> For the complete documentation index, see [llms.txt](https://submodel.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://submodel.gitbook.io/docs/pod/overview.md).

# Overview

Pods are running container instances that can be pulled from a container registry such as Docker Hub, GitHub Container Registry, Amazon Elastic Container Registry, or any other compatible registry.

> **Note:** When building an image for submodel.ai on a Mac (Apple Silicon), use the flag `--platform linux/amd64` to ensure compatibility. This flag is essential because submodel.ai currently supports only the `linux/amd64` architecture.

## Understanding Pod Components and Configuration

A Pod is a server container created to access hardware, assigned a dynamically generated identifier. For example, `2s56cp0pof1rmt` represents one such instance.

A Pod consists of several key components:

* **Container Volume:** Stores the operating system and temporary data.
  * This storage is volatile and will be lost if the Pod is halted or rebooted.
* **Disk Volume:** Provides persistent storage, similar to a hard disk, retained for the duration of the Pod's lease.
  * This storage remains intact even if the Pod is halted or rebooted.
* **Ubuntu Linux Container:** Runs almost any software compatible with Ubuntu.
* **Assigned vCPU and System RAM:** Dedicated resources for the container and its processes.
* **Optional GPUs** Available for specific workloads such as CUDA or AI/ML tasks.
* **Pre-configured Template:** Automates software installation and settings upon Pod creation, enabling quick access to various packages.
* **Proxy Connection for Web Access:** Facilitates connectivity to any open port on the container.
  * Example: `https://[pod-id]-[port number].tun.submodel.ai`, such as `https://2s56cp0pof1rmt-7860.tun.submodel.ai/`.

To get started, check out how to [Choose a Pod](https://github.com/SubModel/docs/tree/main/pods/choose-a-pod.md), then follow the guide on [Managing Pods](https://github.com/SubModel/docs/tree/main/pods/manage-pods.md).

## Learn More

You can quickly launch a running Pod using a template. For further customization, you can configure the following settings:

* [GPU Type](https://github.com/SubModel/docs/tree/main/references/gpu-types.md) and quantity
* System Disk Size
* Start Command
* [Environment Variables](https://github.com/SubModel/docs/tree/main/pods/references/environment-variables.md)
* [Exposing HTTP/TCP Ports](https://github.com/SubModel/docs/tree/main/pods/configuration/expose-ports.md)
* [Persistent Storage Options](https://github.com/SubModel/docs/tree/main/pods/storage/types.md)

To begin, see how to [Choose a Pod](https://github.com/SubModel/docs/tree/main/pods/choose-a-pod.md) and refer to the guide on [Managing Pods](https://github.com/SubModel/docs/tree/main/pods/manage-pods.md).