Based on the research and my experience with Dask and ECS, here are several potential causes and solutions for your stalling issue: 1. Network Configuration - Ensure that your security groups and network ACLs allow proper communication between the Dask scheduler and workers - Verify that the VPC, subnets, and security groups are correctly configured to allow internal communication - Check that your tasks can reach the Dask scheduler's port (typically 8786) 2. Resource Constraints - Monitor the CPU and memory usage in your ECS tasks - Ensure you've allocated sufficient resources in your task definitions - Check if your tasks are being throttled by AWS service limits 3. Infrastructure Setup - Fargate is known to have longer setup times compared to EC2 - Consider switching to EC2 if faster setup times are crucial - Ensure your task definition ARN is correctly specified in your Prefect work pool configuration 4. Debugging Steps: 1. Enable detailed logging for both Dask and Prefect 2. Monitor the Dask dashboard for any error messages or unusual patterns 3. Check the CloudWatch logs for your ECS tasks 4. Verify that your workers are properly registered with the scheduler 5. Code-level Verification: - Try running a simple test task to verify basic connectivity - Ensure your task code is properly serializable - Check if your dependencies are properly installed in your container Here's a simple test flow you can use to diagnose the issue:

python
from prefect import flow, task
from prefect_aws.ecs import ECSTask
import time

@task
def simple_task(x):
    # Add logging to track execution
    print(f"Starting to process {x}")
    time.sleep(1)  # Add small delay to ensure it's not instant
    print(f"Finished processing {x}")
    return x * x

@flow
def test_flow():
    results = []
    for i in range(5):
        results.append(simple_task.submit(i))
    return [r.result() for r in results]

if __name__ == "__main__":
    test_flow()

If this simple flow also stalls, it would indicate an infrastructure issue rather than a problem with your specific task code. Would you be able to: 1. Try running this simple test flow? 2. Share any error messages you see in the CloudWatch logs? 3. Confirm if you can see the print statements in your logs? This would help us narrow down whether it's a configuration issue or a problem with the task execution itself. Also, it might be worth considering if Fargate is the best choice for your use case. While Fargate offers simplified container management, it does come with longer setup times and potentially more complex networking configurations. If you're experiencing consistent issues, you might want to consider using EC2 instead, which typically provides more predictable performance and faster startup times.