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

Why subscribe?

22. Other Books You May Enjoy

Code assistance integration with AWS Glue

Before we start diving deep into code assistance support for AWS Glue service, let’s quickly go through an overview of AWS Glue. AWS Glue is a serverless data integration service designed to simplify the process of discovering, preparing, moving, and integrating data from diverse sources, catering to analytics, ML, and application development needs. At the very high level, AWS Glue has the following major components, and each of them has multiple features to support data engineers:

Glue Data Catalog: It’s a centralized technical metadata repository. It stores metadata about data sources, transformations, and targets, providing a unified view of the data.
Glue Studio: AWS Glue Studio offers a graphical interface that facilitates the seamless creation, execution, and monitoring of data integration jobs within AWS Glue. Additionally, it provides Jupyter notebooks for advanced developers.

AWS Glue Studio is seamlessly...