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- Herausgeber: Packt Publishing
- Kategorie: Fachliteratur
- Sprache: Englisch
Serverless architecture is popular in the tech community due to AWS Lambda. Go is simple to learn, straightforward to work with, and easy to read for other developers; and now it's been heralded as a supported language for AWS Lambda. This book is your optimal guide to designing a Go serverless application and deploying it to Lambda.
This book starts with a quick introduction to the world of serverless architecture and its benefits, and then delves into AWS Lambda using practical examples. You'll then learn how to design and build a production-ready application in Go using AWS serverless services with zero upfront infrastructure investment. The book will help you learn how to scale up serverless applications and handle distributed serverless systems in production. You will also learn how to log and test your application.
Along the way, you'll also discover how to set up a CI/CD pipeline to automate the deployment process of your Lambda functions. Moreover, you'll learn how to troubleshoot and monitor your apps in near real-time with services such as AWS CloudWatch and X-ray. This book will also teach you how to secure the access with AWS Cognito.
By the end of this book, you will have mastered designing, building, and deploying a Go serverless application.
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Seitenzahl: 239
Veröffentlichungsjahr: 2018
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Hands-On Serverless Applications with Go
Copyright © 2018 Packt Publishing
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First published: August 2018
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ISBN 978-1-78913-461-2
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Contributors
About the author
Mohamed Labouardyis a software engineer/DevOps engineer and AWS Solution Architect. He is also a certified Scrum Master.
He is interested in serverless architecture, containers, distributed systems, Go, chaos engineering, and machine learning. He is a contributor to numerous open source projects such as DialogFlow, Jenkins, Docker, Nexus, and Telegraf. He has authored some open source projects related to DevOps as well.
He currently works at Foxintelligence as a lead DevOps engineer. He is also a technical content writer at several platforms and is a regular speaker at multiple international events and conferences, such as Nexus User Conference and AllDayDevOps.
You can find him on Twitter at@mlabouardy.
I would like to thank everyone at Packt Publishing who has contributed to the realization of this book. I would also like to thank all my friends for their support and motivation. Special thanks to Rania Zyane for encouraging me to embrace this opportunity. Finally, I want to thank my parents for their love, good advice, and continuous support.
About the reviewers
Arpit Aggarwal is a programmer with over 7 years of industry experience in software analysis, design, effort estimation, development, troubleshooting, testing, and supporting web applications. He is among the top contributors of StackOverflow with more than 9,000 reputation and more than 100 badges in multiple areas such as Java, Scala, Go, Spring, Spring-MVC, GiT, Angular, Unit Testing, Web Services, and Docker, and has written many technical articles for Java Code Geeks, System Code Geeks, Web Code Geeks, and DZone.
Radomír Sohlichreceived the master's degree in Applied Informatics from Faculty of Applied Informatics at Tomas Bata University in Zlín. After that, he got a job in a start-up company as a software developer and worked on various projects, usually based on the Java platform. Currently, he continues a software developer career as a contractor for a large international company.
In 2015, he fell in love with Go and kept exploring the endless power and possibilities of the language. He is passionate about learning new approaches and technology and feels the same about sharing the knowledge with others.
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Table of Contents
Title Page
Copyright and Credits
Hands-On Serverless Applications with Go
Packt Upsell
Why subscribe?
