Book Image

AWS for Solutions Architects - Second Edition

By : Saurabh Shrivastava, Neelanjali Srivastav, Alberto Artasanchez, Imtiaz Sayed
4 (2)
Book Image

AWS for Solutions Architects - Second Edition

4 (2)
By: Saurabh Shrivastava, Neelanjali Srivastav, Alberto Artasanchez, Imtiaz Sayed

Overview of this book

Are you excited to harness the power of AWS and unlock endless possibilities for your business? Look no further than the second edition of AWS for Solutions Architects! Imagine crafting cloud solutions that are secure, scalable, and optimized – not just good, but industry-leading. This updated guide throws open the doors to the AWS Well-Architected Framework, design pillars, and cloud-native design patterns empowering you to craft secure, performant, and cost-effective cloud architectures. Tame the complexities of networking, conquering edge deployments and crafting seamless hybrid cloud connections. Uncover the secrets of big data and streaming with EMR, Glue, Kinesis, and MSK, extracting valuable insights from data at speeds you never thought possible. Future-proof your cloud with game-changing insights! New chapters unveil CloudOps, machine learning, IoT, and blockchain, empowering you to build transformative solutions. Plus, unlock the secrets of storage mastery, container excellence, and data lake patterns. From simple configurations to sophisticated architectures, this guide equips you with the knowledge to solve any cloud challenge and impress even the most demanding clients. This book is your one-stop shop for architecting industry-standard AWS solutions. Stop settling for average – dive in and build like a pro!
Table of Contents (19 chapters)
17
Other Books You May Enjoy
18
Index

Putting AWS analytic services together

In the previous chapter, Chapter 10, Big Data and Streaming Data Processing in AWS, you learned about AWS ETL services such as EMR and Glue. In this chapter, let’s combine that with learning how to build a data processing pipeline. The following diagram shows a data processing and analytics architecture in AWS that applies various analytics services to build an end-to-end solution:

Figure 11.6: Data analytic architecture in AWS

As shown in the preceding diagram, data is ingested from various sources such as operational systems, marketing, and other systems in S3. You want to ingest data fast without losing it, so this data is collected in a raw format first. You can clean, process, and transform this data using an ETL platform such as EMR or Glue. Using the Apache Spark framework and writing data processing code from scratch is recommended when using Glue; otherwise, you can use EMR if you have Hadoop skill sets in your team...