@Marvin I’m trying to deploy a Prefect Server locally that will run on Prefect 2.20.4 The server is currently running along with a Postgres DB at its backend. I also deployed a Prefect Worker of type Kubernetes, also using an image with Prefect 2.20.4 installed. Now, I’ve deployed a flow that uses a custom image that also uses Prefect 2.20.4. I’m trying to run the flow using the UI and am getting the following errors:

2025-01-28 16:15:28 14:15:28.087 | INFO    | prefect.flow_runs.runner - Opening process...
2025-01-28 16:15:34 /usr/local/lib/python3.8/runpy.py:127: RuntimeWarning: 'prefect.engine' found in sys.modules after import of package 'prefect', but prior to execution of 'prefect.engine'; this may result in unpredictable behaviour
2025-01-28 16:15:34   warn(RuntimeWarning(msg))
2025-01-28 16:15:34 /usr/local/lib/python3.8/site-packages/prefect/utilities/dispatch.py:162: UserWarning: Type 'KubernetesClusterConfig' at /usr/local/lib/python3.8/site-packages/prefect_kubernetes/credentials.py:40 has key 'kubernetes-cluster-config' that matches existing registered type 'KubernetesClusterConfig' from /usr/local/lib/python3.8/site-packages/prefect/blocks/kubernetes.py:32. The existing type will be overridden.
2025-01-28 16:15:34   warnings.warn(
2025-01-28 16:15:34 /usr/local/lib/python3.8/site-packages/pydantic/v1/schema.py:631: UserWarning: Callable print_func was excluded from schema since JSON schema has no equivalent type.
2025-01-28 16:15:34   warnings.warn(skip.message, UserWarning)
2025-01-28 16:15:34 /usr/local/lib/python3.8/site-packages/prefect/engine.py:436: PrefectDeprecationWarning: prefect.deployments.deployments.load_flow_from_flow_run has been deprecated. It will not be available after Dec 2024. Will be moved in Prefect 3 to prefect.flows:load_flow_from_flow_run
2025-01-28 16:15:34   else await load_flow_from_flow_run(
2025-01-28 16:15:34 14:15:34.076 | INFO    | prefect.deployment - Cloned repository '<https://github.com/*/*.git>' into '*-test_filter_flow_locally'
2025-01-28 16:15:34 14:15:34.127 | ERROR   | prefect.flow_runs.runner - Process for flow run 'artichoke-yak' exited with status code: -4
2025-01-28 16:15:34 14:15:34.152 | INFO    | prefect.flow_runs.runner - Reported flow run 'dfacf593-fa9f-496b-ac4c-efcbc41fd592' as crashed: Flow run process exited with non-zero status code -4.
2025-01-28 16:15:35 14:15:35.434 | INFO    | prefect.deployment - Cloned repository '<https://github.com/*/*.git>' into '*-test_filter_flow_locally'

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@Marvin I’m trying to deploy a Prefect Server locally that will run on Prefect 2.20.4 The server is currently running along with a Postgres DB at its backend. I also deployed a Prefect Worker of type Kubernetes, also using an image with Prefect 2.20.4 installed. Now, I’ve deployed a flow that uses a custom image that also uses Prefect 2.20.4. I’m trying to run the flow using the UI and am errors such as:

2025-01-28 15:53:50 Server error '500 Internal Server Error' for url '<http://host.docker.internal:4200/api/logs/>'
2025-01-28 15:53:50 Response: {'exception_message': 'Internal Server Error'}

It seems you're encountering a "500 Internal Server Error" while running your flow on a Prefect Server with a Postgres backend. Here are some potential causes and solutions: 1. Database Configuration: Ensure that the Postgres database is properly configured. The

pg_trgm

extension must be installed and enabled for Prefect to work correctly with Postgres. Check your database connection settings and ensure that the

PREFECT_API_DATABASE_CONNECTION_URL

is correctly set. 2. Timeout Issues: There might be timeouts in database communications, especially if the server is experiencing high load or resource constraints. Consider increasing database connection timeouts or optimizing the database performance. 3. Server and Network Configuration: Verify that your network settings allow the necessary connections between the Prefect server, database, and workers. Ensure that the

