Serverless Offline

This Serverless plugin emulates AWS λ and API Gateway on your local machine to speed up your development cycles. To do so, it starts an HTTP server that handles the request's lifecycle like APIG does and invokes your handlers.

Features

Node.js, Python, Ruby, Go, Java (incl. Kotlin, Groovy, Scala) λ runtimes.
Velocity templates support.
Lazy loading of your handler files.
And more: integrations, authorizers, proxies, timeouts, responseParameters, HTTPS, CORS, etc...

This plugin is updated by its users, I just do maintenance and ensure that PRs are relevant to the community. In other words, if you find a bug or want a new feature, please help us by becoming one of the contributors ✌️ ! See the contributing section.

Documentation

Installation
Usage and command line options
Run modes
Invoke Lambda
The process.env.IS_OFFLINE variable
Docker and Layers
Authorizers
Custom headers
Environment variables
AWS API Gateway Features
WebSocket
Debug process
Resource permissions and AWS profile
Simulation quality
Usage with other plugins
Credits and inspiration
License
Contributing
Contributors

Installation

First, add Serverless Offline to your project:

npm install serverless-offline --save-dev

Then inside your project's serverless.yml file add following entry to the plugins section: serverless-offline. If there is no plugin section you will need to add it to the file.

Note that the "plugin" section for serverless-offline must be at root level on serverless.yml.

It should look something like this:

plugins:
  - serverless-offline

You can check whether you have successfully installed the plugin by running the serverless command line:

serverless --verbose

the console should display Offline as one of the plugins now available in your Serverless project.

Usage and command line options

In your project root run:

serverless offline or sls offline.

to list all the options for the plugin run:

sls offline --help

All CLI options are optional:

corsAllowHeaders

Used as default Access-Control-Allow-Headers header value for responses. Delimit multiple values with commas.
Default: 'accept,content-type,x-api-key'

corsAllowOrigin

Used as default Access-Control-Allow-Origin header value for responses. Delimit multiple values with commas.
Default: '*'

corsDisallowCredentials

When provided, the default Access-Control-Allow-Credentials header value will be passed as 'false'.
Default: true

corsExposedHeaders

Used as additional Access-Control-Exposed-Headers header value for responses. Delimit multiple values with commas.
Default: 'WWW-Authenticate,Server-Authorization'

disableCookieValidation

Used to disable cookie-validation on hapi.js-server.

dockerHost

The host name of Docker.
Default: localhost

dockerHostServicePath

Defines service path which is used by SLS running inside Docker container.

dockerNetwork

The network that the Docker container will connect to.

dockerReadOnly

Marks if the docker code layer should be read only.
Default: true

enforceSecureCookies

Enforce secure cookies

host

-o Host name to listen on.
Default: localhost

httpPort

Http port to listen on.
Default: 3000

httpsProtocol

-H To enable HTTPS, specify directory (relative to your cwd, typically your project dir) for both cert.pem and key.pem files.

ignoreJWTSignature

When using HttpApi with a JWT authorizer, don't check the signature of the JWT token.

lambdaPort

Lambda http port to listen on.
Default: 3002

layersDir

The directory layers should be stored in.
Default: ${codeDir}/.serverless-offline/layers'

localEnvironment

Copy local environment variables.
Default: false

noAuth

Turns off all authorizers.

noPrependStageInUrl

Don't prepend http routes with the stage.

noTimeout

-t Disables the timeout feature.

prefix

-p Adds a prefix to every path, to send your requests to http://localhost:3000/[prefix]/[your_path] instead.
Default: ''

reloadHandler

Reloads handler with each request.

resourceRoutes

Turns on loading of your HTTP proxy settings from serverless.yml.

terminateIdleLambdaTime

Number of seconds until an idle function is eligible for termination.

useDocker

Run handlers in a docker container.

useInProcess

Run handlers in the same process as 'serverless-offline'.

