DevOps with Claude Code: Terraform, EKS, ArgoCD & Helm

About this course

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 zonesAn Amazon EKS cluster running cost-optimized Graviton ARM nodesAmazon RDS MySQL for persistent storageAmazon ECR with lifecycle policies and vulnerability scanningA GitOps pipeline using ArgoCD (auto-sync for dev, manual approvals for production)GitHub Actions CI pipelines that build, push, and trigger deploymentsSecrets Manager integrated with External Secrets Operator for KubernetesA full observability stack with Prometheus, Grafana, Fluent Bit, and ZipkinWhy 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

Course objectives

• apply AI tools in DevOps practices
• gain experience managing a DevOps project end-to-end
• evaluate AI-generated outputs for production readiness