Lambda function to be called from CodePipeline to start and wait for a one-off ECS task

lambda_function.py

# Required env vars:
# $CLUSTER: name of the ECS cluster (i.e. `myapp-prod`)
# $TASK_DEFINITION: name and revision of the task definition (i.e. `mytask:1`)
# $SUBNETS: comma-separated list of subnets to place the new task (i.e. `sg-12345678,sg-abcdef12`)
# $SECURITY_GROUPS: comma-separated list of security groups to be used for the new task (i.e. `subnet-12345678`)

import boto3
import os
import traceback

code_pipeline = boto3.client('codepipeline')
ecs = boto3.client('ecs')


def lambda_handler(event, context):
    try:
        job_id = event['CodePipeline.job']['id']
        job_data = event['CodePipeline.job']['data']
        print('- CodePipeline JobID: %s' % job_id)

        if 'continuationToken' in job_data:
            # Not the first time we are called
            # Let's check the status of the one-off task
            print('- ContinuationToken: %s' % job_data['continuationToken'])
            response = ecs.describe_tasks(
                cluster=os.getenv('CLUSTER'),
                tasks=[
                    job_data['continuationToken']
                ]
            )
            task = response['tasks'][0]
            print('- Task: %s' % str(task))
            if task['lastStatus'] != 'STOPPED':
                # Not yet finished
                print('-- Task not yet finished, continuing at a later time')
                code_pipeline.put_job_success_result(jobId=job_id, continuationToken=job_data['continuationToken'])
            elif task['stoppedReason'] != 'Essential container in task exited':
                # Finished unsuccessfully, for some reason
                print('-- Task failed for unknown reason. Failing CodePipeline job')
                code_pipeline.put_job_failure_result(
                    jobId=job_id,
                    failureDetails={
                        'message': task['stoppedReason'],
                        'type': 'JobFailed'
                    }
                )
            elif task['containers'][0]['exitCode'] != 0:
                # Finished unsuccessfully
                print('-- Task failed because of container failed. Failing CodePipeline job')
                code_pipeline.put_job_failure_result(
                    jobId=job_id,
                    failureDetails={
                        'message': 'Task exited with exit code %s' %
                                   task['containers'][0]['exitCode'],
                        'type': 'JobFailed'
                    }
                )
            else:
                # Finished successfully
                print('-- Task succeeded. Succeeding CodePipeline job')
                code_pipeline.put_job_success_result(jobId=job_id)
        else:
            # First time we are called
            # Let's run the one-off task
            print('-- No ContinuationToken, starting task')
            response = ecs.run_task(
                cluster=os.getenv('CLUSTER'),
                launchType=os.getenv('LAUNCH_TYPE', 'FARGATE'),
                taskDefinition=os.getenv('TASK_DEFINITION'),
                count=int(os.getenv('COUNT', 1)),
                platformVersion='LATEST',
                networkConfiguration={
                    'awsvpcConfiguration': {
                        'subnets': os.getenv('SUBNETS').split(','),
                        'assignPublicIp': os.getenv('ASSIGN_PUBLIC_IP', 'ENABLED'),
                        'securityGroups': os.getenv('SECURITY_GROUPS').split(','),
                    },
                }
            )
            print('- Task: %s' % str(response))

            # Check the status of the task later
            continuation_token = response['tasks'][0]['taskArn']
            print('-- Task just triggered. Continuing at a later time')
            code_pipeline.put_job_success_result(jobId=job_id, continuationToken=continuation_token)

    except Exception as e:
        # If any other exceptions which we didn't expect are raised
        # then fail the job and log the exception message.
        print('ERROR: Function failed due to exception')
        print(e)
        traceback.print_exc()
        code_pipeline.put_job_failure_result(
            jobId=job_id,
            failureDetails={
                'message': 'Function exception: ' + str(e),
                'type': 'JobFailed'
            }
        )

    return "Complete."

Hi! How do you pass environment variables such as cluster, task definition name, etc.? Through code pipeline or you define them directly on the lambda function?

Hi! How do you pass environment variables such as cluster, task definition name, etc.? Through code pipeline or you define them directly on the lambda function?

I define the environment variables in the lambda function directly

Hi! How do you pass environment variables such as cluster, task definition name, etc.? Through code pipeline or you define them directly on the lambda function?

I define the environment variables in the lambda function directly

Thanks for your reply. I want to use the same lambda function for staging and production, how to do it then? Do you have any suggestions? I want to use different clusters at least. I might be able to reuse the same task definitions if I solve issue with environment variables there too.