# Managing AWS lambda functions from start to finish with Terraform

#### First posted on: 2018/08/02

Categories: infrastructure

AWS lambda functions look deceptively simple. The devil is in the details though. Once you have written the code and have created a .zip file, there’s a few more steps to go.

For starters, we need an IAM profile to be defined with appropriate policies allowing the function to access the AWS resources. To setup the lambda function to be invoked automatically in reaction to another event, we need some more permissions and references to these resources. Then, we have to create a lambda function in AWS infrastructure and point it to our .zip file that we have created above. Everytime, we update this, .zip, we have to ask AWS lambda to update the code again. A lot of steps, all ripe for automation.

# Automation using AWS CLI/Serverless frameworks - Creating Lambda infrastructure islands

One straight forward, no fuss approach is to use the AWS CLI. The main problem I think with this approach and using any of the serverless tools and frameworks out there like apex, serverless or zappa is that they treat the infrastructure of your lambda functions as islands, rather than being part of your broader AWS infrastructure. The same S3 bucket’s contents which you want your lambda function to be triggered in reaction to changes in may be the bucket some other non-lambda application writes to. You want to run your lambda function in the same VPC as your database RDS instance. Needless to say, there will cross-application infrastructure references.

What follows is a non-production tested suggestion for managing your lambda functions and their infrastructure as part of your global infrastructure as code repository.

# Managing lambda functions using Terraform

Consider a lambda function ec2_state_change. I wrote this for a recent article. The src directory has the source of the lambda function which is written in Python. To create the lambda function (for the first time) and to deploy new versions of the code, the following BASH script (there is a PowerShell script too) is run:

!/usr/bin/env bash
set -ex

# Create a .zip of src
pushd src
zip -r ../src.zip *
popd

aws s3 cp src.zip s3://aws-health-notif-demo-lambda-artifacts/ec2-state-change/src.zip
version=$(aws s3api head-object --bucket aws-health-notif-demo-lambda-artifacts --key ec2-state-change/src.zip) version=$(echo $version | python -c 'import json,sys; obj=json.load(sys.stdin); print(obj["VersionId"])') # Deploy to demo environment pushd ../../terraform/environments/demo terraform init terraform apply \ -var aws_region=ap-southeast-2 \ -var ec2_state_change_handler_version=$version \
-target=module.ec2_state_change_handler.module.ec2_state_change_handler.aws_lambda_function.lambda \
-target=module.ec2_state_change_handler.module.ec2_state_change_handler.aws_cloudwatch_event_rule.rule \
-target=module.ec2_state_change_handler.module.ec2_state_change_handler.aws_cloudwatch_event_target.target \
-target=module.ec2_state_change_handler.module.ec2_state_change_handler.aws_iam_role_policy.lambda_cloudwatch_logging \
-target=module.ec2_state_change_handler.module.ec2_state_change_handler.aws_lambda_permission.cloudwatch_lambda_execution
popd



The above script does the following main things:

• First, it creates a ZIP of the src sub-directory
• It uploads it to a designated bucket in S3
• It gets the version of the file it just uploaded
• It then changes the current working directory to one with terraform configuration in it
• Then runs terraform apply supplying specific targets related to the function it is uploading

The first time, this script is run, it will create all the infrastructure that is needed by the lambda function to be run. On subsequent applications, only the lambda function’s version will change. We can even separate the script into two such that we can use different AWS credentials for first time creation and subsequent code updates.

We can run this script as part of a CI/CD pipeline. The repository pointed to above has the terraform configuration in it as well, but we can always download the terrraform configuration tarball or git clone it during a CI run. The key idea here that I want to illustrate here is that your terraform configuration for the lambda function can and should co-exist with the rest of your infrastructure.

# Terraform source layout

While working on the article I mentioned above, I also worked for the first time with structuring my terraform code with modules. Especially, how we can leverage modules to manage different environments for our infrastructure. The above script relies on this behavior.

My requirement was to manage two lambda functions. They would both have their own infrastructure, but in terms of terraform code, they would be more or less identical with the exception of the naming of the lambda functions, the AWS cloudwatch event they would be invoked on, and the environmnet variables.

So, I created a root module, cloudwatch_event_handlers with a main.tf and defined a variables.tf file with all the configurable module parameters. This is where my first confusion with terraform modules was cleared. Before this, I somehow couldn’t wrap my head around where my module definitions would go and and where would I be using it. In programming languages, you defined the sharable code in a library of some form which isn’t intended to be executed directly. The program which uses the sharable code is the one that has the executable code. I was expecting something similar with terraform. That is, the resources would be defined in my “real” code. In terraform, the resource statements belong to the “module”, and you actually define module in the code you plan to “execute”.

