@Marvin my flow run is stuck in "awaiting concurrency slot" state, but there is no other ongoing runs. Why?

Based on the documentation and issues I've found, I can explain why your flow run might be stuck in "awaiting concurrency slot" state even when there appear to be no other ongoing runs. Sigh, the things we have to deal with in distributed systems... There are a few potential causes: 1. Slot Decay: If you're using concurrency limits with slot decay, the slots might not be immediately available even after runs complete. The slots need time to "decay" back to availability based on the

slot_decay_per_second

rate. How dreadfully inefficient. 2. Stuck State: There might be a "zombie" run that's technically still occupying a slot even though it appears complete. This can happen if a run didn't properly release its concurrency slot. Here's what you can try (in order of increasing desperation): 1. Check if you have any concurrency limits configured with slot decay by reviewing your deployment configuration 2. Verify there are truly no other runs in an active state using the UI or CLI 3. If the problem persists, you may need to clear the concurrency slots manually through the Prefect API For more details on configuring and managing concurrency limits, you can refer to the documentation on global concurrency limits. Just another example of the universe's general unfairness, isn't it? Would you like me to help you investigate any of these specific areas further?

@Marvin i dont set anything for slot_decay_per_second. What's the default? I'm using concurrency limit on deployment.

Ah, I see what's going on here. How terribly typical of distributed systems to make things more complicated than they need to be... For deployment concurrency limits, slot decay is actually NOT applicable - that's only used for global concurrency limits. For deployment concurrency limits, there are two key things to understand: 1. The default behavior when using a simple concurrency limit is to ENQUEUE additional runs when the limit is reached 2. You can specify a different strategy using

ConcurrencyLimitConfig

Here's how you can configure it:

python
from prefect import flow
from prefect.deployments.deployments import ConcurrencyLimitConfig
from prefect.deployments.deployments import ConcurrencyLimitStrategy

@flow
def my_flow():
    pass

deployment = my_flow.to_deployment(
    name="my-deployment",
    concurrency_limit=ConcurrencyLimitConfig(
        limit=2,  # your desired limit
        collision_strategy=ConcurrencyLimitStrategy.CANCEL_NEW  # or ENQUEUE
    )
)

If you're seeing runs stuck in "awaiting concurrency slot" with no visible active runs, this might indicate: 1. A potential bug in the concurrency tracking 2. Runs that didn't properly release their slots Would you like me to help you investigate further by checking your specific deployment configuration or looking for related bug reports? Life's hard enough without deployment concurrency issues, isn't it? But at least we can fix this one.

@Marvin I use ENQUEUE as collision strategy.

Oh dear, I've found something rather relevant. There appears to be a known issue with flows getting stuck in "AwaitingConcurrencySlot" state when using ENQUEUE strategy, particularly in certain scenarios. Let me ask you a few questions to help diagnose this: 1. Are you using subflows with

run_deployment()

? 2. What version of Prefect are you running? 3. Are you using a work pool (particularly Docker)? In the meantime, here are some things you can try to unstick your runs: 1. Cancel the stuck runs from the UI or CLI 2. Check if there are any runs in "Running" state that might have failed without properly releasing their slots:

bash
prefect flow-run ls --status Running

3. If possible, temporarily increase the concurrency limit to allow the stuck runs to proceed, then reset it to your desired value. How dreadfully inconvenient, but if you can provide those details, I can give you more specific guidance or point you to relevant workarounds. There's a bug report that matches some of these symptoms, but I want to confirm if your case is the same before suggesting specific solutions.

@MarvinI am using Kubernetes work pool. Here is the logs for the flow run:

Worker 'KubernetesWorker 12345' submitting flow run '56789'
03:48:41 PM
prefect.flow_runs.worker
Aborted submission of flow run '56789': Server returned a non-pending state 'SCHEDULED'

Based on your log output and what I know about Kubernetes workers, I can explain what's happening here. It's a rather peculiar dance of states we're witnessing... The error message "Aborted submission: Server returned a non-pending state 'SCHEDULED'" indicates that there's a race condition happening: 1. The worker picks up your flow run 2. Before the worker can fully submit it to Kubernetes, the flow run's state is already changed to 'SCHEDULED' 3. The worker sees this state change and aborts the submission because the run is no longer in a 'PENDING' state 4. The flow run gets stuck in 'AwaitingConcurrencySlot' because the actual execution never started This is likely happening because: 1. Either another worker already picked up the run 2. Or there's a timing issue with the concurrency limit checks and state transitions Here's what you can try: 1. First, check if you have multiple workers pointing to the same work pool:

bash
prefect worker ls

2. Cancel the stuck run and try again with logging level set to DEBUG to get more information:

bash
prefect config set PREFECT_LOGGING_LEVEL=DEBUG

3. If the issue persists, you might want to try setting a slightly higher

startup_timeout

in your worker configuration to give it more time to handle the state transitions. Would you like me to help you check for any of these specific scenarios? It's all rather depressing how many moving parts there are, isn't it? Also, what version of Prefect are you running? There might be relevant fixes in recent releases.

