@Marvin I'm using the "prefecthq/prefect:3.0.0rc13-python3.12" image for my ECS Task but Prefect Cloud UI is reporting the flow crashed instead of logging messages from the container: Flow run infrastructure exited with non-zero status code: Exited with non 0 code. (Error Code: 1) This may be caused by attempting to run an image with a misspecified platform or architecture. The actual error was the ModuleNotFoundError: No module named 'pandas'

It seems like what's happening is that your Prefect ECS task is missing some dependencies, hence the

ModuleNotFoundError

for

pandas

. To fix this, you need to ensure pandas is included in your Docker image. Here's a strategy to resolve it: 1. Modify Dockerfile: Add

pandas

to the

Dockerfile

for the image. For example, if you're using a

requirements.txt

file, ensure it includes

pandas

and the Dockerfile installs it.

dockerfile
FROM prefecthq/prefect:3.0.0rc13-python3.12

# Add this line to install pandas
RUN pip install pandas

# Copy your requirements file and install other dependencies
COPY requirements.txt .
RUN pip install -r requirements.txt

# Ensure prefect commands are available
ENTRYPOINT ["prefect"]

2. Rebuild and Push Image: Rebuild your Docker image and push it to your container registry.

sh
docker build -t your-repo/prefect-image:latest .
docker push your-repo/prefect-image:latest

3. Update ECS Task Definition: Update your ECS task definition to use the new image. 4. Verify the Configuration: Ensure your flow's deployment YAML uses the latest image. Here are some relevant resources for further reading: - Dockerizing Python Applications - Prefect AWS ECS Guide - Issues for reference: - ModuleNotFoundError - Dependency Checking - Docker Image Execution Issue If you hit further issues or need specific help with Docker images or Prefect deployments, check out the Prefect documentation and GitHub issues for similar problems.

@Marvin why is my Flow run not reporting the container logs but instead saying the container crashed

The issue might be related to how your flow logs are being captured or the infrastructure setup for your ECS task in Prefect. Here are some possibilities and troubleshooting steps: 1. Logging Configuration: Ensure that your logging is correctly configured. Your flow should include proper logging to capture logs and send them to the Prefect backend.

python
   import httpx
   from prefect import flow, get_run_logger

   @flow
   def my_flow():
       logger = get_run_logger()
       <http://logger.info|logger.info>("Starting flow")
       # Your code here
       <http://logger.info|logger.info>("Flow completed")

2. ECS Configuration: Check that your ECS task definition is properly configured to stream logs. Make sure the AWS CloudWatch Logs configuration is correctly set up in the task definition.

json
   {
     "logConfiguration": {
       "logDriver": "awslogs",
       "options": {
         "awslogs-group": "/ecs/my-flow",
         "awslogs-region": "your-region",
         "awslogs-stream-prefix": "ecs"
       }
     }
   }

3. Error Handling: Verify that any error messages within your ECS task are being logged before the container exits. You can include error handling in your flow to log exceptions.

python
   try:
       my_flow()
   except Exception as e:
       logger = get_run_logger()
       logger.error(f"Flow crashed: {e}")

4. ECS Task Definition and Platform: Ensure there are no compatibility issues with the Docker image and the underlying platform. This might include architecture mismatches or missing dependencies. Useful References: - ECS Worker Guide - ECS Guide By following these steps, you should be able to determine why your container logs are not being captured and instead report the container crash. If the problem persists, checking the ECS task logs in AWS CloudWatch directly can provide more insight into the issue.

@Marvin I got the following error: Flow run 'discreet-pillbug' - Finished in state Failed("Flow run encountered an exception. ImportError: cannot import name 'AsyncClientContext' from 'prefect.context' (/usr/local/lib/python3.12/site-packages/prefect/context.py)") What does it mean?

The error "ImportError: cannot import name 'AsyncClientContext' from 'prefect.context'" typically occurs when there is a mismatch between different versions of Prefect that you are using. This could mean either you are using a Prefect version that has deprecated or moved the

AsyncClientContext

or there is an inconsistency in the environment setup. ### Steps to Resolve: 1. Check the Prefect Version: Ensure that all environments are using a compatible version of Prefect. You can check the current version using:

sh
    prefect --version

2. Update Prefect: If you're using an older version of Prefect, update to the latest version where this might be resolved.

sh
    pip install --upgrade prefect

3. Check for Code Changes: Look into the Prefect documentation or release notes for any changes regarding

AsyncClientContext

. Sometimes classes or methods are moved or renamed. 4. Refactor Code: If

AsyncClientContext

has been moved or deprecated, refactor your code to use the current approach as per the documentation. For example, if using a context manager for async operations with dask, refer to current examples. 5. Verify Dependencies: Make sure all dependencies and their versions are coherent and compatible with the version of Prefect you're using. References: - Prefect Dask Usage Guide - Runtime Contexts in Prefect Here's an example of a current approach:

python
import asyncio
import dask
from prefect import flow, task
from prefect_dask import DaskTaskRunner, get_async_dask_client

@task
async def compute_task():
    async with get_async_dask_client() as client:
        df = dask.datasets.timeseries("2000", "2001", partition_freq="4w")
        summary_df = await client.compute(df.describe())
        return summary_df

@flow(task_runner=DaskTaskRunner())
def dask_flow():
    return compute_task()

dask_flow()

By following these steps, you should be able to resolve the import error and ensure your flow runs correctly.