@Marvin I have the image to be used in my kubernetes job for my deployment where

pandas

is installed among other deps:

docker run -ti europe-docker.pkg.dev/cambium-earth/prefect-runners-staging/default:latest
root@42107936d492:/opt/prefect# pip freeze
# ...
pandas==2.2.2

In my deployment I'm defining the image and the

ImagePullPolicy

to

'Always'

which I can see it's correctly applied from the job configuration:

k get pod -n prefect amigurumi-grebe-hmq8s-78mwz -o yaml
image: europe-docker.pkg.dev/cambium-earth/prefect-runners-staging/default:latest
    imagePullPolicy: Always
    name: prefect-job

Yet I get this error when the flow runs:

Flow could not be retrieved from deployment.
Traceback (most recent call last):
  File "", line 940, in exec_module
  File "", line 241, in _call_with_frames_removed
  File "/opt/prefect/data-canopy/data-flows/dataflows/flows/projects_observability_export_flow.py", line 4, in 
    import pandas as pd
ModuleNotFoundError: No module named 'pandas'

It seems that your issue lies in the image used for the Kubernetes deployment not containing the necessary dependencies, specifically

pandas

, despite it seemingly being installed. Here are the steps to troubleshoot and resolve the issue: 1. Verify Image Contents: Ensure that the

pandas

package is included in your Docker image. You can check this by running the image locally:

bash
   docker run -ti europe-docker.pkg.dev/cambium-earth/prefect-runners-staging/default:latest /bin/bash
   pip freeze | grep pandas

2. Update Docker Image: If

pandas

is not present, update your Dockerfile to include it. Ensure you rebuild and push the updated image to your repository:

Dockerfile
   FROM prefecthq/prefect:latest
   
   RUN pip install pandas

3. Tagging and Versioning: Use a specific tag or commit SHA for your Docker image to avoid potential issues with the

latest

tag not being updated properly.

yaml
   image: europe-docker.pkg.dev/cambium-earth/prefect-runners-staging/default:commit-sha
   imagePullPolicy: Always

4. Check Prefect Deployment Configurations: Verify your Prefect deployment configuration to ensure it points to the correct image.

yaml
   storage:
     - module: prefect.filesystems.GCS
       bucket: YOUR_BUCKET
       key: PATH/TO/FLOW
   infrastructure:
     job:
       docker:
         image: europe-docker.pkg.dev/cambium-earth/prefect-runners-staging/default:commit-sha

5. Re-deploy the Flow: After making these changes, re-deploy your flow using the updated image. To follow up further on how to manage and debug Kubernetes deployments in Prefect, refer to the Prefect Kubernetes deployment guide: Prefect Kubernetes Guide. Let's hope that fixes it. But, you know, with my luck, it probably won't. Feel free to reach out if you have any more questions.

@Marvin

docker run -ti europe-docker.pkg.dev/cambium-earth/prefect-runners-staging/default:latest /bin/bash
   pip freeze | grep pandas

WARNING: The requested image's platform (linux/amd64) does not match the detected host platform (linux/arm64/v8) and no specific platform was requested
root@825ae754ac21:/opt/prefect# pip freeze | grep pandas
geopandas==0.14.4
pandas==2.2.2

And the flow had been redeployed. I also tried pushing a different image and using it, it did not work either.

It looks like multiple issues and discussions have surfaced around similar problems. Here are a few key insights and suggestions: ### Insights from GitHub Issues: 1. Simultaneous Flows Causing Module Errors: - When running multiple flows, issues like

ModuleNotFoundError

arise. - Checking the cluster logs might show additional errors. - Link to Issue 2. Deployment with Custom Image Issues: - Using a custom image in

KubernetesJob

might not work as expected unless

infra_overrides

are used. - If the image is not respected, the default Prefect image is used instead. - Issue Example 3. GitHub Block Issues: - Using certain GitHub blocks for deployment can lead to errors. - Ensure that the blocks and configurations are properly set up. - Another Issue Example ### Potential Solutions and Next Steps: 1. Verify KubernetesJob Configuration: Make sure your deployment YAML or Python script includes

infra_overrides

to enforce the use of the correct image. Here's an example setup:

yaml
   job:
     docker:
       image: europe-docker.pkg.dev/cambium-earth/prefect-runners-staging/default:latest
   infra_overrides:
     image: europe-docker.pkg.dev/cambium-earth/prefect-runners-staging/default:latest

2. Check for Concurrent Flow Issues: There might be issues running concurrent flows using the same setup. Try running flows sequentially or isolating the problematic flow to identify issues. 3. Use Specific Tags: Ensure that you're tagging images explicitly with versions rather than using

latest

. It helps in avoiding issues arising from using stale images.

yaml
   image: europe-docker.pkg.dev/cambium-earth/prefect-runners-staging/default:<specific-tag>
   imagePullPolicy: Always

4. Review and Debug Logs: Always look at the detailed logs from both Prefect and Kubernetes. They often provide deeper insights into what might be going wrong. ### Deploy the Updated Image and Configuration Redeploy the flow with these updated configurations and tagged images, ensuring all dependencies are correctly included in the environment. Following these steps and suggestions should help in narrowing down and resolving the issue. Hang in there, and if the universe decides to not be completely indifferent, these steps might just work. For more detailed guidelines on deploying with Kubernetes on Prefect, refer to the Prefect Kubernetes Guide.