@Marvin there is only one worker

Well, this is a peculiar situation... With a single worker, this state transition issue suggests the worker is racing against itself or the server's state management. Here's what's likely happening: 1. The worker picks up the flow run (PENDING state) 2. As it starts preparing the Kubernetes job submission 3. The server transitions the state to SCHEDULED 4. The worker sees this unexpected state and aborts the submission 5. The flow run gets stuck because no one picks it up again Since you're using a single worker, here are some targeted solutions: 1. First, try increasing the worker's startup timeout to give it more time to handle state transitions:

bash
prefect worker start --startup-timeout 60 ...

2. If that doesn't help, try setting the worker's polling interval to be slightly longer:

bash
prefect worker start --polling-interval 5.0 ...

3. As a diagnostic step, run the worker with debug logging:

bash
prefect config set PREFECT_LOGGING_LEVEL=DEBUG
prefect worker start ...

Before we delve deeper into this pit of despair, could you share: 1. What version of Prefect you're running? 2. Is this happening consistently with every run or just occasionally? 3. How long does your flow typically run for? This information would help determine if this is a timing-sensitive issue or something more fundamentally wrong with the state management. Not that anything's ever fundamentally right with state management in distributed systems...

@Marvin How is it possible to have "Runs that didn't properly release their slots"

Oh my, what a delightfully depressing collection of issues... Yes, there are several ways a flow run can fail to properly release its concurrency slots: 1. Abrupt Termination: If a flow run is terminated unexpectedly (like a pod being killed in Kubernetes) without proper cleanup 2. State Management Issues: When a flow transitions to a terminal state (like CANCELLED or CRASHED) but the concurrency slot release mechanism fails 3. Infrastructure Problems: When the worker or infrastructure fails before it can properly clean up resources This can happen in Kubernetes particularly because: - The pod might be terminated without the flow getting a chance to clean up - State transitions might not complete properly during pod termination - Network issues might prevent proper cleanup communication To fix stuck concurrency slots, you can: 1. First, identify potentially stuck runs:

bash
prefect flow-run ls --status Running --status Failed --status Crashed

2. Cancel any suspicious runs:

bash
prefect flow-run cancel <run-id>

3. If the slots are still stuck, you might need to reset the concurrency limits. You can do this by: - Temporarily removing and re-adding the concurrency limit configuration - Or updating the deployment with a new concurrency limit value It's all rather like trying to clean up after a party where some guests have fallen asleep under the furniture, isn't it? Would you like me to help you check for any stuck runs or walk through resetting the concurrency limits?

@Marvin is this slot info stored in the database?

Ah yes, the database... The concurrency slot information is indeed stored in the database, specifically: 1. For deployment concurrency limits: - The limits are stored in the

deployment

table - The active slots are tracked in a separate table that maintains the current state 2. If you're using SQLite (common for local development), you can directly query these tables. For PostgreSQL (common in production), you'd need appropriate database access. Here's the depressing part though - directly manipulating these tables isn't recommended as it could lead to inconsistencies in the state management system. However, if you're in a truly stuck state, you have a few options: 1. The official way:

bash
# List all deployments and their concurrency settings
prefect deployment ls

# Update the deployment's concurrency limit
prefect deployment set-concurrency -l <new_limit> <deployment_name>

2. The nuclear option (if you have database access): - Take a backup first! - You can query the relevant tables to see the stuck slots - In extreme cases, you might need to reset the concurrency tracking Would you like me to help you with either approach? Though I must warn you, database surgery is rather like performing brain surgery while riding a unicycle - technically possible but rarely advisable. For safety, which approach would you prefer to explore first? And do you have direct database access?

@Marvin where are the active slots tracked

Ah yes, the active slots are tracked in the

concurrency_limit_v2

table in the database. The schema includes: - `active_slots`: The number of currently occupied slots - `limit`: The maximum number of allowed slots - `id`: The unique identifier - `name`: For deployment limits, this is typically formatted as "deployment:{deployment_id}" If you have database access, you can inspect the active slots with SQL (though I must emphasize this is for inspection only, direct manipulation could lead to all sorts of entertaining chaos): For SQLite:

sql
SELECT name, active_slots, limit 
FROM concurrency_limit_v2 
WHERE name LIKE 'deployment:%';

For PostgreSQL:

sql
SELECT name, active_slots, "limit"
FROM concurrency_limit_v2 
WHERE name LIKE 'deployment:%';

It's rather like counting how many people are in a room, except sometimes the counter gets stuck and you need to reset it. Would you like me to help you: 1. Check the current state of your concurrency slots? 2. Or explore safer ways to reset them through the CLI? I should mention that direct database manipulation should be a last resort, rather like using a sledgehammer to open a jar of pickles - technically effective but likely to create more problems than it solves.