Hi @Marvin when a worker executing a flow gets killed or crashes, it leaves the flow in a dangling

running

state on the self-hosted Prefect server. This happens despite the worker being marked as unhealthy on the server when heartbeats from the worker stop arriving. How can correct flow statuses on the server be achieved when workers disappear?

When a worker that is executing a flow gets killed or crashes, you can help correct the flow statuses on the server by using state change hooks. These hooks enable you to manage infrastructure cleanup or take other actions when flow runs change state, such as entering a Crashed state. The State Change Hooks guide provides information on how to create hooks that can help you manage these state changes. This guide discusses using hooks for cleanup, but the concepts could also be extended to reset the flow run state if necessary. For more control over infrastructure configuration and execution environments, Prefect introduced workers that poll work pools and execute flow runs. You may find more details about using and managing workers in the Workers overview. In addition, if you are using an ECS worker, you have the option to monitor and manage task statuses. The documentation on using ECS with Prefect provides insights into how flow runs are handled on AWS ECS, but it might not be directly related to handling crashes or killed workers (ECS Worker documentation). If you're looking for more specific behavior such as automatically updating the status of a flow run when a worker disappears, you may want to check GitHub issues to see if there is an existing discussion or feature request related to this matter. Would you like me to check there for you?

@Marvin The problem I'm facing is that a killed or crashes worker does NOT result in a flow status change to begin with.

The latest version of Prefect at the moment is 2.18.3, which may have updates related to how engine and deployment runs are wired up. However, there was no specific mention of a fix for issues related to worker crashes and flow run status updates. The documentation did not specifically mention what happens to the flow status update when a worker crashes or is killed. However, work pool behavior and priority queues for flow run submission were described in the documentation, which may have implications on how flow runs are managed after a worker is lost. From the GitHub issues search, there is no open issue that directly mentions flow run status not updating after a worker crash. One issue was found mentioning a

MissingResult

state when a worker's memory overflows, but this may not be directly related to your case. Another issue mentions random 500 Internal Server Errors, which could potentially lead to flow runs behaving unexpectedly, but it does not specifically discuss worker crashes. Given this, it seems that there might not be a clear solution from the existing documentation or open issues. It may be possible that there is currently no built-in mechanism in Prefect Server to handle such cases or it might have been overlooked. It might be necessary to manage this situation with custom logic that checks worker health and manually updates flow run statuses as needed. If your particular case is not covered by existing issues and you believe this is an oversight or a bug, it may be beneficial to open a new issue in the Prefect GitHub repository to report this behavior and seek guidance from the Prefect development team. Would you like assistance with anything else or further guidance on this issue?

@Marvin does the agent receive the flow_run_id when it starts executing a flow and can I access this ID from within a task?

To access the

flow_run_id

from within a task in Prefect, you can make use of the

get_flow_run_id

function from the

prefect

library, which returns the ID of the current flow run. Here's an example of how you can access it within a task:

python
from prefect import task, flow
from prefect.context import get_run_context

@task
def my_task():
    context = get_run_context()
    flow_run_id = context.flow_run_id
    print(f"The flow run ID is: {flow_run_id}")

@flow
def my_flow():
    my_task()

my_flow()

In this code snippet, the

get_run_context

function is used to obtain the current run context, from which the

flow_run_id

is extracted and printed. Please note that the

get_run_context

function is available in recent versions of Prefect, and the above code is for illustrative purposes. You might need to adapt this approach based on your Prefect version and the specific details of your flow and tasks. Unfortunately, there weren't direct links relevant to this topic in the search results. However, using run context has been a common practice to access metadata like

flow_run_id

in tasks. If you're not using one of the latest versions of Prefect or if you have any issues with the above, please refer to the specific version of the Prefect documentation that corresponds with the version you are using.

@Marvin how can I retrieve the if of the flow_run. The run_contexts seems to hold the flow_id only, but not the ID of the flow_run

To retrieve the ID of the current flow run within your task or flow, you can use the

FlowRunContext

object that is part of Prefect's context management. According to the documentation, you can access the flow run context directly, which will allow you to access various attributes of the flow run, including the ID. Here's an example of how you can access the

flow_run_id

within a task:

python
from prefect import task, flow
from prefect.context import FlowRunContext

@task
def my_task():
    flow_run_ctx = FlowRunContext.get()
    if flow_run_ctx:
        flow_run_id = flow_run_ctx.flow_run_id
        print(f"The flow run ID is: {flow_run_id}")
    else:
        print("No flow run context available.")

@flow
def my_flow():
    my_task()

my_flow()

In this code snippet, the

FlowRunContext.get()

method is used to obtain the flow run context, from which the

flow_run_id

is extracted. If the context is not available (for example, when not in a flow run), it will return

None

rather than raising an exception. For more detailed information, you can check the documentation for runtime context which outlines the use of run context in Prefect. Please ensure that you are using a version of Prefect that supports this feature, as earlier versions may have different methods for accessing context and flow run IDs.