webSocketHardTimeout

Set WebSocket hard timeout in seconds to reproduce AWS limits (https://docs.aws.amazon.com/apigateway/latest/developerguide/limits.html#apigateway-execution-service-websocket-limits-table).
Default: 7200 (2 hours)

webSocketIdleTimeout

Set WebSocket idle timeout in seconds to reproduce AWS limits (https://docs.aws.amazon.com/apigateway/latest/developerguide/limits.html#apigateway-execution-service-websocket-limits-table).
Default: 600 (10 minutes)

websocketPort

WebSocket port to listen on.
Default: 3001

Any of the CLI options can be added to your serverless.yml. For example:

custom:
  serverless-offline:
    httpsProtocol: 'dev-certs'
    httpPort: 4000
      foo: 'bar'

Options passed on the command line override YAML options.

By default you can send your requests to http://localhost:3000/. Please note that:

You'll need to restart the plugin if you modify your serverless.yml or any of the default velocity template files.
When no Content-Type header is set on a request, API Gateway defaults to application/json, and so does the plugin. But if you send an application/x-www-form-urlencoded or a multipart/form-data body with an application/json (or no) Content-Type, API Gateway won't parse your data (you'll get the ugly raw as input), whereas the plugin will answer 400 (malformed JSON). Please consider explicitly setting your requests' Content-Type and using separate templates.

Run modes

node.js

Lambda handlers with serverless-offline for the node.js runtime can run in different execution modes and have some differences with a variety of pros and cons. they are currently mutually exclusive and it's not possible to use a combination, e.g. use in-process for one Lambda, and worker-threads for another. It is planned to combine the flags into one single flag in the future and also add support for combining run modes.

worker-threads (default)

handlers run in their own context
memory is not being shared between handlers, memory consumption is therefore higher
memory is being released when handlers reload or after usage
environment (process.env) is not being shared across handlers
global state is not being shared across handlers
easy debugging

NOTE:

native modules need to be a Node-API addon or be declared as context-aware using NODE_MODULE_INIT(): https://nodejs.org/docs/latest/api/addons.html#worker-support

in-process

handlers run in the same context (instance) as serverless and serverless-offline
memory is being shared across lambda handlers as well as with serverless and serverless-offline
no reloading capabilities as it is [currently] not possible to implement for commonjs handlers (without memory leaks) and for esm handlers
environment (process.env) is being shared across handlers as well as with serverless and serverless-offline
global state is being shared across lambda handlers as well as with serverless and serverless-offline
easy debugging

docker

handlers run in a docker container
memory is not being shared between handlers, memory consumption is therefore higher
memory is being released when handlers reload or after usage
environment (process.env) is not being shared across handlers
global state is not being shared across handlers
debugging more complicated

Python, Ruby, Go, Java (incl. Kotlin, Groovy, Scala)

the Lambda handler process is running in a child process.

Invoke Lambda

To use Lambda.invoke you need to set the lambda endpoint to the serverless-offline endpoint:

import { env } from 'node:process'
import aws from 'aws-sdk'

const lambda = new aws.Lambda({
  apiVersion: '2015-03-31',
  // endpoint needs to be set only if it deviates from the default
  endpoint: env.IS_OFFLINE
    ? 'http://localhost:3002'
    : 'https://lambda.us-east-1.amazonaws.com',
})

All your lambdas can then be invoked in a handler using

import { Buffer } from 'node:buffer'
import aws from 'aws-sdk'

const { stringify } = JSON

const lambda = new aws.Lambda({
  apiVersion: '2015-03-31',
  endpoint: 'http://localhost:3002',
})

export async function handler() {
  const clientContextData = stringify({
    foo: 'foo',
  })

  const payload = stringify({
    data: 'foo',
  })

  const params = {
    ClientContext: Buffer.from(clientContextData).toString('base64'),
    // FunctionName is composed of: service name - stage - function name, e.g.
    FunctionName: 'myServiceName-dev-invokedHandler',
    InvocationType: 'RequestResponse',
    Payload: payload,
  }

  const response = await lambda.invoke(params).promise()

  return {
    body: stringify(response),
    statusCode: 200,
  }
}

You can also invoke using the aws cli by specifying --endpoint-url

aws lambda invoke /dev/null \
  --endpoint-url http://localhost:3002 \
  --function-name myServiceName-dev-invokedHandler

