▶Book Description
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 the trade-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.
▶What You Will Learn
⦁ Comprehend the popular design patterns currently being used with serverless architectures
⦁ Understand the various design options and corresponding implementations for serverless web application APIs
⦁ Learn multiple patterns for data-intensive serverless systems and pipelines, including MapReduce and Lambda Architecture
⦁ Learn how to leverage hosted databases, queues, streams, storage services, and notification services
⦁ Understand error handling and system monitoring in a serverless architecture a serverless architecture
⦁ Learn how to set up a serverless application for continuous integration, continuous delivery, and continuous deployment
▶Key Features
⦁ Learn the details of popular software patterns and how they are applied to serverless applications
⦁ Understand key concepts and components in serverless designs
⦁ Walk away with a thorough understanding of architecting serverless applications
▶Who This Book Is For
If you're a software architect, engineer, or someone who wants to build serverless applications, which are non-trivial in complexity and scope, then this book is for you. Basic knowledge of programming and serverless computing concepts are assumed.
▶What this book covers
⦁ Chapter 1, Introduction, covers the basics of serverless systems and discusses when serverless architectures may or may not be a good fit. Three categories of serverless patterns are introduced and briefly explained.
⦁ Chapter 2, A Three-Tier Web Application Using REST, walks you through a full example of building a traditional web application using a REST API powered by AWS Lambda, along with serverless technologies for hosting HTML, CSS, and JavaScript for the frontend code.
⦁ Chapter 3, A Three-Tier Web Application Pattern with GraphQL, introduces GraphQL and explains the changes needed to turn the previous REST API into a GraphQL API.
⦁ Chapter 4, Integrating Legacy APIs with the Proxy Pattern, demonstrates how it's possible to completely change an API contract while using a legacy API backend using nothing other than AWS API Gateway.
⦁ Chapter 5, Scaling Out with the Fan-Out Pattern, teaches you one of the most basic serverless patterns around, where a single event triggers multiple parallel serverless functions, resulting in quicker execution times over a serial implementation.
⦁ Chapter 6, Asynchronous Processing with the Messaging Pattern, explains different classes of messaging patterns and demonstrates how to put messages onto a queue using a serverless data producer, and process those messages downstream with a serverless data consumer.
⦁ Chapter 7, Data Processing Using the Lambda Pattern, explains how you can use multiple subpatterns to create two planes of computation, which provide views into historical aggregated data as well as real-time data.
⦁ Chapter 8, The MapReduce Pattern, explores an example implementation of aggregating large volumes of data in parallel, similar to the way systems such as Hadoop work.
⦁ Chapter 9, Deployment and CI/CD Patterns, explain how to set up Continuous Integration and Continuous Delivery for serverless projects and what to keep in mind when doing so, in addition to showing examples of continuous deployment.
⦁ Chapter 10, Error Handling and Best Practices, reviews the tools and techniques for automatically tracking unexpected errors as well as several best practices and tips when creating serverless applications.
