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

Summary


In this chapter, we discussed the Lambda pattern at a conceptual level as well as in detail. I walked through an example implementation with serverless technologies to calculate average cryptocurrency prices for different time slices. Our example application was fed by a simple script that receives data from the GDAX WebSocket API. This data producer script published data to a single AWS Kinesis stream, which, in turn, triggered a series of events, ultimately resulting in real-time updates to DynamoDB and triggering batch jobs to calculate historical views of the minute, hourly, and daily average prices for multiple cryptocurrencies.

I discussed when the Lambda pattern may be appropriate and the types of data for which it's well suited. We talked through various systems and services that one may leverage when building a lambda architecture using serverless technologies. I introduced AWS Kinesis and AWS Kinesis Firehose, which are streaming systems you may leverage for real-time applications...