# Compute Settings ## Stateful Compute For code execution zerve uses cloud compute (lambda or fargate or GPU) 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. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.zerve.ai/guide/canvas-view/blocks-and-connections/compute-settings.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.