@Marvin I have a periodic job that targets a work queue with a single worker in it. The job is scheduled to run every 10 mins. It has been running perfectly for several weeks. Yesterday the worker was offline for most of the day due to some maintenance. The worker has now come back online but it is not picking up new runs. In the prefect UI I can see many runs that have been created and are now in the "Late" status. New runs continue to be created and go from "Scheduled" to "Late" and are never picked up by the worker. I have restarted the worker process several times but no change. What could be causing the worker to not pick up work?

Your issue with the worker not picking up jobs could be due to several factors. Based on the context gathered, here are some potential causes and solutions: 1. Worker-Queue Mismatch: Ensure that your worker is correctly configured to poll the specific work queue. Workers can only poll work pools that match their type. Double-check that the worker's configuration is aligned with the queue it should be targeting. Learn more about workers and queues. 2. Worker State: Restarting the worker is a good first step. If the worker process is running but not picking up tasks, verify that it is correctly connected to the Prefect API and has the necessary permissions to poll the queue. 3. Database or API Issues: There might be an issue with the Prefect server or database that is preventing the worker from retrieving tasks. Check the server logs for any errors or warnings that might indicate connectivity or database issues. 4. Timeouts and Crashes: There are known issues where workers may crash or timeout, especially if tasks exceed expected execution times. Ensure that your tasks are not running into such timeouts, which might cause the worker to become unresponsive. See related GitHub issue. 5. Prefect Version: Ensure that you are using a compatible version of Prefect. Sometimes, bugs are fixed in newer releases, and updating might resolve the issue. If these steps do not resolve your issue, consider reaching out to the Prefect community or support for more detailed troubleshooting based on your specific setup.

@Marvin I don't see any errors in the stdout or stderr from the worker. It just says

Worker 'myworker' started!

and is waiting.

If the worker logs show that it started successfully and is simply waiting, it suggests that the worker might not be detecting tasks in the queue. Here are a few more steps to consider: 1. Queue and Work Pool Configuration: Double-check the configuration of your work queue and work pool. Ensure that the worker is indeed polling the correct queue. You might want to check the Prefect UI to verify the queue assignments and ensure that there are no misconfigurations. 2. Worker Polling: Workers poll the queue at a regular interval. If the interval is too long, it might seem like the worker is not picking up tasks. You can adjust the polling frequency in the worker configuration if needed. 3. Task State Transition: Since tasks are moving from "Scheduled" to "Late," there might be a delay in state transition or a mismatch in expected execution times. Verify that the task scheduling and timing configurations are correct. 4. API Connectivity: Ensure that the worker can communicate effectively with the Prefect API. Any connectivity issues might prevent it from retrieving tasks. This can sometimes happen due to network changes or firewall settings. 5. Prefect Version and Dependencies: Ensure that both the Prefect version and any related dependencies are up to date. Sometimes, issues arise from mismatched versions or missing dependencies. If the issue persists, you may want to consider increasing logging verbosity to capture more detailed logs that might provide further insights into the problem. Additionally, reaching out to the Prefect community or support might help uncover any less common issues affecting your setup.

@Marvin the work pool in the prefect UI says

Work pool has at least one online worker ready to execute work.

and has the glowing green light. I also see

Last Polled

showing some tesns of seconds as normal, so I assume this means the worker is talking to the database correctly

Given that the work pool indicates an online worker and the polling appears normal, it seems the basic connectivity and worker status are functioning as expected. Here are a few additional considerations: 1. Task Compatibility: Ensure that the tasks in the queue are compatible with the worker's environment. If there are any dependencies or environment-specific configurations required by the tasks, verify that the worker's environment is correctly set up to handle them. 2. Queue Prioritization: Check if there are any priority settings or conditions that might be affecting task execution. Sometimes, tasks with certain priority levels or conditions might not be picked up as expected. 3. Resource Constraints: Verify that there are no resource constraints on the worker that might prevent it from executing tasks. This includes CPU, memory, or any other resource limitations. 4. Inspect Task Details: Look into the specific details of the "Late" tasks in the Prefect UI. There might be clues or logs associated with these tasks that could provide insights into why they are not being picked up. 5. Restarting Components: While you've restarted the worker, consider restarting other components like the Prefect server or any related infrastructure that might be involved in task scheduling and execution. If none of these steps resolve the issue, it might be beneficial to consult the Prefect community forums or support for more tailored troubleshooting based on your specific configuration and setup.

