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

Lambda serverless architecture


While the overall design and theme of a lambda architecture remain the same as a traditional system, there are variations and adaptations that we need to make. Perhaps more importantly, there are many different ways to implement this pattern using serverless systems or, at the very least, managed services.

Streaming data producers

Any system must start with data to process. On serverless platforms, there are multiple choices for streaming systems. Azure, Google Compute, and AWS all offer some form of streaming systems. I mentioned these in Chapter 6Asynchronous Processing with the Messaging Pattern, when discussing the differences between queues and streams:

  • Azure: Event Hubs
  • AWS: Kinesis
  • Google Compute Cloud: Cloud Dataflow

It's worth briefly touching on the topic of queues versus streams again. As mentioned in Chapter 6Asynchronous Processing with the Messaging Pattern, one of the main differentiators is that queues are primarily designed for once-only processing...