Having a treatment that is executed regularly can be really important for a lot of project to do a lot of little tasks. So we will see today how we can do it in AWS!
Global vision
As you can see, it's a really simple architecture to be able to do it. In fact, we only need EventBridge to do it.
AWS EventBridge
Quick overview about AWS EventBridge.
AWS EventBridge is an AWS service which facilitate event driven architectures. It allows with all its features to plan execution of tasks regularly, or if every time some specific actions happen.
Set up
Lambda
About the lambda code, we will use the Python "Hello World" template. This example is enough for our need in this example.
import logging
import os
import boto3
logger = logging.getLogger()
logger.setLevel(logging.INFO)
def lambda_handler(event, context):
logger.info(f'Hello World!')
logger.info(f'## ENVIRONMENT VARIABLES: {os.environ}')
logger.info(f'## EVENT: {event}')
return {
'statusCode': 200,
}
Its Terraform file is simple too, and is like every other terraform file to deploy a lambda
data "archive_file" "lambda_zip" {
type = "zip"
source_file = "${path.module}/src/hello_world.py"
output_file_mode = "0666"
output_path = "${path.module}/bin/hello_world.py.zip"
}
resource "aws_lambda_function" "processing_lambda" {
filename = data.archive_file.lambda_zip.output_path
function_name = "hello_world"
handler = "hello_world.lambda_handler"
source_code_hash = data.archive_file.lambda_zip.output_base64sha256
role = aws_iam_role.processing_lambda_role.arn
runtime = "python3.9"
timeout = 900
memory_size = 10240
tags = {
"service": "cron_lambda"
}
}
resource "aws_iam_role" "processing_lambda_role" {
name = hello_world_role
path = "/service-role/"
permissions_boundary = // To define correctly!
assume_role_policy = data.aws_iam_policy_document.assume-role-policy_document.json
inline_policy {
name = "test_policy"
policy = data.aws_iam_policy_document.test_policy_document.json
}
}
data "aws_iam_policy_document" "assume-role-policy_document" {
statement {
actions = ["sts:AssumeRole"]
principals {
type = "Service"
identifiers = ["lambda.amazonaws.com"]
}
}
}
data "aws_iam_policy_document" "test_policy_document" {
statement {
actions = [
"logs:CreateLogGroup",
"logs:CreateLogStream",
"logs:PutLogEvents",
"logs:AssociateKmsKey"
]
resources = ["*"]
}
}
Warning :
permissions_boundaryfield is not setup in this example, and it's the only thing you need to setup to make it work.
Now that we have everything we need to deploy our lambda, we can go to the next step : write the terraform file for the EventBridge stuff!
EventBridge
Its declaration is in 3 blocks :
- aws_cloudwatch_event_rule : Which will define what are the conditions to trigger an event (here it's our scheduler)
- aws_cloudwatch_event_target : Which will define what will be execute when the event is triggered
- aws_lambda_permission : Which are some permissions to allow EventBridge to call a lambda function.
The Terraform file looks like this :
resource "aws_cloudwatch_event_rule" "scheduler" {
name = "scheduler_lambda_cron"
description = "Schedule for Lambda Function"
schedule_expression = "cron(0/10 * ? * MON-FRI *)"
}
resource "aws_cloudwatch_event_target" "schedule_lambda" {
rule = aws_cloudwatch_event_rule.scheduler.name
target_id = "processing_lambda"
arn = aws_lambda_function.processing_lambda.arn
}
resource "aws_lambda_permission" "allow_events_bridge_to_run_lambda" {
statement_id = "AllowExecutionFromCloudWatch"
action = "lambda:InvokeFunction"
function_name = aws_lambda_function.processing_lambda.function_name
principal = "events.amazonaws.com"
}
In this part, there's only one thing to think about, and it's the schedule_expression field. It's here that you will define when your lambda will be executed.
In this example, the lambda function will be called every 10 minutes during weekdays.
If you want to have more informations about crons and how to update it, please check this documentation from AWS.
Execution
Now that you have everything, you can deploy all the stuff and enjoy more automated treatments!
I hope it will help you! 🍺
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