AWS Lambda announced a standardized way to handle non-code configuration that’s consistent across Lambda runs in the form of environment variables. Anyone who’s read about 12 Factor Apps or used Heroku/OpenShift for any length of time will feel right at home. You set the environment variables on your function, and they show up in the process environment at execution time.

In the Serverless Framework

On the ball as usual, the Serverless Framework team has merged a PR with support for environments. Here’s what my little test project configuration looks like with environment variables set.

service: testenvvars
provider:
  name: aws
  runtime: python2.7
  environment:
    TESTNUM: 27
    TESTSTR: hello
functions:
  hello:
    handler: handler.hello

With those set, I can run serverless deploy normally, and those vars are set for me. To check, I wrote a Python handler for the hello function that will respond with the environment.

import datetime, os

def hello(event, context):
    e = dict(os.environ.items())

    # specifically add the two vars we set
    e['relevant'] = {k: os.environ[k] for k in ('TESTNUM', 'TESTSTR')}
    # and a timestamp
    e['relevant']['timestamp'] = datetime.datetime.utcnow().isoformat()
    return e

The relevant portion of the output is pretty much what you’d expect. You can see the full output in this gist, but here’s the important bits.

{
  "timestamp": "2016-11-21T19:26:22.928586",
  "TESTNUM": "27",
  "TESTSTR": "hello"
}

Restrictions

There are a couple restrictions on environment variables:

Maximum of 4KB total
Must be simple types (strings, ints, etc)

The first restriction is due to KMS, which is where variables are stored. With KMS storage comes a certain peace of mind – it’s safe to put credentials, keys, and other secrets in the Lambda environment.

There’s still an argument to be made for manually encrypting/decrypting secrets. The secrets show up in the Lambda GetFunctionConfiguration API call, for example. If there are secrets that some team members (like contractors) shouldn’t be able to see you’ll still need a different way of limiting access to those secrets.

In my testing, I also found some interesting consistency questions with environment variables. For this example, I used the same handler code from above while deploying new environment values. First, I started looping invocations of the Lambda function with serverless invoke.

while true; do
  ~/code/serverless/bin/serverless invoke -f hello  | jq .relevant
done

Deploying the new values works fine, but it’s not monotonic. I had requests see the old value after the new value was already seen by other functions. Here’s the output:

{
  "TESTNUM": "22",
  "TESTSTR": "hello"
}
{
  "TESTNUM": "22",
  "TESTSTR": "hello"
}
{
  "TESTNUM": "23",
  "TESTSTR": "hello"
}
{
  "TESTNUM": "22",
  "TESTSTR": "hello"
}
{
  "TESTNUM": "23",
  "TESTSTR": "hello"
}
{
  "TESTNUM": "23",
  "TESTSTR": "hello"
}
{
  "TESTNUM": "23",
  "TESTSTR": "hello"
}

Notice the one request where the TESTNUM value shows up as 22 after a request has seen 23. The Lambda and KMS docs don’t make any promises about consistency of new values rolling out, but it’s important to note that even my limited testing uncovered the inconsistency. When doing config changes like changing service keys, make sure that you have overlapping time where both keys work since it’s not possible to rely on config values changing exactly when you want.

Wrapping Up

Having env vars in my toolkit is pretty exciting. Being able to set config values without changing code will make my EBS Snapshot series (part 2) and Yesterdaytabase project to be easier to package and give to you all.

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AWS Lambda Environment Variables

Heroku-Style Environments, Now Shipping In Lambda

In the Serverless Framework

Restrictions

Wrapping Up