Cloud Foundations & AWS Core

Chapter 1 of 6 — AI Cloud Engineer Roadmap

This roadmap is the same week-by-week curriculum beCloudReady runs live in its AI Cloud Engineer Bootcamp, repackaged as a free, self-paced path — six chapters, AWS through containers, IaC, CI/CD, SRE, and finally AI agents. Chapter 1 is the foundation everything after it assumes you have: a real AWS account, a VPC you understand (not just clicked through), and an IAM mental model that doesn't fall apart the first time you hit AccessDenied.

What you'll build: a custom VPC with public and private subnets, plus an IAM setup you'll reuse in every chapter that follows.

Tools: AWS, Terraform, IAM, EKS, Lambda

Where AI helps: Claude (or your LLM of choice) generates the Terraform templates — you still decide the architecture. That division of labor holds for the rest of the roadmap: AI writes boilerplate, you own the design decisions.

Before you start: basic Linux CLI, comfort with Bash or Python, an AWS Free Tier account with an IAM admin user and access keys configured, and the AWS CLI installed.

Modules in this chapter

• AWS Cloud Practitioner Essentials — the vocabulary: regions, AZs, the shared responsibility model
• Virtual Private Cloud (VPC) — subnets, route tables, NAT gateways, security groups
• AWS EC2 — instances, AMIs, instance profiles
• AWS IAM — Lab builder — users, roles, policies, least privilege
• AWS RDS for PostgreSQL — managed relational databases, the data layer most apps in this roadmap eventually need

Why this matters

Every later chapter in this roadmap runs inside the network and IAM model you build here. The Kubernetes cluster in Chapter 2 needs subnets to live in. The Terraform pipeline in Chapter 3 needs an IAM role with exactly the right permissions, no more. Skipping this chapter because "I already know AWS basics" is the single most common reason people get stuck debugging permission errors three chapters later instead of building.

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Next: Containers & Orchestration

Chapter 2 takes the VPC and IAM foundation from this chapter and runs a containerized app on an EKS cluster inside it — Docker, Helm, and your first real Kubernetes deployment.