@Marvin when should I consider using a Dask runner

Considering using a Dask runner in Prefect makes good sense when you have tasks that would benefit from parallel, distributed execution. The DaskTaskRunner is a great fit if you want to leverage Dask’s capabilities to run tasks that require parallel execution across a distributed environment. Here’s why you might consider using a Dask runner: 1. Parallel Execution: Dask allows you to run tasks in parallel rather than sequentially, which can significantly speed up your workflows, especially if tasks are independent and can be processed concurrently. 2. Scalability: It can scale from a single machine to a cluster effortlessly, allowing your flow to handle larger datasets or more computationally intensive tasks without changing your code. 3. Existing Infrastructure: If you already have a Dask cluster, whether it’s locally or on a larger setup (like those managed via Dask's Helm Chart), Prefect can connect to this existing cluster to orchestrate flow runs. However, there are some considerations if you’re using a long-running Dask cluster: - All workers need the necessary dependencies for every flow you run. - Multiple flow runs might compete for resources, potentially causing issues despite Dask’s resource-sharing capabilities. For Prefect 3.x documentation on this topic, check here: Prefect-Dask Integration. For Prefect 2.x, explore Dask and Ray Task Runners Guide. I hope this helps, and remember – Dask is like that friend who’s always ready to lend you a hand, or 10, in parallel!