Managing Envrionments on Serverless Framework

Posted on Mon 02 April 2018 in tutorials by Miguel Lopez

Technical Stack: AWS Lambda, Java 8 Read: 10 minutes


Check out the AWS Lambda Documentation if you're new to AWS Lambda and serverless technology.


AWS Lambda is one of the hottest services out on the market right now. First introduced in November 2014, it has completely revolutionized the way developers develop and deploy cloud-first services and applications. Here are some of the immediate benefits of Lambda functions:

  • Run code without servers
  • Automatically scales code without any configuration
  • Get charged per 100ms of execution time

By the end of this post, you will learn to manage and deploy AWS Lambda functions to dev/test/stage/prod environments using the Serverless framework as your deployment tool.

Serverless Framework

The Serverless Framework should not to be confused with Serverless Technology, the name commonly used to describe Function-as-a-Service technology. The Serverless Framework is a CLI-tool you can install to help you deploy and manage your serverless functions.

Serverless is my #1 choice for deplying lambda functions because:

  • It supports all major cloud providers. Serverless framework deploys to AWS, Azure, Google, etc. (No vendor lock-in)
  • YML based instructions that deploy infrastructure-as-code
  • Large developer community with dozens of plugins Github Repo Plugins

Serverless Framework uses a serverless.yml file to deploy your functions to a cloud provider.

Here is a basic example:

service: aws-java-simple-http-endpoint

frameworkVersion: ">=1.2.0 <2.0.0"

  name: aws
  runtime: java8

  artifact: build/distributions/

    handler: com.serverless.Handler
      - http:
          path: ping
          method: get

If you haven't deployed a function with Serverless yet, I'd recommend taking a few minutes to deploy their boilerplate function here.

Building Environments in Serverless

A creative way to build environments on your serverless.yml file is to take advantage of the serverless variable system. The Serverless variable system allows you to reference other yml files by loading them into a variable. This will be the bread and butter of the pattern i'm about to show you.

For example:

  configFile: ${file(./config/${self:provider.stage}.yml)}

  name: aws
  runtime: java8
  stage: ${opt:stage, 'dev'}
  region: 'us-east-2'
  profile: personal

  vpc: ${self:custom.configFile.vpc}
  • if sls deploy --stage prod is ran, the provider.stage variable in the yml will be set to prod
  • ${self:provider.stage} resolves to prod
  • prod is then used in ${file(./config/${self:provider.stage}.yml)}
  • ${file(./config/prod.yml)} and loaded into the custom.configFile variable
  • ${self:custom.configFile.vpc} will load the vpc variable from the prod.yml file loaded into custom.configFile

Likewise, if you ran sls deploy --stage test, the stage variablle would be set to test and the test.yml would be loaded into custom.configFile.

Organizing your environmentfiles

I'd recommend laying out your files in the following pattern:

| configs 
| - dev.yml
| - test.yml
| - stage.yml
| - prod.yml
| - dr.yml
| src 
| - main
| - - java
| - - -
| - - - - example
| - - - - - ExampleHandler
| serverless.yml

A typical config file will look like this:


region: "us-east-2"

APNS_BASE_ARN: ${ssm:/NONPROD/services/sns-apns-development}
GCM_BASE_ARN: ${ssm:/NONPROD/services/sns-gcm-development}

KMS_KEY: ${ssm:/NONPROD/security/default-kms-key}
ELASTICACHE_CONFIGURATION_ENDPOINT: ${ssm:/DEV/services/memcached/connection-url}

This allows you to define different regions per {stage}.yml. You have the flexibility to set different values for different variables. You could decide that the MEMCACHED_DEFAULT_TTL_VALUE: needs to be 172800 in PROD as opposed to the 604800 in DEV. You could call different SSM values or even define different VPC Security Groups and Subnets.

This pattern gives you a clear-readable format for your environment config files that are loaded into the parent serverless.yml file.

Here is a general serverless.yml that will use the following dev.yml file.

service: aws-java-sample

frameworkVersion: ">=1.2.0 <2.0.0"

  configFile: ${file(./config/${self:provider.stage}.yml)}

  name: aws
  runtime: java8
  stage: ${opt:stage, 'dev'}
  region: ${self:custom.configFile.region}
  profile: personal

  versionFunctions: false
  logRetentionInDays: 30

        APNS_BASE_ARN: ${self:custom.configFile.APNS_BASE_ARN}
        GCM_BASE_ARN: ${self:custom.configFile.GCM_BASE_ARN}


The APNS_BAS_ARN, GCM_BASE_ARN, ELASTICACHE_CONFIGURATION_ENDPOINT, and MEMCACHED_DEFAULT_TTL_VALUE variables are loaded from the custom.configFile file we loaded earlier with sls deploy --stage {env}.

Tip: ${opt:stage, 'dev'} just means to use the text passed in after the --stage cli argument. If no --stage argument is used then default to dev.


I've found this file pattern to be extremely useful for defining my AWS resources throughout serverless.yml. It gives me full control over what I'm passing to the serverless.yml file for each of my lambda environments.

You can find an example of the config pattern i've discussed here.