You're reading from AWS for Solutions Architects The definitive guide to AWS Solutions Architecture for migrating to, building, scaling, and succeeding in the cloud

Product type Paperback

Published in Apr 2023

Publisher Packt

ISBN-13 9781803238951

Length 692 pages

Edition 2nd Edition

Tools

AWS

Concepts

Cloud Computing

Authors (4):

Neelanjali Srivastav

Saurabh Shrivastava

Alberto Artasanchez

Imtiaz Sayed

View More author details

Table of Contents (19) Chapters

AWS for Solutions Architects, Second Edition: Design your cloud infrastructure by implementing DevOps, containers, and Amazon Web Services

1 Understanding AWS Principles and Key Characteristics FREE CHAPTER

2 Understanding AWS Well-Architected Framework and Getting Certified

3 Leveraging the Cloud for Digital Transformation

4 Networking in AWS

5 Storage in AWS – Choosing the Right Tool for the Job

6 Harnessing the Power of Cloud Computing

7 Selecting the Right Database Service

8 Best Practices for Application Security, Identity, and Compliance

9 Dive efficiency with Cloud Operation Automation and DevOps in AWS

10 Bigdata and streaming data processing in AWS

11 Datawarehouse, Data Query and Visualization in AWS

12 Machine Learning, IoT, and Blockchain in AWS

13 Containers in AWS

14 Microservice and Event-Driven Architectures

15 Domain-Driven Design

16 Data Lake Patterns – Integrating Your Data across the Enterprise

17 Availability, Reliability, and Scalability Patterns

18 AWS Hands-On Lab and Use Case

Putting it all together

Now that we have learned about all the major components in AWS Glue let's look at how all the pieces fit together. The following diagram illustrates this:

Figure 10.3 – AWS Glue typical workflow steps

In the preceding diagram, we see can the various steps that can take place when AWS Glue runs. The steps are explained in the following points:

The first step is for the crawlers to scan these sources and extract metadata from them.
This metadata can then be used to seed the AWS Glue Data Catalog.
This metadata can be used by other AWS services, such as Amazon Athena, Redshift Spectrum, and Amazon EMR. These services can be used to write queries against the ingested data using the metadata from the AWS Glue Data Catalog to build these queries.
Finally, the results of these queries can be used for visualizations in other AWS services, including Amazon QuickSight and Amazon SageMaker.

A wide variety of data sources can be ingested with AWS Glue...