@Marvin how do i apply a concurrency limit to a subflow?

To apply a concurrency limit to a subflow in Prefect 3.x, you'll need to use concurrency limits at the deployment or work queue level. Here's a concise guide: 1. Set Concurrency Limits: Concurrency limits for flow runs (including subflows) can be configured at the deployment, work pool, or work queue level. This can be done using the Prefect CLI, Prefect API, or Prefect Cloud UI. 2. Using Tags: You can also apply concurrency limits using tags. Create a concurrency limit for a specific tag and apply this tag to your subflow. This can be done programmatically using the

PrefectClient.orchestration.create_concurrency_limit

method. 3. CLI Commands: Use the Prefect CLI to manage concurrency limits: - `create`: Create a concurrency limit by specifying a tag and limit. - `delete`: Remove a concurrency limit for a specific tag. - `inspect`: View details about a concurrency limit. - `ls`: List all defined concurrency limits. For more detailed instructions, you can refer to the Prefect documentation on concurrency limits and global concurrency limits. If you're working with deployments, make sure to apply the concurrency limit to the specific deployment that includes your subflow. This way, the subflow will inherit the concurrency constraints. Feel free to ask if you need more specific examples or further guidance!

@Marvin like i just want subflow runs to be marked as scheduled/pending while the concurrency limit is reached

To ensure that subflow runs are marked as "scheduled" or "pending" when a concurrency limit is reached, you should utilize the concurrency limits feature at the deployment or work queue level. Here's a step-by-step approach: 1. Set Concurrency Limits: Use the Prefect CLI or Prefect API to set concurrency limits on your deployment. This will control how many instances of the flow, including subflows, can run concurrently. 2. Apply Tags: If you want to manage concurrency at a more granular level, apply specific tags to your subflows and set concurrency limits on those tags. 3. Scheduled/Pending State: When the concurrency limit is reached, additional subflow runs will automatically be placed in a "scheduled" or "pending" state until a slot becomes available. 4. Use the CLI Commands: - To create a concurrency limit:

prefect concurrency-limit create <tag> <limit>

- To check current limits:

prefect concurrency-limit ls

5. Programmatic Management: You can also manage concurrency limits programmatically using the

PrefectClient

. For example:

python
   from prefect.client.orchestration import PrefectClient

   async def set_concurrency_limit():
       async with PrefectClient() as client:
           await client.create_concurrency_limit(tag="subflow_tag", limit=5)

For more information, you can refer to the Prefect documentation on concurrency limits. If you encounter any issues where subflows do not behave as expected, consider checking for related issues in the Prefect GitHub repository.

@Marvin but a subflow is not deployed

If your subflow is not deployed and you want to apply concurrency limits to it, you can still manage concurrency using tags and the Prefect API. Here's how you can approach this: 1. Use Tags for Concurrency Control: Apply a specific tag to your subflow tasks and set a concurrency limit on that tag. This will ensure that tasks with that tag are limited in how many can run concurrently. 2. Programmatic Concurrency Management: Use the

PrefectClient

to create concurrency limits for specific tags. Here's a basic example:

python
   from prefect.client.orchestration import PrefectClient

   async def set_concurrency_limit():
       async with PrefectClient() as client:
           await client.create_concurrency_limit(tag="subflow_tag", limit=5)

3. Flow-Level Concurrency: If you want to control concurrency at the flow level without deploying, you can create a wrapper flow that includes your subflow and apply concurrency limits to the wrapper flow using tags or work queues. 4. CLI Commands: Use the Prefect CLI to create and manage concurrency limits: - To create a concurrency limit:

prefect concurrency-limit create <tag> <limit>

- To list concurrency limits:

prefect concurrency-limit ls

By using tags and the Prefect API or CLI, you can effectively manage concurrency for subflows even if they are not independently deployed. For more details, you can refer to the Prefect documentation on concurrency limits. If you need further customization or face specific issues, consider exploring the ControlFlow documentation for more advanced orchestration patterns.

@Marvin how often does concurrency() poll for slots? i’m finding that its not smoothly starting jobs when slots open up, and instead just starts a big batch all at once

The behavior you're observing with concurrency limits in Prefect may be influenced by the configuration of the

slot_decay_per_second

parameter. This parameter determines how quickly slots become available again after being occupied, effectively controlling the rate at which tasks can be scheduled. Here's how it works: - Slot Decay Rate: The

slot_decay_per_second

parameter sets the rate at which slots refresh. - A higher value (e.g., 5.0) means slots refresh quickly, allowing tasks to run more frequently with shorter pauses. - A lower value (e.g., 0.1) means slots refresh slowly, leading to longer pauses between task runs. For example: - With a decay rate of 5.0, you could run a task roughly every 0.2 seconds. - With a decay rate of 0.1, you’d wait about 10 seconds between task runs. If you're experiencing a large batch of jobs starting simultaneously, it might be due to a lower decay rate causing slots to become available in bursts rather than smoothly over time. Adjusting the

slot_decay_per_second

value could help achieve a more even distribution of task starts. For more details, you can refer to the Prefect documentation on global concurrency limits.

@Marvin what if its 0 because i just want to wait for the jobs to actually finish?

If you set the

slot_decay_per_second

to 0 because you want to wait for jobs to fully complete before new ones start, this effectively means that slots will only become available once the tasks occupying them have finished. This setup ensures that no new tasks will start until a slot is explicitly freed by a completed task. This approach should theoretically prevent any batch-like behavior, as slots are only released upon task completion. However, if you are still experiencing batch starts, it might be due to the polling mechanism or how the concurrency limits are being enforced in your environment. Here are a few considerations and steps you can take: 1. Polling Frequency: Ensure that the polling frequency of your work queue or the mechanism checking for available slots is set appropriately. If the polling interval is too long, it could delay the detection of freed slots, causing tasks to start in batches. 2. Concurrency Limit Configuration: Double-check the concurrency limit settings to confirm they are applied correctly. Any misconfiguration might lead to unexpected behavior. 3. Monitoring and Logs: Monitor the logs and task states to identify any patterns or delays in slot release and task start times. This can provide insights into whether the issue lies with the polling mechanism or elsewhere. 4. Prefect Version: Ensure you are using the latest version of Prefect, as updates may contain bug fixes or improvements related to concurrency handling. If these steps do not resolve the issue, consider reaching out to the Prefect community or checking for known issues in the Prefect GitHub repository.