@Marvin I have over 1000 tasks that can be done in parallel. What's the best practice in submitting tasks? Should I submit them all at once or throttle submission?

It seems there was an issue with retrieving the latest Prefect version, and I need to confirm which version you're using to provide the most accurate advice. Could you please let me know whether you're using Prefect 2.x or 3.x? In general, when dealing with a high volume of tasks that can be executed in parallel, here are a few considerations: 1. Submit All at Once: Prefect is designed to handle many tasks concurrently, especially if you're using a robust orchestration environment. Submitting them all at once might work if your infrastructure can handle it. 2. Throttling: If you are concerned about overwhelming your system's resources (like memory, CPU, or network), you might consider throttling the submissions. This could help in maintaining system stability and preventing resource exhaustion. 3. Prefect Orchestration: Prefect Coordinators and Agents can help distribute tasks efficiently. Ensure you have enough agents and the coordinator is configured correctly to handle the load. 4. Scaling Workers/Executors: Depending on the scale, you might benefit from a dynamic scaling setup where workers or executors are scaled based on the task volume. 5. Monitoring and Logging: Keeping an eye on your system's performance and the logs can help you fine-tune the submission strategy. If you can provide your current Prefect version or additional details about your infrastructure, I can look into more specific guidance or tools provided by that version.

@Marvin perfect v2

In Prefect 2.x, managing the submission of a large number of parallel tasks can be optimized using concurrency controls. Here are some key practices based on the documentation: 1. Global Concurrency Limits: Prefect allows you to set global concurrency limits to control the maximum number of certain tasks allowed to run simultaneously. This can be useful to manage resources effectively and prevent overloads. For example, if you have tasks that rely on limited external resources, you can apply concurrency limits to those specific tasks to ensure they don't exceed certain thresholds. You can use the

concurrency

context manager to define limits in your tasks and flows. 2. Rate Limiting: If you need to throttle task submission to avoid overloading resources or to comply with external rate limits, you can use Prefect's rate limiting features, such as

rate_limit

, which acts as a bottleneck to control task submission rates. 3. Task Retries and Failure Handling: It's also important to consider task retries and failure mechanisms. Using retry strategies with exponential backoff can help manage transient errors, and implementing self-healing logic can improve resiliency. Here's some illustrative code regarding rate limiting from Prefect's documentation:

python
from prefect import flow, task
from prefect.concurrency.sync import rate_limit

@task
def my_task(i):
    return i

@flow
def my_flow():
    for _ in range(100):
        rate_limit("slow-my-flow", occupy=1)
        my_task.submit(1)

if __name__ == "__main__":
    my_flow()

For more detailed guidance, you can refer to the documentation on concurrency limits here. If you have additional questions or need further help setting up these configurations, feel free to ask!

@Marvin Task concurrency limit vs global concurrency limits

In Prefect 2.x, both task concurrency limits and global concurrency limits offer mechanisms for controlling the number of concurrent task executions, but they are applied at different levels and use cases: 1. Task Concurrency Limits: - Task concurrency limits are applied to specific tasks using task tags. These limits define the maximum number of concurrent task runs that can be in a Running state for tasks with a given tag. - This feature is particularly useful for managing resources when multiple tasks across different flows need to share constraints, like a specific database connection limit. You can set a concurrency limit by tagging a task and specifying a maximum number of concurrent runs allowed for that tag. - If a task has multiple tags with concurrency limits, the task will run only if slots are available for all tags. If no slots are available, task execution is delayed rather than aborted, except if a tag's concurrency limit is set to zero, which aborts new runs with that tag. 2. Global Concurrency Limits: - Unlike task concurrency limits, which apply to specific tasks, global concurrency limits apply across your entire Prefect environment. They are more about governance at a higher level rather than specific resource contention. - Global concurrency limits can be created, edited, and deleted using the Prefect CLI. These limits can control and govern the maximum number of specific types of concurrent operations at any one time throughout all workflows. - This is used for managing resource allocation broadly and providing higher-level constraints on how workflows utilize computational resources. If you're interested in setting up these limits, here are some helpful resources: - For details on setting task concurrency limits, refer to the documentation: https://docs-2.prefect.io/latest/concepts/tasks/ - For more information on global concurrency limits and their CLI commands, check the guide: https://docs-2.prefect.io/latest/guides/global-concurrency-limits/ Both tools are powerful in their respective use cases, so choose based on whether your orchestration needs are task-specific or require broader control across your Prefect environment.