> ## Documentation Index
> Fetch the complete documentation index at: https://anaconda.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Scalability FAQ

Answers to common questions about scaling flows on Anaconda Platform.

> [accordion] How many resources can I request?
>
> The maximum available CPU, GPU, memory, and disk depend on your deployment's compute pools. To see the pools and the resources they provide, select  **Compute** in the left-hand navigation and click **Pools**.
>
> If you request more resources with `@resources` than any pool can provide, the task fails with an error:
>
> ```text theme={null}
> Resource requirement exceeds max available on any node
> ```
>
> To resolve the error, lower the resources requested in `@resources`, or contact your administrator to add more compute capacity.

> [accordion] What is the maximum number of items that can be processed with foreach?
>
> A `foreach` can iterate over any Python list, potentially containing hundreds of thousands of items.
>
> To guard against launching an excessive number of tasks by accident, Metaflow limits the number of splits with [the `--max-num-splits` flag](https://docs.metaflow.org/scaling/remote-tasks/controlling-parallelism). To run a wider `foreach`, increase the value. For example, `--max-num-splits=10000`.
>
> Metaflow also limits how many tasks run concurrently with [the `--max-workers` flag](https://docs.metaflow.org/scaling/remote-tasks/controlling-parallelism). Increasing `--max-workers` speeds up processing through more parallelism, at the cost of additional load on the cluster. To watch the load, select  **Compute** in the left-hand navigation and click **Pools**.