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

# Kernels

> Kernels are the execution environments for your Datazone notebooks.

## Overview

A kernel is the computational engine that executes the code contained in a notebook. It acts as an isolated environment that:

* Processes the code you write
* Manages the memory and computations
* Returns the results back to your notebook

<Frame>
  <img src="https://mintcdn.com/datazone/YFojkVY1avf3O4H9/images/light/notebook/kernel-options.png?fit=max&auto=format&n=YFojkVY1avf3O4H9&q=85&s=196e5f8f2d21a7aadd601862eb15901c" alt="kernel-options" width="2160" height="2700" data-path="images/light/notebook/kernel-options.png" />
</Frame>

## Available Kernel Images

Datazone provides two main kernel images:

* **Python**: Standard Python environment with common data science libraries
* **Python Pyspark**: Python environment with Apache Spark support for distributed computing

## Compute Resources

You can select from different compute sizes based on your workload:

| Size | Resources | Best for |
| - | - | - |
| **X-Small** | 2 vCPU, 8 GB RAM | Light data processing, simple scripts |
| **Small** | 4 vCPU, 16 GB RAM | Standard data analysis, medium datasets |
| **Medium** | 8 vCPU, 32 GB RAM | Heavy computations, large datasets |
| **Large** | 16 vCPU, 64 GB RAM | Big data processing, complex analytics |
| **X-Large** | 32 vCPU, 128 GB RAM | Enterprise-level distributed computing |

## Environment Variables

Before initializing a kernel, you can set custom environment variables to:

* Configure access credentials
* Set runtime parameters
* Define application-specific settings
* Control library behaviors


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