Book Image

Serverless Design Patterns and Best Practices

By : Brian Zambrano
Book Image

Serverless Design Patterns and Best Practices

By: Brian Zambrano

Overview of this book

Serverless applications handle many problems that developers face when running systems and servers. The serverless pay-per-invocation model can also result in drastic cost savings, contributing to its popularity. While it's simple to create a basic serverless application, it's critical to structure your software correctly to ensure it continues to succeed as it grows. Serverless Design Patterns and Best Practices presents patterns that can be adapted to run in a serverless environment. You will learn how to develop applications that are scalable, fault tolerant, and well-tested. The book begins with an introduction to the different design pattern categories available for serverless applications. You will learn thetrade-offs between GraphQL and REST and how they fare regarding overall application design in a serverless ecosystem. The book will also show you how to migrate an existing API to a serverless backend using AWS API Gateway. You will learn how to build event-driven applications using queuing and streaming systems, such as AWS Simple Queuing Service (SQS) and AWS Kinesis. Patterns for data-intensive serverless application are also explained, including the lambda architecture and MapReduce. This book will equip you with the knowledge and skills you need to develop scalable and resilient serverless applications confidently.
Table of Contents (18 chapters)
Title Page
Copyright and Credits
Dedication
Packt Upsell
Contributors
Preface
Index

Exploring alternate implementations


While you may find great success implementing your serverless MapReduce system, there are alternatives that still fall under the serverless umbrella or leverage managed services, which should give you a high degree of confidence. I'll talk through some of the other systems or techniques you should consider when working on your own data analysis.

AWS Athena

AWS Athena is a relatively new service from AWS. Of course, this is specific to AWS, but other cloud providers may offer comparable services. Athena gives you the ability to write SQL queries to analyze data stored on S3. Before you can analyze your data with SQL, you must create a virtual database with associated tables across your structured or semi-structured S3 files. You may create these tables manually or with another AWS service called Glue.

I won't go into all of the details of setting up a new Athena database or tables but will show you the results and ease of use after you've set those up. In...