
What you'll learn
- Deploy a real microservices app to AWS EKS using Terraform, ArgoCD, and GitHub Actions — with Claude Code writing all the infra code.
- Build production-grade AWS infrastructure: VPC, EKS, RDS, ECR, Secrets Manager, ALB Ingress, and a full observability stack.
- Use Claude Code to generate, review, and apply Terraform modules, Kubernetes manifests, CI/CD pipelines, and runbooks.
- Implement a GitOps workflow with ArgoCD — auto-sync to dev, manual approval for prod — driven entirely by AI-generated code.
- Master the AI-assisted DevOps workflow: architect, prompt, review — and ship production infrastructure without writing code yourself.
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Course content
17 sections • 81 lectures • 12h 5m total length
Requirements
- Basic Linux command line and AWS familiarity required.
- Familiarity with Terraform, Kubernetes experience needed
Description
What if you could deploy production-grade AWS infrastructure without writing a single line of code yourself?
That’s exactly what this course is about. You’ll take a real Spring Boot microservices application—eight services, real databases, real traffic—and push it all the way to production on AWS. Every Terraform module, every Kubernetes manifest, every CI/CD pipeline, and every runbook is generated by Claude Code. Your role is to think like an architect: write precise prompts, review the outputs, and make sure everything is production-ready.
This isn’t a step-by-step tutorial. It’s a project.
You step into the role of a DevOps engineer handed a Jira board and expected to deliver. You’ll work through real epics—networking, compute, container registry, databases, secrets, GitOps, observability—in the same sequence a real production team would follow.
What you’ll build:
A VPC with public subnets across multiple availability zones
An Amazon EKS cluster running cost-optimized Graviton ARM nodes
Amazon RDS MySQL for persistent storage
Amazon ECR with lifecycle policies and vulnerability scanning
A GitOps pipeline using ArgoCD (auto-sync for dev, manual approvals for production)
GitHub Actions CI pipelines that build, push, and trigger deployments
Secrets Manager integrated with External Secrets Operator for Kubernetes
A full observability stack with Prometheus, Grafana, Fluent Bit, and Zipkin
Why Claude Code?
AI doesn’t replace engineers—it amplifies them. But only if you know how to guide it, evaluate its output, and catch what it misses. This course focuses on building that skill in the context of a real-world project, so you walk away with both working infrastructure and a repeatable workflow.
By the end, you’ll have:
A production-ready AWS platform in your GitHub portfolio
Hands-on experience with Terraform, EKS, ArgoCD, and GitHub Actions
A repeatable, AI-assisted workflow you can apply to future projects
If you’ve been meaning to get serious about cloud infrastructure, this is where it starts.
Who this course is for:
- DevOps and cloud engineers who want to use AI to build real AWS infrastructure faster — and learn by doing, not by watching slides.
- Software engineers moving into DevOps who want a hands-on, project-based intro to AWS, Kubernetes, Terraform, and GitOps with ArgoCD.