Automate Azure, AWS, and GCP with GitHub Copilot. Build IaC, GitHub Actions pipelines, containers, operations workflows, and secure cloud automation using Bicep, AWS CDK, Terraform, OIDC, and policy as code
Key Features
- Use GitHub Copilot to accelerate IaC, scripts, and CI/CD while keeping automation reviewable and safe
- Build hands-on Azure, AWS, and GCP automation with Bicep, AWS CDK, Terraform, GitHub Actions, and OIDC
- Apply policy as code, self-healing, containers, security, compliance, monitoring, and incident automation patterns
Book Description
Cloud Automation using GitHub Copilot is a practical guide for cloud engineers and DevOps practitioners who want to use AI-assisted development to build reliable, scalable automation across Azure, AWS, and Google Cloud. Rather than replacing proven engineering practices, GitHub Copilot is used as a productivity accelerator for deterministic, reviewable Infrastructure as Code, CI/CD, and operational workflows. You will configure Copilot for cloud development, learn prompting and context techniques, and use it to scaffold IaC, scripts, and GitHub Actions workflows. Hands-on projects automate Azure App Service, AWS serverless workloads with Cloud Formation, and GCP automation using Terraform, using OIDC-based deployment pipelines. You will then automate database operations, event-driven workflows, policy as code, self-healing infrastructure, security, compliance, monitoring, and incident response. By the end, you will have reusable cross-cloud automation patterns and a complete approach for applying Copilot safely to modern cloud engineering while preserving validation, governance, maintainability, and human engineering judgment.
What you will learn
- Configure GitHub Copilot for practical cloud engineering workflows
- Prompt and control Copilot context for predictable automation outputs
- Build IaC and CI/CD pipelines with GitHub Actions across Azure, AWS, and GCP
- Automate Azure with Bicep, AWS with CDK, and GCP with Terraform
- Apply event-driven, policy-as-code, and self-healing automation patterns
- Integrate security, compliance, observability, and incident response automation
- Use AI-assisted architectural workflows while maintaining governance and engineering judgment
Who this book is for
This book is for cloud engineers, DevOps practitioners, SREs, and software developers who build, deploy, and operate modern cloud environments. Readers should have basic knowledge of Azure, AWS, or GCP, familiarity with Git and command-line tools, and some exposure to Infrastructure as Code. Deep AI expertise is not required. The book shows practitioners how to use GitHub Copilot to accelerate automation while keeping workflows deterministic, reviewable, secure, and production ready.
