@Marvin - I am deploying a flow to a work pool with compute managed by an ECS cluster. The ECS service's task definition has both a executionRoleArn and taskRoleArn. This successfully creates a worker that receives events. However when the a deployment run is triggered, a fargate task is created with a task definition that does not include the taskRoleArn. It fails with the following eerror botocore.errorfactory.ClientException: An error occurred (ClientException) when calling the RegisterTaskDefinition operation: Fargate requires task definition to have execution role ARN to support ECR images. 023719 PM Error Reported flow run 'b80bfa42-f93c-44e3-85e9-4fdb7053d539' as crashed: Flow run could not be submitted to infrastructure: ClientException('An error occurred (ClientException) when calling the RegisterTaskDefinition operation: Fargate requires task definition to have execution role ARN to support ECR images.')

It seems like you're facing an issue where the task definition for your Fargate tasks is missing the necessary

executionRoleArn

. This is a common issue when deploying flows to ECS using Prefect, and it can result in errors when trying to register the task definition. Here's a concise summary of the findings: 1. Ensure Role ARN Inclusion: Make sure that both

executionRoleArn

and

taskRoleArn

are explicitly set in your task definition. If using Prefect 3.x, ensure these are correctly configured in your deployment settings. 2. Common Issues with ECS: The error you're encountering is often due to missing role ARNs when Prefect attempts to register a new task definition. This can happen if Prefect is creating a new task definition each time a flow runs, which might not carry over the expected roles. 3. Rate Limit and Re-registration: There are known issues with Prefect repeatedly registering task definitions, which can lead to AWS rate limits. This is discussed in issues like PrefectHQ/prefect#15865 and PrefectHQ/prefect#16485. 4. Predefined Task Definitions: Consider using predefined task definitions to mitigate this issue. This involves manually creating a task definition with the necessary ARNs and using it in your deployments. You can find more details on this in Prefect's ECS guide. 5. AWS CLI Configuration: If you haven't already, you might want to manually register your task definition using the AWS CLI to ensure all roles are correctly assigned. This can help verify that the issue isn't with the Prefect configuration but with how the task definition is being registered. If these steps don't resolve your issue, consider reaching out on Prefect's community forums or checking for any updates in related GitHub issues.

@Marvin - this still does not help me. I have created the task definition manually as you suggest, below is that definition. This creates a worker successfully, however a flow being triggered results in the error I shared. It appears there's something missing in my prefect.yaml or flow deployment?

{
  "family": "prefect-worker-task",
  "networkMode": "awsvpc",
  "requiresCompatibilities": [
    "FARGATE"
  ],
  "cpu": "2048",
  "memory": "4096",
  "executionRoleArn": "arn:aws:iam::{masked}:role/ecsTaskExecutionRole",
  "taskRoleArn": "arn:aws:iam::{masked}:role/ml-ecs-task-execution-role",
  "containerDefinitions": [
    {
      "name": "prefect-worker",
      "image": "{masked}.<http://dkr.ecr.us-east-1.amazonaws.com/prefect:3-latest|dkr.ecr.us-east-1.amazonaws.com/prefect:3-latest>",
      "cpu": 2048,
      "memory": 4096,
      "essential": true,
      "command": [
        "/bin/sh",
        "-c",
        "pip install prefect-aws && prefect worker start --pool my-ecs-pool --type ecs"
      ],
      "environment": [
        {
          "name": "PREFECT_API_URL",
          "value": "{masked}"
        },
        {
          "name": "PREFECT_API_KEY",
          "value": "{masked}"
        }
      ]
    }
  ]
}

It appears that your issue might stem from a misconfiguration in how the Prefect deployment interacts with ECS. Here are some insights and steps to consider: 1. ECS Task Role Configuration: - Ensure that the

taskRoleArn

specified in your task definition has the necessary permissions for running your flows. This includes access to any AWS services your flow interacts with, such as S3 or DynamoDB. 2. Prefect Configuration: - Make sure your

prefect.yaml

includes the correct configuration for ECS. Unfortunately, the specific configuration details for

prefect.yaml

related to ECS aren't explicitly detailed in the current Prefect 3.x documentation excerpts, but generally, it should include references to the work pool and any environment variables needed for the flow execution. 3. Role Permissions: - Double-check that the roles (both

executionRoleArn

and

taskRoleArn

) have the necessary policies attached. The

AmazonECSTaskExecutionRolePolicy

is crucial for tasks to pull images from ECR and publish logs to CloudWatch. 4. Prefect API and Worker Setup: - Ensure the worker is correctly set up to connect to your Prefect API using the

PREFECT_API_URL

and

PREFECT_API_KEY

. This is critical for the worker to communicate with Prefect Cloud. 5. ECS Guide: - Refer to the Prefect ECS guide for additional configuration details and ensure your setup aligns with the documented best practices. If these steps do not resolve the issue, you might want to verify the task definition registration process or consider reaching out to Prefect's community forums for more tailored assistance.