Using the cloudwatch_event_handlers module, I define another module to implement the lambda function that would handle EC2 state change events as follows:

variable "lambda_artifacts_bucket_name" {
type = "string"
}

variable "ec2_state_change_handler_version" {
type = "string"
}

module "ec2_state_change_handler" {

source = "../cloudwatch_event_handlers"

cloudwatch_event_rule_name = "ec2-state-change-event"
cloudwatch_event_rule_description = "Notify when there is a state change in EC2 instances"
cloudwatch_event_rule_pattern = <<PATTERN
{
"source": [ "aws.ec2" ],
"detail-type": [ "EC2 Instance State-change Notification" ]
}
PATTERN
lambda_iam_role_name = "ec2_state_change_lambda_iam"
lambda_function_name = "ec2_state_change"
lambda_handler = "main.handler"
lambda_runtime = "python3.6"

lambda_artifacts_bucket_name = "${var.lambda_artifacts_bucket_name}" lambda_artifacts_bucket_key = "ec2-state-change/src.zip" lambda_version = "${var.ec2_state_change_handler_version}"
}



Similarly, the health_event_handler module is defined as:

variable "lambda_artifacts_bucket_name" {
type = "string"
}

variable "health_event_handler_version" {
type = "string"
}

variable "health_event_handler_environment" {
type = "map"
}

module "health_event_handler" {

source = "../cloudwatch_event_handlers"

cloudwatch_event_rule_name = "health-event"
cloudwatch_event_rule_description = "Invoke a lambda function when there is a scheduled health event"
cloudwatch_event_rule_pattern = <<PATTERN
{
"source": [ "aws.health" ],
"detail-type": [ "AWS Health Event" ]
}
PATTERN

lambda_iam_role_name = "health_event_lambda"
lambda_function_name = "health_event"
lambda_handler = "main.handler"
lambda_runtime = "python3.6"

lambda_artifacts_bucket_name = "${var.lambda_artifacts_bucket_name}" lambda_artifacts_bucket_key = "health-event/src.zip" lambda_version = "${var.health_event_handler_version}"

lambda_environment = "${var.health_event_handler_environment}" }  Note how the implementations code here says it’s module! Anyway, another thing I learned here is that the inputs to a module are it’s variables. Thats’ it. I found it hard to wrap my head around it, but I think i have got it now. Okay, now that we defined our “source” configuration, we next define environments for our infrastructure. Currently, the repository here has a demo environment defined under the environments sub-directory. The idea is to have one sub-directory per environment. Inside this demo environment, we have the bootstrap configuration where we create the bucket and dynamodb table for storing our terraform state remotely. We then define the backend created in backend.tf. With the setup done, we then bring in the modules we created above in the main.tf file: provider "aws" { region = "${var.aws_region}"
}

module "lambda_artifacts" {
source = "../../modules/deployment_artifacts"
artifacts_bucket_name = "${var.lambda_artifacts_bucket_name}" } module "ec2_state_change_handler" { source = "../../modules/ec2_state_change_handler" lambda_artifacts_bucket_name = "${var.lambda_artifacts_bucket_name}"
ec2_state_change_handler_version = "${var.ec2_state_change_handler_lambda_version}" } module "health_event_handler" { source = "../../modules/health_event_handler" lambda_artifacts_bucket_name = "${var.lambda_artifacts_bucket_name}"
health_event_handler_version = "${var.aws_health_event_handler_lambda_version}" health_event_handler_environment = "${var.health_event_handler_lambda_environment}"
}


Once again, we have another set of child modules. Here we only specify the environment specific variables which we then populate via terraform.tfvars and during application (in the scripts above).

Coming back to our script I shared at the beginning, here’s the key terraform specific bits reproduced which should make more sense now:

# Deploy to demo environment
pushd ../../terraform/environments/demo
terraform init
terraform apply \
-var aws_region=ap-southeast-2 \
-var ec2_state_change_handler_version=\$version \
-target=module.ec2_state_change_handler.module.ec2_state_change_handler.aws_lambda_function.lambda \
-target=module.ec2_state_change_handler.module.ec2_state_change_handler.aws_cloudwatch_event_rule.rule \
-target=module.ec2_state_change_handler.module.ec2_state_change_handler.aws_cloudwatch_event_target.target \
-target=module.ec2_state_change_handler.module.ec2_state_change_handler.aws_iam_role_policy.lambda_cloudwatch_logging \
-target=module.ec2_state_change_handler.module.ec2_state_change_handler.aws_lambda_permission.cloudwatch_lambda_execution
popd


# Replacing scripts

Of course scripting is hard, and you run into all kinds of issues and they break in all kinds of ways, but they are a fact of life when it comes to infrastructure considering how quick they are to put together. I would want to replace the above scripts by a small tool written in a proper programming language. The difference from the current tools out there would be that it would work with existing terraform code.

May be apex someday? It uses terraform to manage your infrastructure, so may we could make it reuse your existing infrastructure as code.

# Summary

I plan to trial this setup out for managing lambda functions as I get a chance, what do you think? Is this something that could work better than managing lambda functions infrastructure as islands?