> For the complete documentation index, see [llms.txt](https://docs.kinesis.network/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.kinesis.network/what-you-can-do-with-kinesis.md).

# Platform overview

The resources, interfaces and compute choices that make up Kinesis.

Kinesis runs containerized applications across GPU and CPU infrastructure. Bring an image, choose an App Gallery template or connect a GitHub repository. Configure the runtime and choose where it should run.

## The core resources

| Resource    | Purpose                                                       | Example                                            |
| ----------- | ------------------------------------------------------------- | -------------------------------------------------- |
| **Project** | Organizes related applications and shared access              | A product environment or research project          |
| **App**     | Defines the image, runtime, network and resource requirements | An inference endpoint, web service or batch worker |
| **Grid**    | Groups compute resources that apps may use                    | A team's dedicated GPU capacity                    |
| **Server**  | An individual machine, with its own lifecycle                 | A cloud instance or a machine you connect          |
| **Build**   | Turns a GitHub source into a deployable image                 | A Dockerfile build followed by app deployment      |

```mermaid
flowchart TD
  P[Project] --> A[App]
  A --> S[Serverless capacity]
  A --> G[One or more grids]
  G --> C[Dedicated cloud servers]
  G --> B[Your own infrastructure]
```

## Match the platform to your workload

**Model serving.** Run an inference server in a container, select GPU requirements and expose a service port. Templates provide a starting configuration; model size, memory use and concurrency determine the resources you need.

**Application services.** Deploy APIs, web applications and supporting services from an image or a repository. Use environment variables, secrets, health checks and custom domains to configure the service.

**Batch work.** Use the execution and restart-policy settings for task-oriented workloads. Inspect logs and completion state separately from the readiness of a long-running service.

**Team compute.** Compose a grid from dedicated or connected servers, then share it with teammates. Grid policies control contention, idle reclaim and per-user quotas where configured.

## Work through the interface that fits

The [portal](https://portal.kinesis.network) provides interactive configuration and diagnostics. The [REST API](/api.md) supports scripts and integrations. [MCP](/mcp.md) makes supported operations available to agents.

Start with [Deploy an app](/getting-started/running-llms-with-kinesis-network.md), or read [Compute options](/getting-started/running-llms-with-kinesis-network/understanding-compute-sources.md) before choosing capacity.


---

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