Book Image

AWS for Solutions Architects

By : Alberto Artasanchez
3 (1)
Book Image

AWS for Solutions Architects

3 (1)
By: Alberto Artasanchez

Overview of this book

One of the most popular cloud platforms in the world, Amazon Web Services (AWS) offers hundreds of services with thousands of features to help you build scalable cloud solutions; however, it can be overwhelming to navigate the vast number of services and decide which ones best suit your requirements. Whether you are an application architect, enterprise architect, developer, or operations engineer, this book will take you through AWS architectural patterns and guide you in selecting the most appropriate services for your projects. AWS for Solutions Architects is a comprehensive guide that covers the essential concepts that you need to know for designing well-architected AWS solutions that solve the challenges organizations face daily. You'll get to grips with AWS architectural principles and patterns by implementing best practices and recommended techniques for real-world use cases. The book will show you how to enhance operational efficiency, security, reliability, performance, and cost-effectiveness using real-world examples. By the end of this AWS book, you'll have gained a clear understanding of how to design AWS architectures using the most appropriate services to meet your organization's technological and business requirements.
Table of Contents (20 chapters)
1
Section 1: Exploring AWS
4
Section 2: AWS Service Offerings and Use Cases
11
Section 3: Applying Architectural Patterns and Reference Architectures
17
Section 4: Hands-On Labs

Understanding how Amazon Athena works

Amazon Athena originally was intended to work with data stored in Amazon S3. As we will see in a later section in this chapter, it can now work with other source types as well.

This feature of Amazon Athena is a game-changer. You can now combine disparate data sources just as easily as if they all had the same format. This enables you to join a JSON file with a CSV file or a DynamoDB table with an Amazon Redshift table.

Previously, if you wanted to combine this data, it would require performing this combination programmatically, which would invariably translate into a long development cycle and more than likely not scale well when using large datasets.

Now all you have to do is write a SQL query that combines the two data sources. Due to the underlying technology used, this technique will scale well, even when querying terabytes' and petabytes' worth of data.

Data scientists and data analysts will be able to work at a speed...