You're reading from Generative AI-Powered Assistant for Developers Accelerate software development with Amazon Q Developer

Product type Paperback

Published in Aug 2024

Publisher Packt

ISBN-13 9781835089149

Length 416 pages

Edition 1st Edition

Tools

AWS

Concepts

GPT/LLMs

Authors (2):

Behram Irani

Rahul Sonawane

View More author details

Table of Contents (23) Chapters

Preface

1. Part 1:Generative AI-Powered Assistant

2. Chapter 1: Introduction to Generative AI-Powered Assistants FREE CHAPTER

3. Chapter 2: Introducing and Setting Up Amazon Q Developer

4. Part 2:Generate Code Recommendations

5. Chapter 3: Understanding Auto-Code Generation Techniques

6. Chapter 4: Boost Coding Efficiency for Python and Java with Auto-Code Generation

7. Chapter 5: Boost Coding Efficiency for C and C++ with Auto-Code Generation

8. Chapter 6: Boost Coding Efficiency for JavaScript and PHP with Auto-Code Generation

9. Chapter 7: Boost Coding Efficiency for SQL with Auto-Code Generation

10. Chapter 8: Boost Coding Efficiency for Command-Line and Shell Script with Auto-Code Generation

11. Chapter 9: Boost Coding Efficiency for JSON, YAML, and HCL with Auto-Code Generation

12. Part 3:Advanced Assistant Features

13. Chapter 10: Customizing Code Recommendations

14. Chapter 11: Understanding Code References

15. Chapter 12: Simplifying Code Explanation, Optimization, Transformation, and Feature Development

16. Chapter 13: Simplifying Scanning and Fixing Security Vulnerabilities in Code

17. Part 4:Accelerate Build on AWS

18. Chapter 14: Accelerate Data Engineering on AWS

19. Chapter 15: Accelerate Building Solutions on AWS

20. Chapter 16: Accelerate the DevOps Process on AWS

21. Index

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Accelerate Data Engineering on AWS

In this chapter, we will look at the following key topics:

Code assistance options with AWS services
Code assistance integration with AWS Glue
Code assistance integration with Amazon EMR
Code assistance integration with AWS Lambda
Code assistance integration with Amazon SageMaker
Code assistance integration with Amazon Redshift

In the previous part of the book, we explored auto-code generation techniques and the integration of a code companion with integrated development environments (IDEs) and provided examples using JetBrains PyCharm IDE with Amazon Q Developer for different languages that developers use very often. In this chapter, we will specifically focus on how Amazon is expanding in the area of assisting code developers by integrating with core AWS services.