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

Data layer


It's safe to say that most web applications today have some data store, whether it's a relational database (PostgreSQL, MySQL, SQLServer, and so on), a non-relational database (MongoDB, Redis, Cassandra, and so on), or even static file storage (S3, OS filesystem, and so on).

AWS RDS service will manage aPostgreSQL database for our coffee cupping application. RDS offers different RDBMS choices, most notably PostgreSQL, MySQL, Oracle, and SQLServer. There are other choices, and I encourage you to take a look at the various offerings. For this exercise, we'll be using a standard PostgreSQL database hosted on RDS. Many configuration options come with RDS, which we won't cover. Just know that it's possible and quite simple to run, configure, and manage a high-availability RDBMS instance using RDS. Other PaaS providers offer similar services for relational databases.