PacktPub.com
Contributors
About the author
About the reviewers
Packt is searching for authors like you
Preface
Who this book is for
What this book covers
To get the most out of this book
Download the example code files
Download the color images
Conventions used
Get in touch
Reviews
Go Serverless
The serverless paradigm
The cloud-computing evolution
Infrastructure as a Service
Platform as a Service
Container as a Service
Function as a Service
Serverless architecture
Benefits of going serverless
Drawbacks of going serverless
Serverless cloud providers
AWS Lambda
Source events
Use cases
Go serverless
Summary
Questions
Getting Started with AWS Lambda
Technical requirements
Setting up the AWS environment
The AWS command line
Installing the AWS CLI
AWS Management Console
Configuration
Testing
Setting up the Go environment
The runtime environment
The development environment
Summary
Questions
Developing a Serverless Function with Lambda
Technical requirements
Writing a Lambda function in Go
Execution role
Deployment package
Uploading a ZIP file
Uploading from Amazon S3
Event testing
Summary
Questions
Setting up API Endpoints with API Gateway
Technical requirements
Getting started with API Gateway
Setting up an API endpoint
Debugging and troubleshooting
Invoking the function with an HTTP request
Building a RESTful API
API architecture
Endpoints design
The GET method
The GET method with parameters
The POST method
Summary
Managing Data Persistence with DynamoDB
Technical requirements
Setting up DynamoDB
Creating a table
Loading sample data
Working with DynamoDB
Scan request
GetItem request
PutItem request
DeleteItem request
Summary
Questions
Deploying Your Serverless Application
Lambda CLI commands
The list-functions command
The create-function command
The update-function-code command
The get-function-configuration command
The invoke command
The delete-function command
Versions and aliases
Versioning
FindAllMovies v1.0.0
FindAllMovies v1.1.0
Semantic Versioning
Aliases
Stage variables
Summary
Implementing a CI/CD Pipeline
Technical requirements
Continuous Integration and deployment workflow
Continuous Integration
Continuous Deployment
Continuous Delivery
Automating the deployment of Lambda functions
Continuous Deployment with CodePipeline and CodeBuild
Source provider
Build provider
Deploy provider
Continuous Pipeline with Jenkins
Distributed builds
Setting up a Jenkins job
Git Hooks
Continuous Integration with Circle CI
Identity and access management
Configuring the CI Pipeline
Summary
Questions
Scaling Up Your Application
Technical requirements
Load testing and scaling
Lambda autoscaling
Downstream resources
Private Lambda functions
Concurrent execution
Lambda throttling
Concurrency reservation
Summary
Building the Frontend with S3
Technical requirements
Single Page Application
Developing web applications with Angular
Generating your first Angular component
Accessing Rest web services with Angular
Cross Origin Resource Sharing
S3 static website hosting
Setting up an S3 bucket
Setting up Route 53
Certificate Manager
CloudFront distribution
CI/CD workflow
API documentation
Summary
Questions
Testing Your Serverless Application
Technical requirements
Unit testing
Automated unit tests
Integration testing
RPC communications
Serverless Application Model
Load testing
Summary
Questions
Monitoring and Troubleshooting
Monitoring and debugging with AWS CloudWatch
CloudWatch metrics
CloudWatch alarms
CloudWatch logs
Tracing with AWS X-Ray
Summary
Securing Your Serverless Application
Technical requirements
Authentication and user control access
Securing API access
User management with AWS Cognito
Setting up a test user via the AWS Management Console
Setup using Cognito Golang SDK
Encrypted environment variables
Data encryption at rest
Data encryption in transit
Logging AWS Lambda API calls with CloudTrail
Vulnerability scanning for your dependencies
Summary
Questions
Designing Cost-Effective Applications
Lambda pricing model
Lambda cost calculator
Optimal memory size
Code optimization
Lambda cost and memory tracking
Summary
Infrastructure as Code
Technical requirements
Deploying AWS Lambda with Terraform
Creating the Lambda function
Setting up DynamoDB table
Configuring API Gateway
Cleaning up
Deploying AWS Lambda with CloudFormation
CloudFormation designer
Deploying AWS Lambda with SAM
Exporting a serverless application
Summary
Questions
Assessments
Chapter 1: Go Serverless
Chapter 2: Getting Started with AWS Lambda
Chapter 3: Developing a Serverless Function with Lambda
Chapter 5: Managing Data Persistence with DynamoDB
Chapter 7: Implementing a CI/CD Pipeline
Chapter 9: Building the Frontend with S3
Chapter 10: Testing Your Serverless Application
Chapter 12: Securing Your Serverless Application
Chapter 14:
Other Books You May Enjoy
Leave a review - let other readers know what you think
Preface
Serverless architecture is popular in the tech community due to AWS Lambda. Go is simple to learn, straightforward to work with, and easy to read for other developers, and now it's been heralded as a supported language for AWS Lambda. This book is your optimal guide to designing a serverless Go application and deploying it to Lambda. This book starts with a quick introduction to the world of serverless architecture and its benefits, then delves into AWS Lambda through practical examples. You'll then learn how to design and build a production-ready application in Go using AWS serverless services with zero upfront infrastructure investment. The book will help you learn how to scale up serverless applications and handle distributed serverless systems in production. Then you will also learn to log and test your application. Along the way, you'll also discover how to set up a CI/CD pipeline to automate the deployment process of your Lambda functions. Moreover, you will learn to troubleshoot and monitor your applications in near real time with services such as AWS CloudWatch and X-Ray. The book will also teach you how to scale up serverless applications and secure the access with AWS Cognito. By the end of this book, you will have mastered designing, building, and deploying Go-based Lambda applications to production.
