Serverless Design Patterns and Best Practices电子书

Title Page

Copyright and Credits

Serverless Design Patterns and Best Practices

Dedication

Packt Upsell

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Contributors

About the author

About the reviewer

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Preface

Who this book is for

What this book covers

To get the most out of this book

Download the example code files

Conventions used

Get in touch

Reviews

Introduction

What is serverless computing?

No servers to manage

Pay-per-invocation billing model

Ability to automatically scale with usage

Built-in availability and fault tolerance

Design patterns

When to use serverless

The sweet spot

Classes of serverless pattern

Three-tier web application patterns

ETL patterns

Big data patterns

Automation and deployment patterns

Serverless frameworks

Summary

A Three-Tier Web Application Using REST

Serverless tooling

System architecture

Presentation layer

Logic layer

Data layer

Logic layer

Application code and function layout

Organization of the Lambda functions

Organization of the application code

Configuration with environment variables

Code structure

Function layout

Presentation layer

File storage with S3

CDN with CloudFront

Data layer

Writing our logic layer

Application entrypoint

Application logic

Wiring handler.py to Lambda via API Gateway

Deploying the REST API

Deploying the Postgres database

Setting up static assets

Viewing the deployed web application

Running tests

Iteration and deployment

Deploying the entire stack

Deploying the application code

Summary

A Three-Tier Web Application Pattern with GraphQL

Introduction to GraphQL

System architecture

Logic layer

Organization of the Lambda functions

Organization of the application code

Function layout

Presentation layer

Writing the logic layer

Implementing the entry point

Implementing GraphQL queries

Implementing GraphQL mutations

Deployment

Viewing the deployed application

Iteration and deployment

Summary

Integrating Legacy APIs with the Proxy Pattern

AWS API Gateway introduction

Simple proxy to a legacy API

Setting up a pass-through proxy

Deploying a pass-through proxy

Transforming responses from a modern API

Method execution flow

Setting up example

Setting up a new resource and method

Setting up Integration Request

Setting up Integration Response

Complex integration using a Lambda function

Implementing the application code

Setting up a new resource and method

Migration techniques

Staged migration

Migrating URLs

Summary

Scaling Out with the Fan-Out Pattern

System architecture

Synchronous versus asynchronous invocation

Resizing images in parallel

Setting up the project

Setting up trigger and worker functions

Setting up permissions

Implementing the application code

Testing our code

Alternate Implementations

Using notifications with subscriptions

Using notifications with queues

Summary

Asynchronous Processing with the Messaging Pattern

Basics of queuing systems

Choosing a queue service

Queues versus streams

Asynchronous processing of Twitter streams

System architecture

Data producer

Mimicking daemon processes with serverless functions

Data consumers

Viewing results

Alternate Implementations

Using the Fan-out and Messaging Patterns together

Using a queue as a rate-limiter

Using a dead-letter queue

Summary

Data Processing Using the Lambda Pattern

Introducing the lambda architecture

Batch layer

Speed layer

Lambda serverless architecture

Streaming data producers

Data storage

Computation in the speed layer

Computation in the batch layer

Processing cryptocurrency prices using lambda architecture

System architecture

Data producer

Speed layer

Batch layer

AWS resources

Data producer

Speed layer

Batch layer

Results

Summary

The MapReduce Pattern

Introduction to MapReduce

MapReduce example

Role of the mapper

Role of the reducer

MapReduce architecture

MapReduce serverless architecture

Processing Enron emails with serverless MapReduce

Driver function

Mapper implementation

Reducer implementation

Understanding the limitations of serverless MapReduce

Memory limits

Storage limits

Time limits

Exploring alternate implementations

AWS Athena

Using a data store for results

Using Elastic MapReduce

Summary

Deployment and CI/CD Patterns

Introduction to CI/CD

CI

CD

Setting up unit tests

Code organization

Setting up unit tests

Setting up CI with CircleCI

Configuring CircleCI builds

Setting up environment variables

Setting up CD and deployments with CircleCI

Setting up Slack notifications

Setting up a CircleCI badge

Setting up deployments

Setting up AWS credentials

Setting up environment variables

Executing deployments

Summary

Error Handling and Best Practices

Error tracking

Integrating Sentry for error tracking

Integrating Rollbar

Logging

Structuring log messages

Digesting structured logs

Cold starts

Keeping cloud functions warm

AWS Lambda functions and VPCs

Start-up times for different languages

Allocating more memory

Local development and testing

Local development

Learning about testing locally

Managing different environments

Securing sensitive configuration

Encrypting variables

Decrypting variables

Trimming AWS Lambda versions

Summary

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