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

Setting up unit tests


As I mentioned in the prior section, there are a few tricks and tips in setting up unit tests with a serverless system. The most important thing you can do is completely isolate your application code from the fact that it is running in a serverless context or within a given cloud provider. This strategy will lend other significant benefits other than making our tests easier to run, and I'll discuss those advantages in the course of this discussion on testing.

Code organization

What does our code layout look like when we attempt to isolate application code from cloud provider-specific code? Let's take a look at the following diagram that shows the high-level structure of our REST or GraphQL API from Chapter 2, A Three-Tier Web Application Using REST, and Chapter 3, A Three-Tier Web Application Pattern with GraphQL, respectively:

Our example application was authored in Python, but this diagram shows how this general code organization can work for Node, Python, or any other...