@Marvin All of those steps are applied. Here is the prefect.yaml. should i be including the task arns under

deployments

name: ecs-worker-guide
# this is pre-populated by running prefect init
prefect-version: 2.14.20

# build section allows you to manage and build docker images
build:
- prefect_docker.deployments.steps.build_docker_image:
    id: build_image
    requires: prefect-docker>=0.3.1
    image_name: {masked}.<http://dkr.ecr.us-east-1.amazonaws.com/prefect-flows|dkr.ecr.us-east-1.amazonaws.com/prefect-flows>
    tag: latest
    dockerfile: ./Dockerfile

# push section allows you to manage if and how this project is uploaded to remote locations
push:
- prefect_docker.deployments.steps.push_docker_image:
    requires: prefect-docker>=0.3.1
    image_name: '{{ build_image.image_name }}'
    tag: '{{ build_image.tag }}'

 # the deployments section allows you to provide configuration for deploying flows
deployments:
- name: my_ecs_deployment
  version:
  tags: []
  description:
  entrypoint: main.py:my_flow
  parameters: {}
  work_pool:
    name: my-ecs-pool
    job_variables:
      image: '{{ build_image.image }}'    
    work_queue_name:
  schedules: []
  concurrency_limit:

pull:
- prefect.deployments.steps.set_working_directory:
    directory: /opt/prefect/prefect-example

In your

prefect.yaml

, you don't need to explicitly include the task ARNs under the

deployments

section. However, you should ensure that the task definitions and roles are correctly referenced in your work pool configuration. Here's a concise breakdown of what you should consider: 1. Task Definition ARN in Work Pool: - Ensure that your ECS work pool configuration includes the task definition ARN. This tells the worker to use the specified task definition when spinning up ECS tasks, rather than creating new ones. This can be particularly useful if you have a predefined task definition with specific roles and permissions. 2. Prefect YAML Configuration: - Your

prefect.yaml

seems mostly correct. Ensure that the

work_pool

section is correctly configured to reference your ECS pool. This includes the

name

and any specific

job_variables

that might be needed. 3. Environment Variables: - Confirm that all necessary environment variables, like

PREFECT_API_URL

and

PREFECT_API_KEY

, are correctly set in your task definition. This ensures that the worker can communicate with Prefect Cloud. 4. Reference Documentation: - For detailed steps and configurations, refer to the Prefect ECS guide. This guide provides insights into setting up ECS workers and configuring tasks properly. If you've ensured all these configurations are correct and the issue persists, it might be worth checking Prefect's community forums or support channels for further assistance.

@Marvin - after updating the worker pool to reference the arns i am now receiving the following error. i can confirm the role that the assumed role does have the policy

ec2:DescribeSubnets

raise error_class(parsed_response, operation_name)
botocore.exceptions.ClientError: An error occurred (UnauthorizedOperation) when calling the DescribeSubnets operation: You are not authorized to perform this operation. User: arn:aws:sts::{masked}:assumed-role/ml-ecs-task-execution-role/9a79be54fa1a42d8b9aa7f614876844b is not authorized to perform: ec2:DescribeSubnets because no identity-based policy allows the ec2:DescribeSubnets action

The error you're encountering indicates that the ECS task execution role does not have sufficient permissions to perform the

ec2:DescribeSubnets

action. Here are the steps you should take to resolve this: 1. Verify Role Permissions: - Ensure that the IAM role (

adonis-ml-ecs-task-execution-role

) associated with your ECS task has the necessary permissions. Specifically, it should include the

ec2:DescribeSubnets

action in its policy. 2. Policy Attachment: - If the role does not have the required permissions, you need to attach a policy that includes

ec2:DescribeSubnets

. You can either create a custom policy with this specific permission or attach a more comprehensive policy like

AmazonEC2FullAccess

if appropriate. 3. Policy Update: - If you've confirmed that the policy is attached but still face issues, ensure that the policy is correctly propagated. Sometimes, IAM policy changes can take a few moments to propagate across AWS services. 4. Reference Documentation: - You can refer to the Prefect ECS guide for more insights into setting up roles and permissions for ECS tasks. By ensuring the ECS task execution role has the correct permissions, you should be able to resolve the unauthorized operation error. If the issue persists, consider reaching out to AWS support for more detailed assistance on IAM configurations.