Who this book is for
This book is for Gophers who would like to learn about serverless architectures. Go programming knowledge is assumed. DevOps and solution architects who are interested in building serverless applications in Go will also benefit from this book.
What this book covers
Chapter 1, Go Serverless, gives a foundational explanation of what serverless is, how it works, whats its features are, why AWS Lambda pioneered serverless compute offerings, and why you should use Go for building serverless applications.
Chapter 2, Getting Started with AWS Lambda, supplies guidelines for setting up an AWS environment alongside the Go runtime and development environment.
Chapter 3, Developing a Serverless Function with Lambda, describes how to write your first Go-based Lambda function from scratch and how to invoke it manually from the console.
Chapter 4, Setting Up API Endpoints with API Gateway, illustrates how to trigger your Lambda function in response to incoming HTTP requests with API Gateway and build a unified event-driven RESTful API backed with serverless functions.
Chapter 5, Managing Data Persistence with DynamoDB, shows how to resolve Lambda functions stateless issue by using a DynamoDB datastore to manage data.
Chapter 6, Deploying Your Serverless Application, presents advanced AWS CLI commands and options that you can use while building serverless functions in AWS Lambda to save time. It also shows how to create and maintain multiple versions and releases of Lambda functions.
Chapter 7, Implementing a CI/CD Pipeline, shows how to set up a Continuous Integration and Continuous Deployment pipeline to automate the deployment process of Lambda functions from end to end.
Chapter 8, Scaling Up Your Application, covers how autoscaling works, how Lambda can handle traffic demands during peak service usage with no capacity planning or scheduled scaling, and how you can throttle and limit the number of executions using concurrency reservation.
Chapter 9, Building the Frontend with S3, illustrates how to build a single-page application with a REST backend backed by serverless functions.
Chapter 10, Testing Your Serverless Application, shows how test the serverless application locally using the AWS Serverless Application Model. It also covers Go unit testing and performance testing with third-party tools and shows how Lambda can be used to perform test harness.
Chapter 11,Monitoring and Troubleshooting, goes a step further in order to show you how to set up function-level monitoring with CloudWatch and how to debug and troubleshoot Lambda functions with AWS X-Ray to profile the application for abnormal behavior detection.
Chapter 12,Securing Your Serverless Application, is dedicated to the best practices and recommendations to follow in AWS Lambda to make your application resilient and secure according to the AWS Well-Architected Framework.
Chapter 13,Designing Cost-Effective Applications, covers also some tips for optimizing and reducing your serverless application billing and how to track the Lambda cost and usage with real-time alerts, before this becomes an issue.
Chapter 14,Infrastructure as Code, introduces tools such as Terraform and SAM to help you design and deploy your N-Tier serverless application in automated way, in order to avoid human errors and repeatable tasks.
To get the most out of this book
This book is written for anyone who work under Linux, Mac OS X, or Windows. You will need Go installed and an AWS account. You will also need Git in order to clone the repository with the source code provided with this book. Similarly, you are expected to have a basic knowledge of Go, the Bash command line, and some web programming skills. All prerequisites are described in the Chapter 2, Getting Started with AWS Lambda, with instructions to make sure you can follow this book with ease.
Last, keep in mind that this book is not intended to replace online resources, but rather aims to complement them. So you will obviously need internet access to complete your reading experience at some points, through provided links.
Download the example code files
You can download the example code files for this book from your account at www.packtpub.com. If you purchased this book elsewhere, you can visit www.packtpub.com/support and register to have the files emailed directly to you.
You can download the code files by following these steps:
Log in or register at
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Select the
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Click on
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Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:
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The code bundle for the book is also hosted on GitHub athttps://github.com/PacktPublishing/Hands-On-Serverless-Applications-with-Go. In case there's an update to the code, it will be updated on the existing GitHub repository.
We also have other code bundles from our rich catalog of books and videos available athttps://github.com/PacktPublishing/. Check them out!
