> For the complete documentation index, see [llms.txt](https://docs.zerve.ai/guide/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.zerve.ai/guide/notebook-view/blocks/compute-settings.md).

# Compute Settings

## Stateful Compute

For code execution zerve uses cloud compute (lambda, fargate, GPU or Kubernetes) at block level. When a block is run, zerve spins up relevant compute resources for code execution. 

Once successfully executed the results are cached, serialized and stored on disk. This is built on top of a canvas environment for true collaboration and uses DAG workflow to process code execution order.

Post successful code execution data is stored on disk separate from compute. This creates a stable environment to do data science and removes all the shortcomings that we get from a normal jupyter notebook.