Leverage Amazon Q Developer to boost productivity and maximize efficiency by accelerating software development life cycle tasks
Key Features
- First book on the market to thoroughly explore all of Amazon Q Developer’s features
- Gain an understanding of Amazon Q Developer’s capabilities across the software development life cycle through real-world examples
- Build apps with Amazon Q Developer by auto-generating code in various languages within supported IDEs
- Purchase of the print or Kindle book includes a free PDF eBook
Book Description
Many developers face the challenge of managing repetitive tasks and maintaining productivity. This book will help you tackle both these challenges with Amazon Q Developer, a generative AI-powered assistant designed to optimize coding and streamline workflows.
This book takes you through the setup and customization of Amazon Q Developer, demonstrating how to leverage its capabilities for auto-code generation, code explanation, and transformation across multiple IDEs and programming languages. You’ll learn to use Amazon Q Developer to enhance coding experiences, generate accurate code references, and ensure security by scanning for vulnerabilities. The book also shows you how to use Amazon Q Developer for AWS-related tasks, including solution building, applying architecture best practices, and troubleshooting errors. Each chapter provides practical insights and step-by-step guidance to help you fully integrate this powerful tool into your development process. You’ll get to grips with effortless code implementation, explanation, transformation, and documentation, helping you create applications faster and improve your development experience.
By the end of this book, you’ll have mastered Amazon Q Developer to accelerate your software development lifecycle, improve code quality, and build applications faster and more efficiently.
What you will learn
- Understand the importance of generative AI-powered assistants in developers’ daily work
- Enable Amazon Q Developer for IDEs and with AWS services to leverage code suggestions
- Customize Amazon Q Developer to align with organizational coding standards
- Utilize Amazon Q Developer for code explanation, transformation, and feature development
- Understand code references and scan for code security issues using Amazon Q Developer
- Accelerate building solutions and troubleshooting errors on AWS
Who this book is for
This book is for coders, software developers, application builders, data engineers, and technical resources using AWS services looking to leverage Amazon Q Developer’s features to enhance productivity and accelerate business outcomes. Basic coding skills are needed to understand the concepts covered in this book.
Table of Contents
- Introduction to Generative AI-Powered Assistants
- Introducing and Setting Up Amazon Q Developer
- Understanding Auto-Code Generation Techniques
- Boost Coding Efficiency for Python and Java with Auto-Code Generation
- Boost Coding Efficiency for C and C++ with Auto-Code Generation
- Boost Coding Efficiency for JavaScript and PHP with Auto-Code Generation
- Boost Coding Efficiency for SQL with Auto-Code Generation
- Boost Coding Efficiency for Command Line and Shell Script with Auto-Code Generation
- Boost Coding Efficiency for JSON, YAML, and HCL with Auto-Code Generation
- Customizing Code Recommendations
- Understanding Code References
- Simplifying Code Explanation, Optimization, Transformation, and Feature Development
- Simplifying Scanning and Fixing Security Vulnerabilities in Code
(N.B. Please use the Read Sample option to see further chapters)
About the Author
Behram Irani is currently a technology leader at Amazon Web Services (AWS), specializing in data, analytics, and AI/ML. With over 20 years in the tech industry, he has helped organizations ranging from start-ups to large-scale enterprises modernize their data platforms. In the last 7 years at AWS, Behram has been a thought leader in the data, analytics, and AI/ML space. He has published a book and multiple papers and has led digital transformation efforts for many companies worldwide. Behram holds a Bachelor of Engineering in Computer Science from the University of Pune and an MBA from the University of Florida. He is also the author of Modern Data Architecture on AWS.
Rahul Sonawane is currently a specialist solution architect at AWS specializing in data, analytics, and AI/ML. With over 24 years of technology experience, he has worked across multiple industries globally, including retail, consulting, and large-scale enterprises. Before joining AWS, Rahul worked on Google Cloud Platform for 2 years. For the last 7 years at AWS, he has been helping organizations modernize their data platforms. Rahul has published multiple public blog posts and articles focusing on data, analytics, and AI/ML. He holds a Master of Engineering in Computer Science from the University of Pune with a specialization in data warehouse technologies.
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