Download the color images
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: http://www.packtpub.com/sites/default/files/downloads/HandsOnServerlessApplicationswithGo_ColorImages.pdf.
Conventions used
In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.
Code words in text are shown as follows: "Within the workspace, create a main.go file using vim with the following content."
A block of code is set as follows:
package mainimport "fmt"func main(){ fmt.Println("Welcome to 'Hands-On serverless Applications with Go'")}
Any command-line input or output is written as follows:
pip install awscli
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: "On the Source page, select GitHub as the source provider."
Get in touch
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General feedback: Email [email protected] and mention the book title in the subject of your message. If you have questions about any aspect of this book, please email us at [email protected].
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Go Serverless
This chapter will give you a foundational understanding of what serverless architecture is, how it works, and what its features are. You'll learn how AWS Lambda is on a par with big players such as Google Cloud Functions and Microsoft Azure Functions. Then, you will discover AWS Lambda's different execution environments and its Go support. Moreover, we'll discuss the advantages of using Go as your programming language for building serverless applications.
The following topics will be covered in this chapter:
Cloud-computing models—u
nderstanding what they are and what they can be used for.
Pros and cons of serverless architecture.
Why Go is a great fit for AWS Lambda.
The serverless paradigm
Cloud-based applications can be built on low-level infrastructure pieces or can use higher-level services that provide abstraction from the management, architecting, and scaling requirements of core infrastructure. In the following section, you will learn about the different cloud-computing models.
The cloud-computing evolution
Cloud providers offer their services according to four main models: IaaS, PaaS, CaaS, and FaaS. All the aforementioned models are just thousands of servers, disks, routers, and cables under the hood. They just add layers of abstraction on top to make management easier and increase the development velocity.
Infrastructure as a Service
Infrastructure as a Service (IaaS), sometimes abbreviated to IaaS, is the basic cloud-consumption model. It exposes an API built on top of a virtualized platform to access compute, storage, and network resources. It allows customers to scale out their application infinitely (no capacity planning).
In this model, the cloud provider abstracts the hardware and physical servers, and the cloud user is responsible for managing and maintaining the guest operating systems and applications on top of it.
AWS is the leader according to Gartner's Infrastructure as a Service Magic Quadrant. Irrespective of whether you're looking for content delivery, compute power, storage, or other service functionality, AWS is the most advantageous of the various available options when it comes to the IaaS cloud-computing model. It dominates the public cloud market, while Microsoft Azure is gradually catching up with to Amazon, followed by Google Cloud Platform and IBM Cloud.
Platform as a Service
Platform as a Service (PaaS) provides developers with a framework in which they can develop applications. It simplifies, speeds up, and lowers the costs associated with the process of developing, testing, and deploying applications while hiding all implementation details, such as server management, load balancers, and database configurations.
PaaS is built on top of IaaS and thus hides the underlying infrastructure and operating systems, to allow developers to focus on delivering business values and reduce operational overhead.
Among the first to launch PaaS was Heroku, in 2007; later, Google App Engine and AWS Elastic Beanstalk joined the fray.
Container as a Service
Container as a Service (CaaS) became popular with the release of Docker in 2013. It made it easy to build and deploy containerized applications on on-premise data centers or over the cloud.
Containers changed the unit of scale for DevOps and site reliability engineers. Instead of one dedicated VM per application, multiple containers can run on a single virtual machine, which allows better server utilization and reduces costs. Also, it brings developer and operation teams closer together by eliminating the "worked on my machine" joke. This transition to containers has allowed multiple companies to modernize their legacy applications and move them to cloud.
To achieve fault-tolerance, high-availability, and scalability, an orchestrations tool, such as Docker Swarm, Kubernetes, or Apache Mesos, was needed to manage containers in a cluster of nodes. As a result, CaaS was introduced to build, ship, and run containers quickly and efficiently. It also handles heavy tasks, such as cluster management, scaling, blue/green deployment, canary updates, and rollbacks.
The most popular CaaS platform in the market today is AWS as 57% of the Kubernetes workload is running on Amazon Elastic Container Service (ECS), Elastic Kubernetes Service (EKS), and AWS Fargate, followed by Docker Cloud, CloudFoundry, and Google Container Engine.
