@Marvin i'm running on prefect 2.x with Prefect Cloud, using an Agent on Google Kubernetes Engine. occasionally the status and logs from a flow run stop being received by Prefect Cloud in the middle of a Task, even though the task completes locally. In Prefect Cloud, the Task shows as running forever. what could be the cause?

It seems you're experiencing an issue where the Prefect Cloud sometimes fails to receive updates from a running task on your Google Kubernetes Engine (GKE) agent. Here are a few things that might be contributing to this problem: 1. Network and API Connections: Ensure that your agent on GKE is correctly configured with the Prefect API URL and API key, as any network issues could disrupt the connection to Prefect Cloud. Refer to the Prefect documentation on connecting to Prefect Cloud for more details. 2. Timeout and Retries: There might be a timeout setting that is being reached, or some retry logic might be necessary for the flow run submissions. You can consider implementing a retry mechanism for tasks that involve network interactions. Check out the GitHub issue on adding retries for infrastructure creations for some related information. 3. Service Account and Permissions: Configuring the correct service accounts with appropriate permissions is crucial. Make sure your service account is active and has the necessary IAM roles. Read more on GCP Gotchas when deploying Prefect with GKE. 4. Bug or Known Issues: There might be a bug affecting Prefect agents or workers, similar to the one mentioned in GitHub issue #15033, where the task state is not updated correctly. While there's no single silver bullet for this issue, you can start investigating based on these points. Consider setting up detailed logging in your tasks to trace where the connection might be breaking, and whether the agent is struggling with long-running tasks or timeout settings. If you continue to face issues, consider reaching out to the Prefect community for more targeted assistance.

@Marvin would task-level timeouts help with this issue?

Yes, implementing task-level timeouts can help address the issue of tasks running indefinitely. Task timeouts in Prefect are used to prevent unintentional long-running tasks. If a task exceeds the specified timeout duration, a timeout exception will be raised, and the task will be marked as failed in the Prefect UI. Here is how you can add a timeout to a task:

python
from prefect import task
import time

@task(timeout_seconds=60, log_prints=True) # Timeout after 60 seconds
def my_task():
    print("Task is running")
    time.sleep(120) # Simulating a long task
    print("Task completed") # This line won't execute if timeout is reached

By setting a timeout, you ensure that tasks do not run longer than intended and can help in managing cases where tasks hang due to unforeseen issues. However, while this won't directly resolve the issue of logs not being sent to Prefect Cloud, it will help in mitigating scenarios where tasks are stuck without completing. For more detailed information, you can refer to the Prefect documentation on task timeouts.

@Marvin is the timeout enforced in Prefect Cloud or on the worker?

Task timeouts in Prefect are enforced on the worker level, not directly within Prefect Cloud. When you set a timeout, it is the worker executing the task that monitors the execution time and raises a timeout exception if the specified duration is exceeded. This means that the task will be marked as failed and the appropriate timeout state will be reported back to Prefect Cloud by the worker. This allows the system to manage task execution efficiently at the source. Let me know if you have any more questions or need further clarification!

@Marvin where are flow level timeouts enforced, Prefect Cloud or the worker?

Flow-level timeouts in Prefect are enforced similarly to task-level timeouts, meaning they occur on the worker executing the flow. When the duration of execution for a flow exceeds the specified timeout, a timeout exception will be raised, and the flow will be marked as failed by the worker. This state is then reported back to Prefect Cloud, where the flow run will be visibly designated as "TimedOut" in the user interface. This mechanism helps manage potentially long-running flows directly from the execution environment, ensuring that any delays or runaway executions are capably handled at the source. Feel free to reach out if you have further questions!

@Marvin are there any changes between version 2.10.20 and the latest 2.x that may help this issue?

The latest release notes for Prefect mention a bug fix related to served flows exiting early, which may not directly correlate with your issue of task logs and statuses ceasing to update. Therefore, this specific fix might not address the problem you're experiencing. Nonetheless, it's a good practice to regularly update to the latest version of any software to benefit from recent bug fixes and improvements. Given that updates might sometimes contain undocumented or indirect fixes, you might consider testing the later versions to see if they inadvertently resolve the issues you're encountering. If you wish to view more details or if any underlying updates might apply, you can check the full changelog for Prefect. Let me know if you need more help or further exploration of specific features!

@Marvin are prefect Agents supported in the latest 2.x version, 2.20.10 ?

In the latest version of Prefect 2.x, specifically 2.20.10, agents are still supported but with certain updates and changes. Prefect 2.x implements a more streamlined agent model with a singular generic agent type, which polls a work pool looking for flow runs. However, it's important to be aware that Prefect's overall architecture is evolving, especially with the move towards Prefect 3. Furthermore, there are deprecations and shifts in focus towards newer constructs such as workers. Some features, particularly specific infrastructure blocks, show deprecation notices indicating that they will be removed in future releases (e.g., Prefect 3). This includes a transition from older infrastructure agents to newer constructs like workers, which are already recommended in some documentation as the preferred approach see migration guide. For a seamless transition and to stay ahead with best practices, monitoring Prefect's updates and following guidelines in their migration and upgrade guides is advisable. Feel free to reach out if you need further details!