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

# Overview

> Get on-demand access to powerful computing resources.

export const FineTuningTooltip = () => {
  return <Tooltip headline="AI fine-tuning" tip="The process of adapting a pre-trained model to a specific task using a smaller, specialized dataset." cta="Learn more about fine-tuning" href="/fine-tune">fine-tuning</Tooltip>;
};

export const TrainingTooltip = () => {
  return <Tooltip headline="AI training" tip="The initial phase of AI model development, in which a model analyzes a dataset to learn patterns and relationships.">training</Tooltip>;
};

export const RunpodHubTooltip = () => {
  return <Tooltip headline="Runpod Hub" tip="A repository for discovering, deploying, and sharing preconfigured AI projects optimized for Runpod." cta="Learn more about Runpod Hub" href="/hub/overview">Runpod Hub</Tooltip>;
};

export const ServerlessTooltip = () => {
  return <Tooltip headline="Serverless" tip="A cloud computing platform that allows you to deploy AI/ML applications without provisioning or managing servers." cta="Learn more about Serverless" href="/serverless/overview">Serverless</Tooltip>;
};

export const VolumeDiskTooltip = () => {
  return <Tooltip headline="Volume disk" tip="Persistent storage that remains available for the duration of the Pod's lease. It functions like a dedicated hard drive, allowing you to store data that needs to be retained even if the Pod is stopped or rebooted. Mounted at /workspace by default." cta="Learn more about volume disks" href="/pods/storage/types">volume disk</Tooltip>;
};

export const PodContainerDiskTooltip = () => {
  return <Tooltip headline="Container disk" tip="Temporary storage that exists only while a Pod is running, and is completely lost when the Pod is stopped or deleted." cta="Learn more about container disks" href="/pods/storage/types">container disk</Tooltip>;
};

export const NetworkVolumeTooltip = () => {
  return <Tooltip headline="Network volume" tip="Persistent storage that exists independently of your other compute resources. Can be attached to multiple Pods or Serverless endpoints to share data between machines." cta="Learn more about network volumes" href="/storage/network-volumes">network volume</Tooltip>;
};

<div className="overview-page-wrapper" />

Pods provide instant access to powerful GPU and CPU resources for AI <TrainingTooltip />, <FineTuningTooltip />, rendering, and other compute-intensive workloads. You have full control over your computing environment, allowing you to customize software, storage, and networking to match your exact requirements.

## Get started

<CardGroup cols={3}>
  <Card title="Quickstart" href="/get-started" icon="bolt" horizontal>
    Create an account and deploy your first Pod.
  </Card>

  <Card title="Choose a Pod" href="/pods/choose-a-pod" icon="microchip" horizontal>
    Select the right GPU type and configuration for your workload.
  </Card>

  <Card title="Connect to your Pod" href="/pods/connect-to-a-pod" icon="plug" horizontal>
    Access your Pod via SSH, JupyterLab, or VS Code.
  </Card>
</CardGroup>

## Concepts

### [Templates](/pods/templates/overview)

Pre-configured [Docker image](/tutorials/introduction/containers#what-are-images) setups that let you quickly spin up Pods without manual environment configuration. Instead of installing PyTorch, configuring JupyterLab, and setting up all dependencies yourself, you can select an official Runpod PyTorch template and have everything ready to go instantly.

### [Storage](/pods/storage/types)

Pods offer three types of storage: <PodContainerDiskTooltip /> for temporary files, <VolumeDiskTooltip /> for persistent storage throughout the Pod's lease, and optional <NetworkVolumeTooltip />s for permanent storage that can be transferred between Pods.

### [Connection](/pods/connect-to-a-pod)

Once deployed, you can connect to your Pod through SSH for command-line access, web proxy for [exposed web services](/pods/configuration/expose-ports), JupyterLab for data science workflows, or [VS Code/Cursor](/pods/configuration/connect-to-ide) for local IDE integration.

## Deployment options

You can deploy Pods in several ways:

* [From a template](/pods/templates/overview): Pre-configured environments for quick setup of common workflows.
* **Custom containers**: Pull from any compatible container registry such as Docker Hub, GitHub Container Registry, or Amazon ECR. Learn more about [creating your own container images](/tutorials/introduction/containers/create-dockerfiles).
* [From Serverless repos](/hub/overview#deploy-as-a-pod): Deploy any <ServerlessTooltip />-compatible repository from the <RunpodHubTooltip /> directly as a Pod.

## Pod types

Runpod offers two cloud options:

* **Secure Cloud:** Operates in T3/T4 data centers, providing high reliability and security for enterprise and production workloads.
* **Community Cloud:** Connects individual compute providers to users through a vetted, secure peer-to-peer system, with competitive pricing options.

## Pricing

Pods are billed by the minute with no fees for ingress/egress. Runpod also offers long-term [savings plans](/pods/pricing#savings-plans) for extended usage patterns. See [Pod pricing](/pods/pricing) for details.

## Limitations

* **Docker Compose is not supported:** Runpod runs Docker for you, so you cannot spin up your own Docker instance or use Docker Compose on Pods.
* **UDP connections are not supported:** Pods only support TCP and HTTP connections.
* **Windows is not supported:** Pods do not currently support Windows.

## Tutorials

<CardGroup cols={3}>
  <Card title="Run Ollama on a Pod" href="/tutorials/pods/run-ollama" icon="message-bot" horizontal>
    Run LLM inference with HTTP API access.
  </Card>

  <Card title="Build Docker images with Bazel" href="/tutorials/pods/build-docker-images" icon="box" horizontal>
    Emulate a Docker-in-Docker workflow.
  </Card>

  <Card title="Create a custom template" href="/pods/templates/create-custom-template" icon="layer-group" horizontal>
    Build your own reusable Pod template.
  </Card>
</CardGroup>