Amazon Q Developer for Programmers and DevOps AWS AI coding

Explore getting started with Amazon Q developer, examining chat interactions, code generation, and practical applications you can apply to your app ideas.

Discover Amazon queue chat in your IDE, learn to use the chat interface and agentic mode to create or edit a readme file.

Discover how Amazon Q chat uses context by pinning files or a workspace to tailor responses. Create and reuse prompts, and apply rules to standardize code outputs across projects.

Learn how to interact with Amazon Q directly in your code using comments, function names, and inline chat to generate, explain, and refine email parsing implementations.

Generate professional documentation for code by adding type annotations to functions and using prompts, showing both the slash doc command and the quick, old-fashioned approach with Amazon Q Developer.

Explore Amazon Q's code review capabilities, viewing categorized warnings by severity, examining findings with explanations, and choosing to explain, fix, or ignore issues within your project.

Explore how amazon q assists debugging by hover-based hints, quick fixes, and chat fixes for simple to medium errors, including resolving promise and await issues in async code.

Explore how Amazon Q serves as a learning tool by practicing prompts, guided questions, and hints in learning mode to master Python string manipulation, regular expressions, and scripting.

Apply vibe coding with Amazon Q to build apps fast with a three-step workflow and large language models: create a base skeleton with a specialized tool, prompt AI, then iterate.

Build a password checker project with Amazon show developer, generating code, docs, unit tests, and error handling, while exploring devops and cloud operations across Java, JavaScript, and Python.

Explore how Amazon Q developer assists Java development with a coding intensive section that generates logic and unit tests, including a password checker and lists practice.

Create a Java Maven project via the cli, configure groupId and artifactId, update JUnit and Java versions, run with Maven, and generate a gitignore with Amazon Q guidance.

Build a Java password checker with Amazon Q coding assistance, implementing a checkPassword method that enforces length 8–20, requires lowercase and uppercase, digits via regex, and special characters with exceptions.

Discover how Amazon Q generates unit tests for a password checker and writes JUnit 5 tests. Learn to run tests with Maven and the Surefire plugin and inspect results.

Explore creating a Java employee list with Amazon Queue guidance, including an employee class (name, age, salary), array list operations, streams for names, age sorting, salary filters, and unit tests.

Explore Amazon Q developer for JavaScript and TypeScript to build a password checker with generated logic and tests, using node and npm in an IDE, plus lists practice.

Leverage Amazon Queue to scaffold a node project: create js/starter, run npm init -y for package.json, add src/index.js, set a start script, and gitignore node_modules.

Craft a JavaScript password checker with type and length validation, uppercase and lowercase checks, numbers and special characters, plus a version that throws the invalid password reason, with Amazon Q.

Write unit tests for the password checker functions using the node testing module, while experimenting with describe blocks and npm test, and comparing libraries like jest, mocha, and Jasmine.

Use Amazon Q to rewrite the password check, excluding the exclamation mark with a regex update, and add a clarifying comment to express intent while updating unit tests.

Learn to integrate TypeScript into your project with Amazon Q, initialize tsconfig, install as a dev dependency, and generate types and code from objects and prompts.

Explore a collections exercise in TypeScript, creating an employee type and list, filtering by salary and age, using reduce for max and average salaries, with unit tests.

Explore using Amazon Q for Python development to build a password checker and generate logic and unit tests. Practice lists and visualize data with Matplotlib, while reviewing VSCode Python setup.

Learn to build a Python password checker with Amazon Q guidance, covering length, digits, uppercase, lowercase, special-character checks, optional raise reasons, and unit tests.

Discover how to set up Python tests using built-in unit test, explore pi test and doc test options, and generate practical unit tests for password checker functions, with debugging tips.

Create an employee class with name, age, salary; build a list, populate with data via amazon q, and implement functions to list names, max salary, and salaries above a threshold.

Create and activate a Python virtual environment for data visualization with matplotlib, manage dependencies via a requirements.txt, and document steps in a readme.

Learn to visualize data in Python with matplotlib and Amazon Queue guidance, from basic plots to cosine and sine curves, world population and pie charts, with practical backend fixes.

Explore how the Amazon Q developer platform supports continuous integration and delivery using GitHub actions, with prerequisites like a GitHub account, Git installed, and basic Git operations.

Automate code building, testing, and deployment with CI/CD to deliver updates quickly through GitHub actions, guided by Amazon Q as we build AWS and Terraform workflows.

Explore how to implement CI/CD with Amazon Q using GitHub Actions. Create a repository, configure a .github/workflows YAML, and run version checks for Node, Python, and Java.

Implement end-to-end CI workflows for Java, JavaScript, and Python projects using Maven and JDK 17, including setup, build, and test steps, with workflow management for selective runs.

Explore how to use git branches, GitHub Actions, and pull requests to implement features, run tests, fix failures, and safely merge changes while managing branches.

Explore how Amazon Q developer assists infrastructure as code with Terraform, builds a serverless stack using API gateway, Lambda, and S3, and automates a CI CD pipeline with GitHub Actions.

Install the Terraform CLI and the AWS CLI across macOS, Linux, and Windows; verify versions and configure credentials, including Windows environment variables, to enable AWS access.

Configure an IAM user for the Terraform learning app, attach administrator access, generate access keys, and set up the AWS CLI with eu central 1 and json output.

Learn to write your first Terraform code with Amazon Q to create a messages bucket on S3 using the random provider for a unique suffix, and configure the AWS provider.

Deploy a small aws project with terraform, focusing on amazon ec2, and master cli commands: init, validate, plan, apply, and destroy to provision and tear down resources.

Develop simple AWS lambda functions in JavaScript and Python for a Terraform project that read and write to an S3 bucket, with CloudWatch logs testing and zip-based deployment.

Create an AWS API gateway v2 with dev stage, link it to a Python lambda via AWS proxy, and expose get and post routes with Terraform, including permissions and endpoint.

Learn to implement AWS SDK calls in a Python lambda to post json bodies to an S3 bucket and retrieve a list of objects, with IAM policy and Terraform setup.

Learn to manage Python dependencies for AWS Lambda using Terraform and layers. Create a requirements.txt, install packages with pip, and package a layer for deployment.

Handle external packages for a JavaScript lambda by initializing npm, optionally using TypeScript, and bundling with Esbuild. Automate npm install and build with Terraform to produce a dist bundle.

Build a terraform-based deployment pipeline with GitHub actions and Amazon EC2 while managing credentials via GitHub secrets; automate init, format check, validate, plan, and apply on push to main.

Discover how to use Amazon Q Developer at its full potential to boost your coding and DevOps productivity with this powerful tool.