A service
is like a project. It's where you define your AWS Lambda Functions, the events
that trigger them and any AWS infrastructure resources
they require, all in a file called serverless.yml
.
To get started building your first Serverless Framework project, create a service
.
In the beginning of an application, many people use a single Service to define all of the Functions, Events and Resources for that project. This is what we recommend in the beginning.
myService/
serverless.yml # Contains all functions and infrastructure resources
However, as your application grows, you can break it out into multiple services. A lot of people organize their services by workflows or data models, and group the functions related to those workflows and data models together in the service.
users/
serverless.yml # Contains 4 functions that do Users CRUD operations and the Users database
posts/
serverless.yml # Contains 4 functions that do Posts CRUD operations and the Posts database
comments/
serverless.yml # Contains 4 functions that do Comments CRUD operations and the Comments database
This makes sense since related functions usually use common infrastructure resources, and you want to keep those functions and resources together as a single unit of deployment, for better organization and separation of concerns.
To create a service, use the create
command. You must also pass in a runtime (e.g., node.js, python etc.) you would like to write the service in. You can also pass in a path to create a directory and auto-name your service:
# Create service with nodeJS template in the folder ./myService
serverless create --template aws-nodejs --path myService
Here are the available templates for AWS Lambda:
Check out the create command docs for all the details and options.
You'll see the following files in your working directory:
serverless.yml
handler.js
Each service
configuration is managed in the serverless.yml
file. The main responsibilities of this file are:
events
section to automatically create the resources required for the event upon deploymentYou can see the name of the service, the provider configuration and the first function inside the functions
definition which points to the handler.js
file. Any further service configuration will be done in this file.
# serverless.yml
service: users
provider:
name: aws
runtime: nodejs12.x
stage: dev # Set the default stage used. Default is dev
region: us-east-1 # Overwrite the default region used. Default is us-east-1
stackName: my-custom-stack-name-${sls:stage} # Overwrite default CloudFormation stack name. Default is ${self:service}-${sls:stage}
apiName: my-custom-api-gateway-name-${sls:stage} # Overwrite default API Gateway name. Default is ${sls:stage}-${self:service}
profile: production # The default profile to use with this service
memorySize: 512 # Overwrite the default memory size. Default is 1024
deploymentBucket:
name: com.serverless.${self:provider.region}.deploys # Overwrite the default deployment bucket
serverSideEncryption: AES256 # when using server-side encryption
tags: # Tags that will be added to each of the deployment resources
key1: value1
key2: value2
deploymentPrefix: serverless # Overwrite the default S3 prefix under which deployed artifacts should be stored. Default is serverless
versionFunctions: false # Optional function versioning
stackTags: # Optional CF stack tags
key: value
stackPolicy: # Optional CF stack policy. The example below allows updates to all resources except deleting/replacing EC2 instances (use with caution!)
- Effect: Allow
Principal: '*'
Action: 'Update:*'
Resource: '*'
- Effect: Deny
Principal: '*'
Action:
- Update:Replace
- Update:Delete
Resource: '*'
Condition:
StringEquals:
ResourceType:
- AWS::EC2::Instance
functions:
usersCreate: # A Function
handler: users.create
events: # The Events that trigger this Function
- http: post users/create
usersDelete: # A Function
handler: users.delete
events: # The Events that trigger this Function
- http: delete users/delete
# The "Resources" your "Functions" use. Raw AWS CloudFormation goes in here.
resources:
Resources:
usersTable:
Type: AWS::DynamoDB::Table
Properties:
TableName: usersTable
AttributeDefinitions:
- AttributeName: email
AttributeType: S
KeySchema:
- AttributeName: email
KeyType: HASH
ProvisionedThroughput:
ReadCapacityUnits: 1
WriteCapacityUnits: 1
Every serverless.yml
translates to a single AWS CloudFormation template and a CloudFormation stack is created from that resulting CloudFormation template.
The handler.js
file contains your function code. The function definition in serverless.yml
will point to this handler.js
file and the function exported here.
Note: This file is not created by default
Create this file and add event data so you can invoke your function with the data via serverless invoke -p event.json
When you deploy a Service, all of the Functions, Events and Resources in your serverless.yml
are translated to an AWS CloudFormation template and deployed as a single CloudFormation stack.
To deploy a service, first cd
into the relevant service directory:
cd my-service
Then use the deploy
command:
serverless deploy
Deployment defaults to dev
stage and us-east-1
region on AWS, unless you specified these elsewhere, or add them in as options:
serverless deploy --stage prod --region us-east-1
Check out the deployment guide to learn more about deployments and how they work. Or, check out the deploy command docs for all the details and options.
To easily remove your Service from your AWS account, you can use the remove
command.
Run serverless remove -v
to trigger the removal process. As in the deploy step we're also running in the verbose
mode so you can see all details of the remove process.
Serverless will start the removal and informs you about its process on the console. A success message is printed once the whole service is removed.
The removal process will only remove the service on your provider's infrastructure. The service directory will still remain on your local machine so you can still modify and (re)deploy it to another stage, region or provider later on.
The Serverless Framework is usually installed globally via npm install -g serverless
. This way you have the Serverless CLI available for all your services.
Installing tools globally has the downside that the version can't be pinned inside package.json. This can lead to issues if you upgrade Serverless, but your colleagues or CI system don't. You can now use a new feature in your serverless.yml which is available only in the latest version without worrying that your CI system will deploy with an old version of Serverless.
To configure version pinning define a frameworkVersion
property in your serverless.yaml. Whenever you run a Serverless command from the CLI it checks if your current Serverless version is matching the frameworkVersion
range. The CLI uses Semantic Versioning so you can pin it to an exact version or provide a range. In general we recommend to pin to an exact version to ensure everybody in your team has the exact same setup and no unexpected problems happen.
# serverless.yml
frameworkVersion: '2.1.0'
service: users
provider:
name: aws
runtime: nodejs12.x
memorySize: 512
…
# serverless.yml
frameworkVersion: "^2.1.0" # >=2.1.0 && <3.0.0
service: users
provider:
name: aws
runtime: nodejs12.x
memorySize: 512
…
If you already have a Serverless service, and would prefer to lock down the framework version using package.json
, then you can install Serverless as follows:
# from within a service
npm install serverless --save-dev
To execute the locally installed Serverless executable you have to reference the binary out of the node modules directory.
Example:
node ./node_modules/serverless/bin/serverless deploy
Product