The Serverless Framework (previously known as JAWS) debuted several months ago and has been rapidly maturing to help engineers build scalable applications without the hassle of maintaining servers.
The Framework relies exclusively on Amazon Web Services’ Lambda technology to run your code in the cloud. Lambda is unique in that it containerizes your code and auto-scales those containers for you, with zero administration required from developers. For clarity, “serverless” means the developer does not have to think about servers, even though they exist. AWS handles them. Plus, Lambda only charges you when your code is run, which is an attractive pricing model.
Overall, Lambda is possibly the most efficient resource available in the cloud for running applications. Myself and the full-time team behind the Serverless Framework believe AWS Lambda will be the focal point of the AWS cloud in the future, so we’ve designed the Framework to interpret AWS from the perspective of Lambda.
The Framework seeks to build on Lambda’s benefits and offer a familiar development experience despite Lambda’s nuances. Structure, best practices, optimization, and automation are built in. Further, the Framework allows you to decide how to containerize your logic. You can fit an entire microservice into Lambda or take a nanoservices approach and isolate the logic for each REST API endpoint in its own Lambda function. The result is unprecedented agility.
Now, let’s get a REST API up and running quickly with the Serverless Framework by using a starter/boilerplate project called the Serverless Starter.
The Serverless Framework is one of the first application frameworks that manages both your application code as well as your infrastructure. First, you will need to give it Access Keys for your AWS account.
- Log in or sign up for a new AWS account.
- Navigate to the Identity & Access Management (IAM) service and create a new User called
- Copy the Security Credentials in a safe place (i.e., Access Key ID and the Secret Access Key).
- Assign the “AdministratorAccess” policy to this User. (Later, you can reduce the permissions this IAM User has for security reasons.
Next, make sure you have Node.js v4 or greater installed and then install the Serverless Framework via npm using this command:
$ npm install serverless -g
The Framework takes the form of a CLI, creating scaffolding, automating tasks, performing concurrent deployments, and more.
Note that we work closely with multiple teams at AWS to implement best practices. Using the Framework offers you years of AWS expertise and best practices, out of the box.
The CLI can also install existing Serverless Projects that have been published as npm packages. To install the Serverless Starter project, run this:
$ serverless project install serverless-starter
You’ll be prompted for some information to customize this project and make it your own. Be sure to enter a globally unique domain, which will be used to name an AWS S3 Bucket that’s automatically created for your project on installation. This bucket stores backups of project information that can be shared across your team. Finally, enter the Access Keys you created in the steps above.
Once you’ve finished the prompts, the following will happen:
- The Serverless Project will be downloaded and renamed.
- Serverless Plugins used by the Project will be installed.
- A project “development” stage and region will be initialized.
- An IAM Role will be created for your Project; its Lambda functions will use it to access other AWS resources in your account (e.g., a DynamoDb table).
The Serverless Framework is designed to help you share code across your Lambda functions. It does this by including the functions’ parent folders and any code those parent folders hold within the deployed package.
The top level of these parent folders are called Serverless Components, and they exist in the root of your project. When you deploy any of your project’s functions, each function zips up its entire parent component. That is what’s uploaded to AWS.
In the installed Project, you will see a folder entitled
restApi. This is a Serverless Component. If you look inside it, you will see the following folders:
- lib. This is code shared across all of your functions.
- multi. This is a Serverless Module (a folder that contains related Lambda functions). There are multiple Lambda functions in this module, each with a single REST API endpoint. You can see a function’s endpoints by looking at their
s-function.jsonfile. This is one way you can architect your REST API endpoints.
- single. This is another Serverless Module, containing only one Lambda function. However, this Lambda has multiple REST API endpoints associated with it. This single Lambda reads the HTTP method of the incoming request and performs logic accordingly. This is another way you can architect your REST API endpoints.
serverless-starter (project) |- _meta |- node_modules |- restApi (component) |- lib |- node_modules |- multi (module) |- create (function) |- show (function) |- single (module) |- all (function
To run your functions locally, you can use the following command. Make sure you enter the path to your function as a parameter:
$ serverless function run restApi/single/all
This command runs your functions locally and emulates the AWS Lambda environment.
Let’s deploy your Lambda functions using the Serverless deployment dashboard. Run:
$ serverless dash deploy
This will display an interactive screen, listing all of the functions and endpoints in your component. Use the arrow keys and press Enter next to each asset you want to deploy.
Then hit Enter next to
Deploy, and the following will happen:
- The Framework will make copies of the component for each Lambda function you’ve toggled for deployment.
- This project comes with the Serverless Optimizer Plugin, which will browserify and minify your component’s code for each Lambda function, reducing their file size and improving their response times.
- The Framework will compress and back up each Lambda function to your Project Bucket on AWS S3 with a timestamp, as well as upload the compressed files directly to AWS Lambda.
- Your deployed Lambda functions on AWS will be automatically versioned and aliased to the Project stage you target during deployment (likely your “development” stage).
- The endpoints you selected for deployment will be provisioned on AWS API Gateway and connected to their respective Lambda functions.
After deployment has finished, you will be presented with AWS ARNs for your Lambda functions, as well as URLs for any endpoints you deployed.
You’re done! Your serverless REST API is up and running. It’s massively scalable, and it charges you only when it’s called. It doesn’t get more efficient than that.