@Marvin Restatring the server also made no difference here

Given that the worker and server seem to be functioning correctly in terms of connectivity and status, yet tasks remain in the "Late" state, consider these additional steps: 1. Task and Flow Configuration: Double-check the configuration of your tasks and flows for any conditions or constraints that might prevent execution. This includes task dependencies, retries, and any resource requirements that might not be met. 2. Worker Logs: While you've mentioned no errors in the logs, consider increasing the verbosity of the logs to capture more detailed information. This might reveal subtle issues not immediately apparent in standard logs. 3. Prefect Version: Ensure that both the server and worker are running the latest compatible version of Prefect. Sometimes, issues are resolved in newer releases. 4. Task State Investigation: In the Prefect UI, inspect the details of the "Late" tasks. Look for any clues in the task state history or logs associated with these tasks. 5. Community and Support: Given the complexity and specificity of the issue, reaching out to the Prefect community forums or support might provide insights from others who have faced similar issues. If none of these steps resolve the issue, it might be beneficial to perform a more in-depth review of the system's configuration and any recent changes that could have affected task scheduling and execution.

@Marvin when the workers went offline yesterday, many of these messages were sent (here is the prefect server log part)

10:44:44.668 | INFO    | apprise - Notifying 1 service(s) asynchronously.
10:44:44.668 | DEBUG   | apprise - Slack POST URL: <https://hooks.slack.com/services/><REDACTED> (cert_verify=True)
10:44:44.668 | DEBUG   | apprise - Slack Payload: {'username': 'Prefect Notifications', 'mrkdwn': True, 'attachments': [{'title': 'My Process!', 'text': 'Flow run run/vagabond-badger observed in state `Crashed` at 2025-01-16 10:44:44.051730+00:00.\nFlow ID: 73418c18-cce5-4df8-a312-6a3ec0023f47\nFlow run ID: e9c532ab-bec5-4809-b3b4-04e1a03ddd35\nFlow run URL: None\nState message: Flow run infrastructure exited with non-zero status code 1.', 'color': None, 'ts': 1737024284.6684716, 'footer': 'Prefect Notifications'}]}

In addition I see many of hese in the prefect server log

10:44:43.626 | WARNING | prefect.server.utilities.messaging.memory - Message failed after 4 retries and will be moved to the dead letter queue

but have been seeing those from long before yesterday as well so not sure if they are related

Your message was too long by 47 tokens...

@Marvin when the workers went offline yesterday, many of these messages were sent (here is the prefect server log part)

10:44:44.668 | INFO    | apprise - Notifying 1 service(s) asynchronously.
10:44:44.668 | DEBUG   | apprise - Slack POST URL: <https://hooks.slack.com/services/><REDACTED> (cert_verify=True)
10:44:44.668 | DEBUG   | apprise - Slack Payload: {'username': 'Prefect Notifications', 'mrkdwn': True, 'attachments': [{'title': 'My Process!', 'text': 'Flow run run/vagabond-badger observed in state `Crashed` at 2025-01-16 10:44:44.051730+00:00.\nFlow ID: 73418c18-cce5-4df8-a312-6a3ec0023f47\nFlow run ID: e9c532ab-bec5-4809-b3b4-04e1a03ddd35\nFlow run URL: None\nState message: Flow run infrastructure exited with non-zero status code 1.', 'color': None, 'ts': 1737024284.6684716, 'footer': 'Prefect Notifications'}]}

The log message indicates that some of your flow runs transitioned to a "Crashed" state when the workers went offline. This state transition could be affecting the subsequent scheduling and execution of tasks. Here are some things to consider: 1. State Transition Handling: When a flow run crashes, it might prevent subsequent tasks from executing or being picked up by workers. Inspect the crashed flow runs in the Prefect UI to understand the cause and determine if any manual intervention is needed to reset or retry these runs. 2. Notification System: The log shows that notifications were sent out, which means there might be an alerting mechanism in place. Ensure that any automated actions triggered by these alerts are not interfering with the normal operation of your flows. 3. Flow Recovery: Depending on your setup, you might need to manually reset or restart the affected flow runs. Check for any automated recovery mechanisms and ensure they are functioning correctly. 4. Infrastructure Exit Codes: The message indicates that the flow run infrastructure exited with a non-zero status code. Investigate the underlying cause of this exit code, as it might provide insights into why the flows crashed. 5. Worker Recovery: After resolving the crashed flows, ensure that the worker is correctly configured to resume processing tasks. This might involve clearing any backlog or resetting specific states. By addressing these areas, you should be able to resolve the issue and ensure that tasks are picked up and executed as expected. If the problem persists, further investigation into the specific configurations and logs of your Prefect environment may be necessary.