PREFECT_API_URL

is correctly set in your environment, particularly if running inside containers. 4. Resource Allocation: If the server is experiencing resource constraints, it might lead to internal server errors. Consider increasing CPU and memory limits for the Prefect server. 5. Logs and Debugging: Check the server logs for more detailed error messages. You can enable debug mode by setting

PREFECT_DEBUG_MODE=1

to get more insights into what's happening. 6. Version Compatibility: Ensure that all components (server, workers, and flows) are using compatible versions. You mentioned using Prefect 2.20.4, so double-check that all components are indeed using this version. For more detailed troubleshooting, you can refer to the Prefect documentation and GitHub issues related to similar errors. If these suggestions do not resolve the issue, consider reaching out to the Prefect community or support for more targeted assistance.

@Marvin I’m running Prefect Server locally, both my Server and Kubernetes Worker are using Prefect 2.20.4 with Python 3.8. I’m triggering a deployment that is also running on the same versions. The Kubernetes pod is created and the flow run enters the Running step, but it crashes due to:

RuntimeWarning: 'prefect.engine' found in sys.modules after import of package 'prefect', but prior to execution of 'prefect.engine'; this may result in unpredictable behaviour
UserWarning: Type 'KubernetesClusterConfig' at /python3.8/site-packages/prefect_kubernetes/credentials.py:40 has key 'kubernetes-cluster-config' that matches existing registered type 'KubernetesClusterConfig' from /python3.8/site-packages/prefect/blocks/kubernetes.py:32. The existing type will be overridden.
/python3.8/site-packages/prefect/engine.py:436: PrefectDeprecationWarning: prefect.deployments.deployments.load_flow_from_flow_run has been deprecated.
else await load_flow_from_flow_run(
 | ERROR   | prefect.flow_runs.runner - Process for flow run 'copper-tody' exited with status code: -4
 | INFO    | prefect.flow_runs.runner - Reported flow run 'c0d46037-79fc-4fcc-bffc-9bac55b4af08' as crashed:

You've encountered several issues related to Prefect 2.20.4, particularly when running Kubernetes deployments. Here's a summary of the problems and potential solutions: 1. RuntimeWarning with `prefect.engine`: This warning indicates that

prefect.engine

is being found in

sys.modules

before its execution, which can lead to unpredictable behavior. This issue has been noted in various contexts, often related to the way Prefect is imported and executed. It might not directly cause crashes but can contribute to instability. 2. Duplicate Type Registration Warning: The warning about

KubernetesClusterConfig

suggests a conflict between different Prefect packages or versions. This can occur if multiple packages define the same block type. Ensure that your environment is clean and that there are no conflicting installations of Prefect or its extensions. 3. Deprecation Warning for `load_flow_from_flow_run`: This function has been deprecated, and you should transition to using the recommended alternatives. You can check the Prefect 2.x upgrade guide for more details on how to adjust your workflows accordingly. Upgrade Guide. 4. Flow Run Crashing: The crash with status code

-4

may be related to the above issues, particularly if the environment is unstable due to conflicting packages or deprecated functions. For resolving these issues, consider the following steps: - Clean Environment: Ensure your Python environment is clean and not polluted with multiple conflicting versions of Prefect or its dependencies. - Update Prefect: Although you're on 2.20.4, consider checking for any patches or updates that might address these specific issues. - Review and Adjust Code: Review the code for deprecated functions and adjust according to the latest documentation. For further assistance, you may need to delve deeper into specific logs or consider reaching out to the Prefect community or support channels. If these steps don't resolve the issues, you might also want to explore the Prefect GitHub issues for any ongoing discussions or solutions. Relevant GitHub issues and discussions: - RuntimeWarning 'prefect.engine' found in sys.modules - Duplicate pods running same flow run If you want to explore more about these warnings and their resolutions, it might be worth checking Prefect's documentation and community channels for more detailed guidance.