> ## 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.

<AccordionGroup>
  <Accordion title="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>

  <Accordion title="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**.
  </Accordion>
</AccordionGroup>