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

Deploying the REST API


Now the fun part, we'll deploy our REST API using the Serverless Framework. At this point, we have not discussed the various configuration options when implementing serverless architectures on AWS. I'll cover different possibilities, and our particular configuration, later on in this chapter.

My pattern of using Docker as a build and deployment tool makes this process a bit easier. You are not required to do this, and there are likely other ways to make the process even simpler.

We will do all package building and deployment from inside a running Docker container, which I start and enter with the following Makefile target:

brianz@gold(master=)$ ENV=dev make shell

This equates to the following Docker command:

docker run --rm -it \
        -v `pwd`:/code \
        --env ENV=$(ENV) \
        --env-file envs/$2 \
        --name=coffee-cupping-$(ENV) \
        verypossible/serverless:1.20.0-python3 bash

There is nothing magical here. We're starting up a Docker container from...