[Changelog] Hot Aisle [WIP]

docs/blog/posts/hotaisle.md

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+---
+title: Supporting Hot Aisle AMD AI Developer Cloud
+date: 2025-08-11
+description: "TBA"  
+slug: hotaisle
+image: https://dstack.ai/static-assets/static-assets/images/dstack-hotaisle.png
+categories:
+  - Changelog
+---
+
+# Supporting Hot Aisle AMD AI Developer Cloud
+
+As the ecosystem around AMD GPUs matures, developers are looking for easier ways to experiment with ROCm, benchmark new architectures, and run cost-effective workloads—without manual infrastructure setup.  
+
+`dstack` is an open-source orchestrator designed for AI workloads, providing a lightweight, container-native alternative to Kubernetes and Slurm.
+
+<img src="https://dstack.ai/static-assets/static-assets/images/dstack-hotaisle.png" width="630"/>
+
+Today, we’re excited to announce native integration with [Hot Aisle :material-arrow-top-right-thin:{ .external }](https://www.hotaisle.io/){:target="_blank"}, an AMD-only GPU neocloud offering VMs and clusters at highly competitive on-demand pricing.  
+
+<!-- more -->
+
+## About Hot Aisle
+
+Hot Aisle is a next-generation GPU cloud built around AMD’s flagship AI accelerators.  
+
+Highlights:
+
+- AMD’s flagship AI-optimized accelrators
+- On-demand pricing: $1.99/hour for 1-GPU VMs
+- No commitment – start and stop when you want
+- First AMD-only GPU backend in `dstack`
+
+While it has already been possible to use HotAisle’s 8-GPU MI300X bare-metal clusters via [`SSH fleets`](../../docs/concepts/fleets.md#ssh-fleets), this integration now enables automated provisioning of VMs—made possible by HotAisle’s newly added API for MI300X instances.
+
+## Why dstack
+
+`dstack` is a new open-source container orchestrator built specifically for GPU workloads.  
+It fills the gaps left by Kubernetes and Slurm when it comes to GPU provisioning and orchestration:
+
+- Unlike Kubernetes, `dstack` offers a high-level, AI-engineer-friendly interface, and GPUs work out of the box, with no need to wrangle custom operators, device plugins, or other low-level setup.
+- Unlike Slurm, it’s use-case agnostic — equally suited for training, inference, benchmarking, or even setting up long-running dev environments.
+- It works across clouds and on-prem without vendor lock-in.
+
+With the new Hot Aisle backend, you can automatically provision MI300X VMs for any workload — from experiments to production — with a single `dstack` CLI command.
+
+## Getting started
+
+Before configuring `dstack` to use Hot Aisle’s VMs, complete these steps:
+
+1. Create a project via `ssh admin.hotaisle.app`
+2. Get credits or approve a payment method
+3. Create an API key
+
+Then, configure the backend in `~/.dstack/server/config.yml`:
+
+<div editor-title="~/.dstack/server/config.yml">
+
+```yaml
+projects:
+- name: main
+  backends:
+    - type: hotaisle
+      team_handle: hotaisle-team-handle
+      creds:
+        type: api_key
+        api_key: 9c27a4bb7a8e472fae12ab34.3f2e3c1db75b9a0187fd2196c6b3e56d2b912e1c439ba08d89e7b6fcd4ef1d3f
+```
+
+</div>
+
+Install and start the `dstack` server:
+
+<div class="termy">
+
+```shell
+$ pip install "dstack[server]"
+$ dstack server
+```
+
+</div>
+
+For more details, see [Installation](../../docs/installation/index.md).
+
+Use the `dstack` CLI to
+manage [dev environments](../../docs/concepts/dev-environments.md), [tasks](../../docs/concepts/tasks.md),
+and [services](../../docs/concepts/services.md).
+
+<div class="termy">
+
+```shell
+$ dstack apply -f .dstack.yml
+
+ #  BACKEND                   RESOURCES                                     INSTANCE TYPE                     PRICE   
+ 1  hotaisle (us-michigan-1)  cpu=13 mem=224GB disk=12288GB MI300X:192GB:1  1x MI300X 13x Xeon Platinum 8470  $1.99
+ 2  hotaisle (us-michigan-1)  cpu=8 mem=224GB disk=12288GB MI300X:192GB:1   1x MI300X 8x Xeon Platinum 8470   $1.99
+
+ Submit the run? [y/n]:
+```
+
+</div>
+
+Currently, `dstack` supports 1xGPU Hot Aisle VMs. Support for 8xGPU VMs will be added once Hot Aisle supports it.
+
+> If you prefer to use Hot Aisle’s bare-metal 8-GPU clusters with dstack, you can create an [SSH fleet](../../docs/concepts/fleets.md#ssh-fleets).
+> This way, you’ll be able to run [distributed tasks](../../docs/concepts/tasks.md#distributed-tasks) efficiently across the cluster.
+
+!!! info "What's next?"
+    1. Check [Quickstart](../../docs/quickstart.md)
+    2. Learn more about [Hot Aisle :material-arrow-top-right-thin:{ .external }](https://hotaisle.xyz/){:target="_blank"}
+    3. Explore [dev environments](../../docs/concepts/dev-environments.md), 
+        [tasks](../../docs/concepts/tasks.md), [services](../../docs/concepts/services.md), 
+        and [fleets](../../docs/concepts/fleets.md)
+    4. Join [Discord :material-arrow-top-right-thin:{ .external }](https://discord.gg/u8SmfwPpMd){:target="_blank"}