List of available function names and their corresponding serverless.yml function keys are listed after the server starts. This is important if you use a custom naming scheme for your functions as serverless-offline will use your custom name. The left side is the function's key in your serverless.yml (invokedHandler in the example below) and the right side is the function name that is used to call the function externally such as aws-sdk (myServiceName-dev-invokedHandler in the example below):

serverless offline
...
offline: Starting Offline: local/us-east-1.
offline: Offline [http for lambda] listening on http://localhost:3002
offline: Function names exposed for local invocation by aws-sdk:
           * invokedHandler: myServiceName-dev-invokedHandler

To list the available manual invocation paths exposed for targeting by aws-sdk and aws-cli, use SLS_DEBUG=* with serverless offline. After the invoke server starts up, full list of endpoints will be displayed:

SLS_DEBUG=* serverless offline
...
offline: Starting Offline: local/us-east-1.
...
offline: Offline [http for lambda] listening on http://localhost:3002
offline: Function names exposed for local invocation by aws-sdk:
           * invokedHandler: myServiceName-dev-invokedHandler
[offline] Lambda Invocation Routes (for AWS SDK or AWS CLI):
           * POST http://localhost:3002/2015-03-31/functions/myServiceName-dev-invokedHandler/invocations
[offline] Lambda Async Invocation Routes (for AWS SDK or AWS CLI):
           * POST http://localhost:3002/2014-11-13/functions/myServiceName-dev-invokedHandler/invoke-async/

You can manually target these endpoints with a REST client to debug your lambda function if you want to. Your POST JSON body will be the Payload passed to your function if you were to calling it via aws-sdk.

The `process.env.IS_OFFLINE` variable

Will be "true" in your handlers when using serverless-offline.

Docker and Layers

To use layers with serverless-offline, you need to have the useDocker option set to true. This can either be by using the --useDocker command, or in your serverless.yml like this:

custom:
  serverless-offline:
    useDocker: true

This will allow the docker container to look up any information about layers, download and use them. For this to work, you must be using:

AWS as a provider, it won't work with other provider types.
Layers that are compatible with your runtime.
ARNs for layers. Local layers aren't supported as yet.
A local AWS account set-up that can query and download layers.

If you're using least-privilege principals for your AWS roles, this policy should get you by:

{
  "Statement": [
    {
      "Action": "lambda:GetLayerVersion",
      "Effect": "Allow",
      "Resource": "arn:aws:lambda:*:*:layer:*:*"
    }
  ],
  "Version": "2012-10-17"
}

Once you run a function that boots up the Docker container, it'll look through the layers for that function, download them in order to your layers folder, and save a hash of your layers so it can be re-used in future. You'll only need to re-download your layers if they change in the future. If you want your layers to re-download, simply remove your layers folder.

You should then be able to invoke functions as normal, and they're executed against the layers in your docker container.

Additional Options

There are 5 additional options available for Docker and Layer usage.

dockerHost
dockerHostServicePath
dockerNetwork
dockerReadOnly
layersDir

dockerHost

When running Docker Lambda inside another Docker container, you may need to configure the host name for the host machine to resolve networking issues between Docker Lambda and the host. Typically in such cases you would set this to host.docker.internal.

dockerHostServicePath

When running Docker Lambda inside another Docker container, you may need to override the code path that gets mounted to the Docker Lambda container relative to the host machine. Typically in such cases you would set this to ${PWD}.

dockerNetwork

When running Docker Lambda inside another Docker container, you may need to override network that Docker Lambda connects to in order to communicate with other containers.

dockerReadOnly

For certain programming languages and frameworks, it's desirable to be able to write to the filesystem for things like testing with local SQLite databases, or other testing-only modifications. For this, you can set dockerReadOnly: false, and this will allow local filesystem modifications. This does not strictly mimic AWS Lambda, as Lambda has a Read-Only filesystem, so this should be used as a last resort.

layersDir

By default layers are downloaded on a per-project basis, however, if you want to share them across projects, you can download them to a common place. For example, layersDir: /tmp/layers would allow them to be shared across projects. Make sure when using this setting that the directory you are writing layers to can be shared by docker.