This model, CaaS, enables you to split your virtual machines further to achieve higher utilization and orchestrate containers across a cluster of machines, but the cloud user still needs to manage the life cycle of containers; as a solution to this, Function as a Service (FaaS) was introduced.
Function as a Service
The FaaS model allows developers to run code (called functions) without provisioning or maintaining a complex infrastructure. Cloud Providers deploy customer code to fully-managed, ephemeral, time-boxed containers that are live only during the invocation of the functions. Therefore, business can grow without customers having to worry about scaling or maintaining a complex infrastructure; this is called going serverless.
Amazon kicked off the serverless revolution with AWS Lambda in 2014, followed by Microsoft Azure Functions and Google Cloud Functions.
Serverless architecture
Serverless computing, or FaaS, is the fourth way to consume cloud computing. In this model, the responsibility for provisioning, maintaining, and patching servers is shifted from the customer to cloud providers. Developers can now focus on building new features and innovating, and pay only for the compute time that they consume.
Benefits of going serverless
There are a number of reasons why going serverless makes sense:
NoOps
: The server infrastructure is managed by the cloud provider, and this reduces the overhead and increases developer velocity. OS updates are taken care of and patching is done by the FaaS provider. This results in d
ecreased time to market and faster software releases,
and eliminates the need for a system administrator.
Autoscaling and high-availability
:
Function as a unit of scale leads to small, loosely-coupled, and stateless components that, in the long run, lead to scalable applications. It is up to the service provider to decide how to use its infrastructure effectively to serve requests from the customers and horizontally scale functions-based on the load.
Cost-optimization
: You pay only for the compute time and resources (RAM, CPU, network, or invocation time) that you consume. You don't pay for idle resources. No work indicates no cost. If t
he billing period on
a Lambda function
, for example, is 100 milliseconds, then it could significantly reduce costs.
Polygot
: One benefit that the serverless approach brings to the table is that, as a programmer, you can choose between different language runtimes depending on your use case. On
e part of the application can be written in Java, another in Go, another in Python; it doesn't really matter as long as it gets the job done.
Drawbacks of going serverless
On the other hand, serverless computing is still in its infancy; hence, it is not suitable for all use cases and it does have its limitations:
Transparency
: The infrastructure is managed by the FaaS provider. This is in exchange for flexibility; you don't have full control of your application, you cannot access the underlying infrastructure, and you cannot switch between platform providers (vendor lock-in). In future, we expect increasing work toward the unification of FaaS; this will help avoid vendor lock-in and allow us to run serverless applications on different cloud providers or even on-premise.
Debugging
: Monitoring and debugging tools were built without serverless architecture in mind. Therefore, serverless functions are hard to debug and monitor. In addition, it's difficult to set up a local environment to test your functions before deployment (pre-integration testing)
.
The good news is that tools will eventually arrive to improve observability in serverless environments, as serverless popularity is rising and multiple open source projects and frameworks have been created by the community and cloud providers (AWS X-Ray, Datadog, Dashbird, and Komiser).
Cold starts
: It takes some time to handle a first request by your function as the cloud provider needs to allocate proper resources (AWS Lambda needs to start a container) for your tasks. To avoid this situation, your function must remain in an active state.
Stateless
:
Functions need to be stateless to provide the provisioning that enables serverless applications to be transparently scalable. Therefore, to persist data or manage sessions, you need to use an external database, such as DynamoDB or RDS, or an in-memory cache engine, such as Redis or Memcached.
Having stated all these limitations, these aspects will change in the future with an increasing number of vendors coming up with upgraded versions of their platforms.
Serverless cloud providers
There are multiple FaaS providers out there, but to keep it simple we'll compare only the biggest three:
AWS Lambda
Google Cloud Functions
Microsoft Azure Functions
The following is a pictorial comparison:
As shown in the preceding diagram, AWS Lambda is the most used, best-known, and the most mature solution in the serverless space today, and that's why upcoming chapters will be fully dedicated to AWS Lambda.
AWS Lambda
AWS Lambda is the center of the AWS serverless platform:
AWS Lambda was launched at re:Invent 2014. It was the first implementation of serverless computing where users could upload their code to Lambda. It performs operational and administrative activities on their behalf, including provisioning capacity, monitoring fleet health, applying security patches, deploying their code, and publishing realtime logs and metrics to Amazon CloudWatch.
