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

System architecture


Our system architecture, at a high level, will be the same as in the REST API version of our sample application. Requests from the web will hit the CloudFront CDN, which is backed by S3. Our JavaScript code from the served-up HTML files will query the serverless API, which itself will communicate with the RDS-backed data layer:

Thinking through this application from a top-down approach, the steps in fetching data will be the same regardless of how the logic layer is implemented:

  • End-user requests a website
  • Static assets are served to the user from CloudFront and S3
  • Static assets request data via logic layer/web APIs (GraphQL in this case)
  • Logic layer fetches/writes data from/to Postgres database in the data layer

Moving our example web application from a REST design to GraphQL means focusing on the logic layer, as the presentation and data layers won't change much, if at all. Of course, any changes to our API mean that our presentation layer (that is, the client) will need...