Authorizers

Token authorizers

As defined in the Serverless Documentation you can use API Keys as a simple authentication method.

Serverless-offline will emulate the behaviour of APIG and create a random token that's printed on the screen. With this token you can access your private methods adding x-api-key: generatedToken to your request header. All api keys will share the same token.

Custom authorizers

Only custom authorizers are supported. Custom authorizers are executed before a Lambda function is executed and return an Error or a Policy document.

The Custom authorizer is passed an event object as below:

{
  "authorizationToken": "<Incoming bearer token>",
  "methodArn": "arn:aws:execute-api:<Region id>:<Account id>:<API id>/<Stage>/<Method>/<Resource path>",
  "type": "TOKEN"
}

The methodArn does not include the Account id or API id.

The plugin only supports retrieving Tokens from headers. You can configure the header as below:

"authorizer": {
  "authorizerResultTtlInSeconds": "0",
  "identitySource": "method.request.header.Authorization", // or method.request.header.SomeOtherHeader
  "type": "TOKEN"
}

Remote authorizers

You are able to mock the response from remote authorizers by setting the environmental variable AUTHORIZER before running sls offline start

Example:

Unix: export AUTHORIZER='{"principalId": "123"}'

Windows: SET AUTHORIZER='{"principalId": "123"}'

JWT authorizers

For HTTP APIs, JWT authorizers defined in the serverless.yml can be used to validate the token and scopes in the token. However at this time, the signature of the JWT is not validated with the defined issuer. Since this is a security risk, this feature is only enabled with the --ignoreJWTSignature flag. Make sure to only set this flag for local development work.

Serverless plugin authorizers

If your authentication needs are custom and not satisfied by the existing capabilities of the Serverless offline project, you can inject your own authentication strategy. To inject a custom strategy for Lambda invocation, you define a custom variable under serverless-offline called authenticationProvider in the serverless.yml file. The value of the custom variable will be used to require(your authenticationProvider value) where the location is expected to return a function with the following signature.

module.exports = function (endpoint, functionKey, method, path) {
  return {
    getAuthenticateFunction() {
      return {
        async authenticate(request, h) {
          // your implementation
        },
      }
    },

    name: 'your strategy name',
    scheme: 'your scheme name',
  }
}

A working example of injecting a custom authorization provider can be found in the projects integration tests under the folder custom-authentication.

Custom headers

You are able to use some custom headers in your request to gain more control over the requestContext object.

Header	Event key	Example
cognito-identity-id	event.requestContext.identity.cognitoIdentityId
cognito-authentication-provider	event.requestContext.identity.cognitoAuthenticationProvider
sls-offline-authorizer-override	event.requestContext.authorizer	{ "iam": {"cognitoUser": { "amr": ["unauthenticated"], "identityId": "abc123" }}}

By doing this you are now able to change those values using a custom header. This can help you with easier authentication or retrieving the userId from a cognitoAuthenticationProvider value.

Environment variables

You are able to use environment variables to customize identity params in event context.

Environment Variable	Event key
SLS_COGNITO_IDENTITY_POOL_ID	event.requestContext.identity.cognitoIdentityPoolId
SLS_ACCOUNT_ID	event.requestContext.identity.accountId
SLS_COGNITO_IDENTITY_ID	event.requestContext.identity.cognitoIdentityId
SLS_CALLER	event.requestContext.identity.caller
SLS_API_KEY	event.requestContext.identity.apiKey
SLS_API_KEY_ID	event.requestContext.identity.apiKeyId
SLS_COGNITO_AUTHENTICATION_TYPE	event.requestContext.identity.cognitoAuthenticationType
SLS_COGNITO_AUTHENTICATION_PROVIDER	event.requestContext.identity.cognitoAuthenticationProvider

You can use serverless-dotenv-plugin to load environment variables from your .env file.

