@Marvin in prefect 2.x if i have a timeout_seconds on a flow decorator. what should i expect to see when the timeout occurs?

In Prefect 2.x, if you specify a

timeout_seconds

on a flow decorator and the flow exceeds this time limit, a timeout exception will be raised. Consequently, the flow will be marked as failed, and in the Prefect UI, you will see it designated as "TimedOut". This serves as a mechanism to prevent unintentional long-running flows. For more detailed information, you can check out the Prefect 2.x documentation here. Ah, timeouts—nature's way of telling your code, "Nap time is over!"

@Marvin does this error message relate to the timeout setting ? aiohttp.client_exceptions.ClientOSError: [WinError 121] The semaphore timeout period has expired

The error message you're encountering,

aiohttp.client_exceptions.ClientOSError: [WinError 121] The semaphore timeout period has expired

, isn't directly related to the flow timeout setting in Prefect. Instead, this error usually stems from network-related issues. It indicates that a network operation took too long to complete and the semaphore timeout for that I/O operation expired. Such errors can occur due to various reasons, such as unstable network connections, server-side slowdowns, or misconfigurations in the network setup. It can also be caused by extended delays in network communication, unrelated to the flow execution's timeout logic in Prefect. If you need to dive deeper into this specific issue, you might want to check your network settings or consider if there are any proxy or firewall configurations that might affect network operations. And if all else fails, you could consider it a sign from the digital cosmos to perform a ritual known as "turning it off and on again."

@Marvin within the specific flow i see this error. and chance this helps better shape the issue Crash detected! Execution was cancelled by the runtime environment.

The error message "Crash detected! Execution was cancelled by the runtime environment" suggests that the execution was stopped unexpectedly by an external factor, rather than something like a Prefect flow timeout. This could happen due to various reasons, such as resource constraints, abrupt termination signals, or issues related to the runtime environment itself. I found a related GitHub issue here where users experienced similar crashes in Prefect flows. In that particular case, asynchronous tasks and the runtime environment seemed to be factors in the problem. Here are some things you might want to consider or investigate: 1. Resource Limits: Check if your environment has sufficient resources (CPU, memory, etc.) to handle the flow execution. 2. System Constraints: Ensure that there are no system-level issues or limits being hit (like file descriptor limits or network constraints). 3. Code Configuration: Make sure the code that deploys or runs your Prefect flows is correctly configured to manage async tasks without hitting runtime limits or deadlocks. 4. External Termination: Verify if the runtime environment (e.g., container orchestrator, server configurations) isn't forcibly terminating the task or container. 5. Upgrade Prefect: Check if upgrading to a newer version of Prefect mitigates the issue, as bug fixes and improvements often come with updates. Unfortunately, without more concrete diagnostics from the environment, pinpointing the exact cause can be a bit of detective work. But it's worth looking into these potential areas.

@Marvin do you have any recommendations for how to use the timeout_seconds with the flow decorator?

When using the

timeout_seconds

with the flow decorator in Prefect 2.x, here are some recommendations to keep in mind: 1. Purpose: Use the

timeout_seconds

parameter to prevent unintended long-running flows. It's helpful for ensuring that your flow doesn't exceed a certain execution time, which can be crucial for resource management and system predictability. 2. Specification: You specify the timeout duration by passing the

timeout_seconds

keyword argument to the flow decorator. For example:

python
   from prefect import flow
   import time

   @flow(timeout_seconds=10)
   def my_flow():
       time.sleep(15)
       print("This will not execute if timeout is 10 seconds")

3. Behavior: If the execution time exceeds the timeout duration, a timeout exception is raised, and the flow is marked as failed. You'll also see it marked as "TimedOut" in the UI. 4. Testing: It's a good practice to test your flow with smaller timeout values initially, to ensure that the timeout mechanism is working as expected before applying it in a production setting. 5. Logging: Consider using the

log_prints=True

parameter along with the timeout, to ensure you have logging enabled for debugging purposes. Here's an example provided in the Prefect documentation:

python
from prefect import flow
import time

@flow(timeout_seconds=1, log_prints=True)
def show_timeouts():
    print("I will execute")
    time.sleep(5)
    print("I will not execute")

More information can be found in this section of the Prefect documentation. Remember, like setting an alarm clock,

timeout_seconds

should be set thoughtfully to match your flow's expected execution pattern.