> ## Documentation Index > Fetch the complete documentation index at: https://runpod-b18f5ded-public-endpoints.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Overview > Get on-demand access to powerful computing resources. Pods provide instant access to powerful GPU and CPU resources for AI development, machine learning, 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. Alternatively, you can use pre-configured templates that include ready-to-use environments for popular AI frameworks and applications. When you're ready to get started, [follow this tutorial](/get-started) to create an account and deploy your first Pod. ## Key components Each Pod consists of these core components: * **Container environment**: An Ubuntu Linux-based container that can run almost any compatible software. * **Unique identifier**: Each Pod receives a dynamic ID (e.g., `2s56cp0pof1rmt`) for management and access. * [Storage](#storage-options): * **Container volume**: Houses the operating system and temporary storage. * **Disk volume**: Persistent storage that is preserved between Pod starts and stops. * **Network volume (optional)**: Permanent, portable storage that can be moved between machines and persists even after Pod deletion. * **Hardware resources**: Allocated vCPU, system RAM, and multiple GPUs (based on your selection). * **Network connectivity**: A proxy connection enabling web access to any [exposed port](/pods/configuration/expose-ports) on your container. ## Storage Pods offer three types of storage to match different use cases: Every Pod comes with a resizable **container volume** that houses the operating system and stores temporary files, which are cleared after the Pod stops. **Disk volumes** provide persistent storage that is preserved throughout the Pod's lease, functioning like a dedicated hard drive. Data stored in the disk volume directory (`/workspace` by default) persists when you stop the Pod, but is erased when the Pod is deleted. Optional **network volumes** provide more flexible permanent storage that can be transferred between Pods, replacing the disk volume when attached. When using a Pod with network volume attached, you can safely delete your Pod without losing the data stored in your network volume directory (`/workspace` by default). To learn more, see [Storage options](/pods/storage/types). ## Deployment options You can deploy Pods in several ways: * [From a template](https://docs.runpod.io/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. * **Custom images**: Build and deploy your own container images. When building a container image for Runpod on a Mac (Apple Silicon), use the flag `--platform linux/amd64` to ensure your image is compatible with the platform. ## Connecting to your Pod Once deployed, you can [connect to your Pod](/pods/connect-to-a-pod) through: * **SSH**: Direct [command-line access](/pods/configuration/use-ssh) for development and management. * **Web proxy**: HTTP access to [exposed web services](/pods/configuration/expose-ports) via URLs in the format `https://[pod-id]-[port].proxy.runpod.net`. * **API**: Programmatic access and control through the [Runpod API](/api-reference/pods/POST/pods). * **JupyterLab**: A web-based IDE for data science and machine learning. * **VSCode/Cursor**: [Connect to your Pod with VSCode or Cursor](/pods/configuration/connect-to-ide), working within your volume directory as if the files were stored on your local machine. ## Data transfer You can transfer data from your Pod to [most major cloud providers](/pods/configuration/export-data), and to your local machine using the [Runpod CLI](/runpodctl/overview). To learn more about all available options, see [Transfer files](/pods/storage/transfer-files). ## Customization options Pods offer extensive customization to match your specific requirements. You can select your preferred [GPU type](/references/gpu-types) and quantity, adjust system disk size, and specify your container image. Additionally, you can configure custom start commands, set [environment variables](/pods/references/environment-variables), define [exposed HTTP/TCP ports](/pods/configuration/expose-ports), and implement various [storage configurations](pods/storage/types) to optimize your Pod for your specific workload. ## Pod types Runpod offers two types of Pod: * **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. ## Deploy a Pod Follow these steps to deploy a Pod: 1. [Choose a Pod](/pods/choose-a-pod) based on your computing needs and budget. 2. Navigate to the [Pod creation page](https://console.runpod.io/pod/create). 3. Configure your Pod settings, including GPU type, storage, and networking options. 4. Launch your Pod and connect using SSH, JupyterLab, or your preferred remote access method. 5. [Manage your Pod](/pods/manage-pods) through the Runpod console. ## Pricing Pods are billed by the minute with no fees for ingress/egrees. Runpod also offers long-term [savings plans](/pods/pricing#savings-plans) for extended usage patterns. See [GPU pricing](https://www.runpod.io/pricing) for details. ## Next steps Ready to get started? Explore these pages to learn more: * [Deploy your first Pod](/get-started) using this tutorial. * [Choose a Pod](/pods/choose-a-pod) based on your requirements. * Learn how to [connect to your Pod](/pods/connect-to-a-pod) after deployment. * Learn how to [manage your Pods](/pods/manage-pods) using the console and CLI. * Set up [persistent storage](/pods/storage/types) for your data. * Configure [global networking](/pods/networking) for your applications.