Serverless architectures are changing the way software systems are being built and operated. When compared with systems that use physical servers or virtual machines, many tools, techniques, and patterns remain the same; however, there are several things that can or need to change drastically. To fully capitalize on the benefits of serverless systems, tools, patterns, and best practices should be thought through carefully before embarking on a serverless journey.
This book introduces and describes reusable patterns applicable to almost any type of serverless application, whether it be web systems, data processing, big data, or Internet of Things. You will learn, by example and explanation, about various patterns within a serverless context, such as RESTful APIs, GraphQL, proxy, fan-out, messaging, lambda architecture, and MapReduce, as well as when to use these patterns to make your applications scalable, performant, and fault tolerant. This book will take you through techniques for Continuous Integration and Continuous Deployment as well as designs for testing, securing, and scaling your serverless applications. Learning and applying these patterns will speed up your development lifecycle, while also improving the overall application architecture when building on top of your serverless platform of choice.
This book is aimed at software engineers, architects, and anyone who is interested in building serverless applications using a cloud provider. Readers should be interested in learning popular patterns to improve agility, code quality, and performance, while also avoiding some of the pitfalls that new users may fall into when starting with serverless systems. Programming knowledge and basic serverless computing concepts are assumed.
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.
Almost all of the examples in this book use the Serverless Framework to manage AWS resources and Lambda functions. Installation instructions for the Serverless Framework can be found at https://serverless.com/framework/docs/getting-started/.
In addition to the Serverless Framework, readers will need to have an AWS account to run the examples. For those new to AWS, you can create a new account, which comes with a year of usage in their Free Tier, at https://aws.amazon.com.
During the course of this book, you will need the following tools:
- AWS Lambda
- AWS RDS
- AWS API Gateway
- AWS DynamoDB
- AWS S3
- AWS SQS
- AWS Rekognition
- AWS Kinesis
- AWS SNS
We will learn how to use these tools through the course of this book.
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There are a number of text conventions used throughout this book.
CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "To test this, we need to set the timeout of the divide function to 4 seconds and put a time.sleep(3) in the middle of the application code."
A block of code is set as follows:
def divide(event, context):
params = event.get('queryStringParameters') or {}
numerator = int(params.get('numerator', 10))
denominator = int(params.get('denominator', 2))
body = {
"message": "Results of %s / %s = %s" % (
numerator,
denominator,
numerator // denominator,
)
}
response = {
"statusCode": 200,
"body": json.dumps(body)
}
return responseWhen we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:
from raven_python_lambda import RavenLambdaWrapper @RavenLambdaWrapper()
from raven_python_lambda import RavenLambdaWrapper
@RavenLambdaWrapper()
def divide(event, context):
# CodeAny command-line input or output is written as follows:
$ curl "https://5gj9zthyv1.execute-api.us-west-2.amazonaws.com/dev?numerator=12&denominator=3" {"message": "Results of 12 / 3 = 4"}
Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: "The following screenshot showsInvocation errorsfrom the AWS Lambda monitoring page for the divide function:"
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