serverless-cloudside-plugin

Serverless plugin for using cloudside resources when developing functions locally.

This plugin allows you to use AWS CloudFormation intrinsic functions (such as !Ref and !GetAtt) to reference cloud resources during local development. When added to your environment variables, these values are replaced with the same identifiers used when deployed to the cloud. You can invoke your functions locally, use the serverless-offline plugin, or use a compatible test runner that uses the serverless invoke test command. You can now keep your serverless.yml files free from pseudo variables and other concatenated strings and simply use the built-in CloudFormation features.

Installation

Install using Serverless plugin manager

serverless plugin install --name serverless-cloudside-plugin

Install using npm

Install the module using npm:

npm install serverless-cloudside-plugin --save-dev

Add serverless-cloudside-plugin to the plugin list of your serverless.yml file:

plugins:
  - serverless-cloudside-plugin

Usage

When executing your function locally, the serverless-cloudside-plugin will replace any environment variable that contains either a !Ref or a !GetAtt that references a CloudFormation resource within your serverless.yml file.

In the example below, we are creating an SQS Queue named myQueue and referencing it (using a CloudFormation intrinsic function) in an environment variable named QUEUE.

functions:
  myFunction:
    handler: myFunction.handler
    environment:
      QUEUE: !Ref myQueue

resources:
  Resources:
    myQueue:
      Type: AWS::SQS::Queue
      Properties:
        QueueName: ${self:service}-${self:provider.stage}-myQueue

If we deploy this to the cloud, our !Ref myQueue will be replaced with a QueueUrl (e.g. https://sqs.us-east-1.amazonaws.com/1234567890/sample-service-dev-myQueue). We can then use that when invoking the AWS SDK and working with our queue. However, if we were to invoke this function locally using sls invoke local -f myFunction, our QUEUE environment variable would return [object Object] instead of our QueueUrl. This is because the Serverless Framework is actually replacing our !Ref with: { "Ref": "myQueue" }.

There are workarounds to this, typically involving using pseudo variables to construct our own URL. But this method is error prone and requires us to hardcode formats for the different service types. Using the serverless-cloudside-plugin, you can now use the simple reference format above, and always retrieve the correct PhysicalResourceId for the resource.

Invoking a function locally

Once the plugin is installed, you will have a new invoke option named invoke cloudside. Simply run this command with a function and it will resolve all of your cloud variables and then execute the standard invoke local command.

sls invoke cloudside -f myFunction

PLEASE NOTE that in order for resources to be referenced, you must deploy your service to the cloud at least initially. References to non-deployed resources will be populated with "RESOURCE NOT DEPLOYED".

All invoke local parameters are supported such as --stage and --path, as well as the new --docker flag that lets you run your function locally in a Docker container. This mimics the Lambda environment much more closely than your local machine.

By default, the plugin will reference resources from your current CloudFormation stack (including your "stage" if it is part of your stack name). You can change the cloudside stage by using the --cloudStage option and supplying the stage name that you'd like to use. For example, if you are developing in your dev stage locally, but want to use a DynamoDB table that is deployed to the test stage, you can do the following:

sls invoke cloudside -f myFunction -s dev --cloudStage test

This will populate any ${opt:stage} references with dev, but your !Ref values will use the ones from your test stage.

You might also want to pull values from an entirely different CloudFormation stack. You can do this by using the --stackName option and supplying the complete stack name. For example:

sls invoke cloudside -f myFunction --stackName someOtherStack-dev

Using with the serverless-offline plugin

The serverless-offline plugin is a great tool for testing your serverless APIs locally, but it has the same problem referencing CloudFormation resources. The serverless-cloudside-plugin lets you run serverless-offline with all of your cloud variables correctly replaced.

sls offline cloudside

To enable hot-reload when running the server, use the --reloadHandler flag:

sls offline cloudside --reloadHandler

The above command will start the API Gateway emulator and allow you to test your functions locally. The --cloudStage and --stackName options are supported as well as all of the serverless-offline options.

Using with a test runner

You can use this plugin with other test runner plugins such as serverless-mocha-plugin. This will make it easier to run integration tests (including in your CI/CD systems) before deploying. Simply run the following when invoking your tests:

sls invoke test cloudside -f myFunction

This plugin extends the invoke test command, so any test runner plugin that uses that format should work correctly. All plugin options should remain available.

Available Functions

This plugin currently supports the !Ref function that returns the PhysicalResourceId from CloudFormation. For most resources, this is the value you will need to interact with the corresponding service in the AWS SDK (e.g. QueueUrl for SQS, TopicArn for SNS, etc.).

There is also initial (and limited) support for using !GetAtt to retrieve an ARN. For example, you may use !GetAtt myQueue.Arn to retrieve the ARN for myQueue. The plugin generates the ARN based on the service type. For supported types, it will return a properly formatted ARN. For others, it will replace the value with "FUNCTION NOT SUPPORTED". In most cases, it should be possible to support generating an ARN for a resource, but the format will need to be added to the plugin.

Contributions

Contributions, ideas and bug reports are welcome and greatly appreciated. Please add issues for suggestions and bug reports or create a pull request.