AWS API Gateway Features

Velocity Templates

Serverless doc ~ AWS doc

You can supply response and request templates for each function. This is optional. To do so you will have to place function specific template files in the same directory as your function file and add the .req.vm extension to the template filename. For example, if your function is in code-file: helloworld.js, your response template should be in file: helloworld.res.vm and your request template in file helloworld.req.vm.

Velocity nuances

Consider this requestTemplate for a POST endpoint:

"application/json": {
  "payload": "$input.json('$')",
  "id_json": "$input.json('$.id')",
  "id_path": "$input.path('$').id"
}

Now let's make a request with this body: { "id": 1 }

AWS parses the event as such:

{
  "payload": {
    "id": 1
  },
  "id_json": 1,
  "id_path": "1" // Notice the string
}

Whereas Offline parses:

{
  "payload": {
    "id": 1
  },
  "id_json": 1,
  "id_path": 1 // Notice the number
}

Accessing an attribute after using $input.path will return a string on AWS (expect strings like "1" or "true") but not with Offline (1 or true). You may find other differences.

CORS

Serverless doc

For HTTP APIs, the CORS configuration will work out of the box. Any CLI arguments passed in will be ignored.

For REST APIs, if the endpoint config has CORS set to true, the plugin will use the CLI CORS options for the associated route. Otherwise, no CORS headers will be added.

Catch-all Path Variables

AWS doc

Set greedy paths like /store/{proxy+} that will intercept requests made to /store/list-products, /store/add-product, etc...

ANY method

AWS doc

Works out of the box.

Lambda and Lambda Proxy Integrations

Serverless doc ~ AWS doc

Works out of the box. See examples in the manual_test directory.

HTTP Proxy

Serverless doc ~ AWS doc - AWS::ApiGateway::Method ~ AWS doc - AWS::ApiGateway::Resource

Example of enabling proxy:

custom:
  serverless-offline:
    resourceRoutes: true

    YourCloudFormationMethodId:
      Properties:
        ......
        Integration:
          Type: HTTP_PROXY
          Uri: 'https://s3-${self:custom.region}.amazonaws.com/${self:custom.yourBucketName}/{proxy}'
          ......
      Type: AWS::ApiGateway::Method

custom:
  serverless-offline:
    resourceRoutes:
      YourCloudFormationMethodId:
        Uri: 'http://localhost:3001/assets/{proxy}'

Response parameters

AWS doc

You can set your response's headers using ResponseParameters.

May not work properly. Please PR. (Difficulty: hard?)

Example response velocity template:

"responseParameters": {
  "method.response.header.X-Powered-By": "Serverless", // a string
  "method.response.header.Warning": "integration.response.body", // the whole response
  "method.response.header.Location": "integration.response.body.some.key" // a pseudo JSON-path
},

WebSocket

Usage in order to send messages back to clients:

POST http://localhost:3001/@connections/{connectionId}

Or,

import aws from 'aws-sdk'

const apiGatewayManagementApi = new aws.ApiGatewayManagementApi({
  apiVersion: '2018-11-29',
  endpoint: 'http://localhost:3001',
});

apiGatewayManagementApi.postToConnection({
  ConnectionId: ...,
  Data: ...,
});

Where the event is received in the lambda handler function.

There's support for websocketsApiRouteSelectionExpression in it's basic form: $request.body.x.y.z, where the default value is $request.body.action.

Debug process

Serverless offline plugin will respond to the overall framework settings and output additional information to the console in debug mode. In order to do this you will have to set the SLS_DEBUG environmental variable. You can run the following in the command line to switch to debug mode execution.

