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

Definition of a data lake

We have a tremendous amount of information available with just a few keystrokes (thank you, Google) or a simple voice command (thank you, Alexa).

The data that companies are generating is richer than ever before. The amount they are generating is growing at an exponential rate. Fortunately, the processing power needed to harness this data deluge is increasing and becoming cheaper. Cloud technologies such as AWS allow us to scale data almost instantaneously and in a massive fashion.

Data is everywhere today. It was always there, but it was too expensive to keep it. With the massive drops in storage costs, enterprises keep much of what they were throwing away before. And this is the problem. Many enterprises are collecting, ingesting, and purchasing vast amounts of data but are struggling to gain insights from it:

Many Fortune 500 companies are generating data faster than they can process it. The maxim data is that the new gold has a lot of truth, but just...