Learn to automate AWS development workflows using Amazon Q and CloudShell for container deployment, infrastructure as code, and Rust development. You will explore Amazon Q as an AI-powered CLI assistant with inline completion in CloudShell's ZSH environment, generating commands for AWS resource management. The course covers Docker integration in CloudShell as a stealth feature, running containers directly in the browser-based shell with pre-installed Docker, checking available CPUs and memory, and building container workflows from pull to run. You will automate Docker build, tag, and push operations from CloudShell to Amazon ECR, including ECR authentication and image registry management. The CDK module demonstrates deploying Lambda functions with Amazon Q assistance, from CDK bootstrap through stack deployment, using Q chat to generate infrastructure as code configurations. You will develop Rust applications in CloudShell with Amazon Q inline completion in ZSH, exploring AI-powered code generation and debugging directly in the terminal. The course also covers the Docker-to-ECR architecture for production container deployments, building complete pipelines from CloudShell build to ECR push to Lambda deployment. By completing this course, you will be able to automate AWS workflows with Amazon Q in CloudShell, deploy containers to ECR, and build CDK infrastructure with AI assistance.

CLI Automation with Amazon Q and CloudShell

Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
3 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Use Amazon Q as an AI-powered CLI assistant in CloudShell with ZSH inline completion, and run Docker containers directly in CloudShell
Deploy Lambda functions with AWS CDK and Amazon Q assistance, from bootstrap to stack deployment with AI-generated configurations
Build Docker-to-ECR container pipelines from CloudShell, including image tagging, ECR authentication, and Rust development workflows
Details to know

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Recently updated!
April 2026
Assessments
3 assignments
Taught in English
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There are 3 modules in this course
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