@Marvin In addition I see many of these in the prefect server log

10:44:43.626 | WARNING | prefect.server.utilities.messaging.memory - Message failed after 4 retries and will be moved to the dead letter queue

but have been seeing those from long before yesterday as well so not sure if they are related

The warning message about messages being moved to the "dead letter queue" indicates that certain messages could not be processed successfully after multiple attempts. While this has been happening before the current issue, it might still be related or indicative of underlying problems in the system. Here's how you can approach this: 1. Dead Letter Queue: Investigate the contents of the dead letter queue. Understanding what messages are failing might provide insights into potential misconfigurations or issues with specific tasks or flows. 2. Impact Assessment: Determine if the messages in the dead letter queue are related to critical operations or workflows. If they are, resolving these failures might help in stabilizing the system overall. 3. Retry Logic: Examine the retry logic and the reasons why these messages are failing. It could be due to transient issues, configuration errors, or resource constraints. 4. System Health: Review the overall health of the Prefect server and related components. Persistent warnings like this could indicate broader issues that might affect task scheduling and execution. 5. Logs and Metrics: Check other logs and metrics for any patterns or anomalies that coincide with the message failures. This might help pinpoint the root cause. While these warnings might not be directly causing the current issue with tasks not being picked up, addressing them could improve the reliability and performance of your Prefect setup. If the problem persists, consider reaching out to the Prefect community or support for more targeted assistance.

@Marvin i tried redoing the deployments and starting the runs, but they are still not being picked up by the worker

Given the persistence of the issue despite recreating deployments and starting new runs, let's consider a few more targeted actions: 1. Worker and Queue Reconfiguration: Double-check the worker's configuration to ensure it is correctly linked to the intended work queue. Sometimes, even minor misconfigurations can cause significant disruptions. 2. Deployment and Environment Verification: Ensure that the deployments are correctly configured with all necessary dependencies and environment variables. Verify that the worker's environment matches the requirements of the tasks. 3. Prefect Server Logs: Examine the server logs for any additional warnings or errors that might provide clues. Pay attention to any network-related issues or database connectivity problems. 4. Network and Firewall: Ensure there are no network or firewall rules that might be blocking communication between the worker and the Prefect server. 5. Prefect Version Consistency: Verify that all components (server, worker, and client) are running compatible versions of Prefect. Inconsistencies can sometimes lead to unexpected behavior. 6. Community and Support Engagement: Given the complexity and persistence of the issue, engaging with the Prefect community or support might provide insights or solutions that are specific to your setup. If these steps do not resolve the issue, it may be necessary to conduct a more comprehensive review of your Prefect environment, including any recent changes or updates that could have affected its operation.

@Marvin the solution here was just to • delete the work pool and deployemnt from the server • redo the deployments and runs Then the works started to pick up the jobs Is this perhaps a bug?

It seems that deleting and recreating the work pool and deployments resolved the issue, which suggests there might have been a misconfiguration or a state inconsistency within the Prefect server. Here are a few considerations: 1. Potential Bug: It's possible that this behavior is indicative of a bug, particularly if the system state became inconsistent after the worker went offline. Such issues can sometimes arise when components are not fully in sync. 2. State Corruption: There may have been some form of state corruption or misalignment between the server and the worker, which was resolved by recreating the work pool and deployments. 3. Reporting the Issue: If you suspect this is a bug, it would be beneficial to report it to the Prefect team. Providing details about your setup, the steps you took, and the logs you observed can help them diagnose and address any underlying issues. 4. Preventive Measures: For future occurrences, consider documenting the steps you took to resolve the issue and monitor for any patterns or recurring problems that might indicate a systemic issue. If you decide to report this as a bug, you can do so on the Prefect GitHub issues page. This will help the developers investigate and potentially fix the issue in future releases.