@Marvin how do I only get one job to run on the machine that has 1 docker worker? If I have 2 docker workers, 1 per machine, I want 1 job per machine.

To limit jobs to one per Docker worker, you can use concurrency limits in Prefect through task tags. This approach applies to both Prefect 2.x and 3.x versions. Here's a concise approach to achieve your aim: 1. Task Tags with Concurrency Limits: Use task tags to set concurrency limits. Assign the same tag to each task you want to limit to a particular worker and set its concurrency limit to 1. 2. Configure Limits via CLI: You can set these limits using the Prefect CLI. Here's an example command to create a concurrency limit for a specific tag:

prefect concurrency-limit create <TAG_NAME> 1

This command will restrict the concurrent execution of tasks with this tag to one at a time. 3. Flow Concurrency Limits: Beyond task limits, you can also set flow run concurrency limits at the deployment level, addressing scenarios with multiple worker nodes. Find more detailed instructions from the Prefect Docs: - Prefect 2.x Task Concurrency - Prefect 3.x Task Concurrency Now you can control worker tasks like a traffic warden organizing orderly queueing, ensuring there's never a crowded machine. If only all multitasking were this manageable!

@Marvin tasks can't even run on different machines unless you use dask or ray, so this is not relevant at all. On cloud infra, you can do this memory_limits. In combination with concurrency limits

It seems I might have misunderstood your setup. When you're dealing with Prefect, especially in distributed systems like with Dask or Ray, indeed these frameworks handle the task distribution across different nodes. If you're on Prefect Cloud and want to manage the distribution and resource allocation, especially for memory, you might look into the following options: 1. Dask/Ray Task Management: Using Dask or Ray, you can manage task distribution across multiple machines. These frameworks allow specifying memory, CPU, and other resource limits which ensure that tasks only consume a given amount of resources, effectively limiting how tasks are scheduled on workers. 2. Resource Constraints: On cloud infrastructure, set memory and CPU constraints within your Dask or Ray configuration. This helps in preventing more than one task from running simultaneously if the available resources for additional tasks are exhausted. For a deeper dive into configuring resources with Dask or Ray, you might want to explore: - Dask Documentation: Dask Resource Management - Ray Documentation: Ray Resource Management I sometimes wonder why not all multitasking could be as orderly as this. Nonetheless, feel free to ask if you have more questions about Prefect configurations or any other topic!

@Marvin My machine has 32GB of memory and I set the memory limit of my docker workpool to be 12GB. Although I set this limit, I still see more than 2 flows running at once. Why is this happening?

If you set a memory limit of 12GB on your Docker work pool but observe more than two flows running concurrently, there might be a few explanations: 1. Work Queue Concurrency: Prefect allows setting concurrency limits at the work queue level. If the work queue doesn't have strict concurrency limitations, it might allow more flows to run than anticipated. Check the concurrency settings and configure them to restrict the number of concurrent flows. 2. Work Pool Memory and Concurrency Limits: Ensure that the memory limit is enforced at the work pool level. It's possible to have discrepancies between what's configured and what's effectively applied, especially if the configuration doesn't propagate down to the pool's worker level. 3. Multiple Work Queues: If your work pool includes multiple work queues with different concurrency settings, this could lead to more flows running if not all are subject to the same restrictions. 4. Prefect Version: Depending on whether you're using Prefect 2.x or 3.x, the configuration might differ slightly. Ensure that you're using the correct version's documentation and settings. Review these sections on concurrency and limiting in Prefect's documentation: - Prefect 2.x Managed Execution - Prefect 3.x Infrastructure and Work Pool Concepts If only task management were as straightforward as an assembly line—one job gets done before the next minefield of issues begins! If you need further assistance, feel free to ask.

@Marvin How do I make a docker workpool only have 1 flow run per machine and set a memory requirement so that I can make sure that the machine I am running on has sufficient memory and two flow won't be scheduled on the same machine because they both require >50% of the machine's memory

To ensure that your Docker work pool only has one flow run per machine and set memory requirements effectively, you can follow these steps: 1. Limiting to One Flow Per Machine: - Concurrency Limits: Set a concurrency limit on your work pool or queue to ensure that only one task can run on the machine at a time. This will prevent more than one flow from running concurrently on a single machine. - You can configure this via the CLI or the Prefect API. For example, you might use:

prefect concurrency-limit create <tag_or_queue_name> 1

2. Setting Memory Requirements: - Prefect Infrastructure Settings: When defining your Docker work pool, specify the resource constraints you require for each flow run, particularly the memory limit, ensuring it's less than your machine limit but sufficient for your task. - This can be specified in the Prefect YAML configuration for your deployment or directly in the Prefect UI if you're using Prefect Cloud. 3. Prefect YAML Example: - Here's a snippet of how you might configure these settings in a Prefect YAML file:

yaml
     work_pool:
       type: docker
       memory: 12G  # Memory limit per flow run

By combining concurrency limits with specific resource settings in your configuration, you can ensure that only one flow is assigned to each machine, while also managing the required memory resources. For detailed configuration options and examples, you might want to check: - Prefect 2.x Work Pools Documentation - Prefect 3.x Infrastructure Concepts for Work Pools Now your flows can strut around with all the space they need, without tripping over one another like in some bizarre flow-running marathon! If there's more I can help with, just ask.