Unix: export SLS_DEBUG=*

Windows: SET SLS_DEBUG=*

Interactive debugging is also possible for your project if you have installed the node-inspector module and chrome browser. You can then run the following command line inside your project's root.

Initial installation: npm install -g node-inspector

For each debug run: node-debug sls offline

The system will start in wait status. This will also automatically start the chrome browser and wait for you to set breakpoints for inspection. Set the breakpoints as needed and, then, click the play button for the debugging to continue.

Depending on the breakpoint, you may need to call the URL path for your function in separate browser window for your serverless function to be run and made available for debugging.

Interactive Debugging with Visual Studio Code (VSC)

With newer versions of node (6.3+) the node inspector is already part of your node environment and you can take advantage of debugging inside your IDE with source-map support. Here is the example configuration to debug interactively with VSC. It has two steps.

Step 1 : Adding a launch configuration in IDE

Add a new launch configuration to VSC like this:

{
  "cwd": "${workspaceFolder}",
  "name": "Debug Serverless Offline",
  "request": "launch",
  "runtimeArgs": ["run", "debug"],
  "runtimeExecutable": "npm",
  "sourceMaps": true,
  "type": "node"
}

Step2 : Adding a debug script

You will also need to add a debug script reference in your package.json file

Add this to the scripts section:

Unix/Mac: "debug" : "export SLS_DEBUG=* && node --inspect /usr/local/bin/serverless offline"

Windows: "debug": "SET SLS_DEBUG=* && node --inspect node_modules\\serverless\\bin\\serverless offline"

Example:

....
"scripts": {
  "debug" : "SET SLS_DEBUG=* && node --inspect node_modules\\serverless\\bin\\serverless offline"
}

In VSC, you can, then, add breakpoints to your code. To start a debug sessions you can either start your script in package.json by clicking the hovering debug intellisense icon or by going to your debug pane and selecting the Debug Serverless Offline configuration.

Resource permissions and AWS profile

Lambda functions assume an IAM role during execution: the framework creates this role and set all the permission provided in the iamRoleStatements section of serverless.yml.

However, serverless offline makes use of your local AWS profile credentials to run the lambda functions and that might result in a different set of permissions. By default, the aws-sdk would load credentials for you default AWS profile specified in your configuration file.

You can change this profile directly in the code or by setting proper environment variables. Setting the AWS_PROFILE environment variable before calling serverless offline to a different profile would effectively change the credentials, e.g.

AWS_PROFILE=<profile> serverless offline

Simulation quality

This plugin simulates API Gateway for many practical purposes, good enough for development - but is not a perfect simulator. Specifically, Lambda currently runs on Node.js v12.x, v14.x and v16.x (AWS Docs), whereas Offline runs on your own runtime where no memory limits are enforced.

Usage with other plugins

When combining this plugin with other plugins there are a few things that you need to keep in mind.

You should run serverless offline start instead of serverless offline. The start command fires the offline:start:init and offline:start:end lifecycle hooks which can be used by other plugins to process your code, add resources, perform cleanups, etc.

The order in which plugins are added to serverless.yml is relevant. Plugins are executed in order, so plugins that process your code or add resources should be added first so they are ready when this plugin starts.

For example:

plugins:
  - serverless-middleware # modifies some of your handler based on configuration
  - serverless-webpack # package your javascript handlers using webpack
  - serverless-dynamodb-local # adds a local dynamo db
  - serverless-offline # runs last so your code has been pre-processed and dynamo is ready

That works because all those plugins listen to the offline:start:init to do their processing. Similarly they listen to offline:start:end to perform cleanup (stop dynamo db, remove temporary files, etc).

Credits and inspiration

This plugin was initially a fork of Nopik's Serverless-serve.

License

MIT

Contributing

Yes, thank you! This plugin is community-driven, most of its features are from different authors. Please update the docs and tests and add your name to the package.json file. We try to follow Airbnb's JavaScript Style Guide.