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</div>
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`dstack` is an open-source alternative to Kubernetes and Slurm, designed to simplify GPU allocation and AI workload
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orchestration for ML teams across top clouds and on-prem clusters.
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`dstack` is an open-source container orchestrator that simplifies workload orchestration and drives GPU utilization for ML teams. It works with any GPU cloud, on-prem cluster, or accelerated hardware.
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#### Accelerators
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Copy file name to clipboardExpand all lines: docs/docs/concepts/backends.md
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# Backends
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To use `dstack` with cloud providers, configure backends
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via the [`~/.dstack/server/config.yml`](../reference/server/config.yml.md) file.
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The server loads this file on startup.
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Backends allow `dstack` to manage compute across various providers.
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They can be configured via `~/.dstack/server/config.yml` (or through the [project settings page](../concepts/projects.md#backends) in the UI).
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Alternatively, you can configure backends on the [project settings page](../concepts/projects.md#backends) via UI.
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See below for examples of backend configurations.
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> For using `dstack` with on-prem servers, no backend configuration is required.
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> Use [SSH fleets](../concepts/fleets.md#ssh) instead once the server is up.
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??? info "SSH fleets"
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For using `dstack` with on-prem servers, no backend configuration is required.
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Use [SSH fleets](../concepts/fleets.md#ssh) instead once the server is up.
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Below examples of how to configure backends via `~/.dstack/server/config.yml`.
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## Cloud providers
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### AWS
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## AWS
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There are two ways to configure AWS: using an access key or using the default credentials.
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* Docker is installed
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* (For NVIDIA instances) NVIDIA/CUDA drivers and NVIDIA Container Toolkit are installed
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###Azure
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## Azure
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There are two ways to configure Azure: using a client secret or using the default credentials.
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Using private subnets assumes that both the `dstack` server and users can access the configured VPC's private subnets.
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Additionally, private subnets must have outbound internet connectivity provided by [NAT Gateway or other mechanism](https://learn.microsoft.com/en-us/azure/nat-gateway/nat-overview).
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###GCP
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## GCP
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There are two ways to configure GCP: using a service account or using the default credentials.
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Using private subnets assumes that both the `dstack` server and users can access the configured VPC's private subnets.
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Additionally, [Cloud NAT](https://cloud.google.com/nat/docs/overview) must be configured to provide access to external resources for provisioned instances.
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###Lambda
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## Lambda
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Log into your [Lambda Cloud :material-arrow-top-right-thin:{ .external }](https://lambdalabs.com/service/gpu-cloud) account, click API keys in the sidebar, and then click the `Generate API key`
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button to create a new API key.
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</div>
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### Nebius
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## Nebius
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Log into your [Nebius AI Cloud :material-arrow-top-right-thin:{ .external }](https://console.eu.nebius.com/) account, navigate to Access, and select Service Accounts. Create a service account, add it to the editors group, and upload its authorized key.
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### RunPod
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## RunPod
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Log into your [RunPod :material-arrow-top-right-thin:{ .external }](https://www.runpod.io/console/) console, click Settings in the sidebar, expand the `API Keys` section, and click
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the button to create a Read & Write key.
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</div>
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### Vultr
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## Vultr
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Log into your [Vultr :material-arrow-top-right-thin:{ .external }](https://www.vultr.com/) account, click `Account` in the sidebar, select `API`, find the `Personal Access Token` panel and click the `Enable API` button. In the `Access Control` panel, allow API requests from all addresses or from the subnet where your `dstack` server is deployed.
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</div>
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### Vast.ai
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## Vast.ai
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Log into your [Vast.ai :material-arrow-top-right-thin:{ .external }](https://cloud.vast.ai/) account, click Account in the sidebar, and copy your
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API Key.
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Also, the `vastai` backend supports on-demand instances only. Spot instance support coming soon.
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<!-- ### TensorDock
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<!-- ## TensorDock
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Log into your [TensorDock :material-arrow-top-right-thin:{ .external }](https://dashboard.tensordock.com/) account, click Developers in the sidebar, and use the `Create an Authorization` section to create a new authorization key.
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The `tensordock` backend supports on-demand instances only. Spot instance support coming soon. -->
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### CUDO
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## CUDO
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Log into your [CUDO Compute :material-arrow-top-right-thin:{ .external }](https://compute.cudo.org/) account, click API keys in the sidebar, and click the `Create an API key` button.
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</div>
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### OCI
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## OCI
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There are two ways to configure OCI: using client credentials or using the default credentials.
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compartment_id: ocid1.compartment.oc1..aaaaaaaa
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```
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### DataCrunch
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## DataCrunch
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Log into your [DataCrunch :material-arrow-top-right-thin:{ .external }](https://cloud.datacrunch.io/) account, click Keys in the sidebar, find `REST API Credentials` area and then click the `Generate Credentials` button.
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</div>
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### CloudRift
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## CloudRift
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Log into your [CloudRift :material-arrow-top-right-thin:{ .external }](https://console.cloudrift.ai/) console, click `API Keys` in the sidebar and click the button to create a new API key.
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## On-prem servers
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### SSH fleets
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> For using `dstack` with on-prem servers, no backend configuration is required.
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> See [SSH fleets](fleets.md#ssh) for more details.
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### Kubernetes
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## Kubernetes
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To configure a Kubernetes backend, specify the path to the kubeconfig file,
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and the port that `dstack` can use for proxying SSH traffic.
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## dstack Sky
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If you're using [dstack Sky :material-arrow-top-right-thin:{ .external }](https://sky.dstack.ai){:target="_blank"},
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backends are pre-configured to use compute from `dstack`'s marketplace.
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You can reconfigure backends via the UI, to use your own cloud accounts instead.
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backends come pre-configured to use compute from the dstack marketplace. However, you can update the configuration via UI
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to use your own cloud accounts instead.
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[//]: # (TODO: Add link to the server config reference page)
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!!! info "What's next"
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1. See the [`~/.dstack/server/config.yml`](../reference/server/config.yml.md) reference
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