> For the complete documentation index, see [llms.txt](https://docs.roboflow.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.roboflow.com/deployment/self-hosted/inference-server/install/cloud.md).

# Deploy in Your Own Cloud

You can run Roboflow Inference on major cloud platforms like AWS, Azure, or GCP.

Deploying in your own cloud is a good fit when you want the scalability and flexibility of the cloud but have technical or organizational constraints on where your data can be sent. Billing works the same as self-hosting on an edge device: the software is free and open source and you pay your cloud provider for the machine.

Inference integrates with [SkyPilot](https://github.com/skypilot-org/skypilot), which makes deploying a cloud instance to run Inference a single command once you have authenticated with your cloud provider.

Read the provider guides for details:

* [Set up Inference on AWS](/deployment/self-hosted/inference-server/install/cloud/aws.md)
* [Set up Inference on Azure](/deployment/self-hosted/inference-server/install/cloud/azure.md)
* [Set up Inference on GCP](/deployment/self-hosted/inference-server/install/cloud/gcp.md)

## Manual setup

You can also follow the [Linux install guide](/deployment/self-hosted/inference-server/install/linux.md) to configure a Docker container manually on your cloud VM.

[A Helm chart](https://github.com/roboflow/inference/tree/main/inference/enterprise/helm-chart) is available for enterprise cloud deployments via Kubernetes. See [Kubernetes deployment](/deployment/self-hosted/enterprise/kubernetes.md) for more advice.

{% hint style="info" %}
If you want cloud inference without managing infrastructure at all, compare the Roboflow-hosted options in [Choosing a Deployment Option](/deployment/choosing-a-deployment.md).
{% endhint %}