[Docs] Update image URLs in documentation to use the new static asset links

Author: peterschmidt85

docs/blog/archive/ambassador-program.md

@@ -3,7 +3,7 @@ title: "Get involved as a community ambassador"
 date: 2024-12-18
 description: "Join dstack as an ambassador to grow the community, share knowledge, and help others use dstack."  
 slug: ambassador-program
-image: https://github.com/dstackai/static-assets/blob/main/static-assets/images/ambassador-program.png?raw=true
+image: https://dstack.ai/static-assets/static-assets/images/ambassador-program.png
 categories:
   - Community
 ---
@@ -23,7 +23,7 @@ of the `dstack` community, and play a key role in advancing the open AI ecosyste
 [//]: # (Mention:)
 [//]: # (Who we are looking for)
 
-<img src="https://github.com/dstackai/static-assets/blob/main/static-assets/images/ambassador-program.png?raw=true" width="630"/>
+<img src="https://dstack.ai/static-assets/static-assets/images/ambassador-program.png" width="630"/>
 
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docs/blog/posts/amd-mi300x-inference-benchmark.md

@@ -3,7 +3,7 @@ title: "Benchmarking Llama 3.1 405B on 8x AMD MI300X GPUs"
 date: 2024-10-09
 description: "Exploring how the inference performance of Llama 3.1 405B varies on 8x AMD MI300X GPUs across vLLM and TGI backends in different use cases."  
 slug: amd-mi300x-inference-benchmark
-image: https://github.com/dstackai/static-assets/blob/main/static-assets/images/dstack-hotaisle-amd-mi300x-prompt-v5.png?raw=true
+image: https://dstack.ai/static-assets/static-assets/images/dstack-hotaisle-amd-mi300x-prompt-v5.png
 categories:
   - AMD
   - Benchmarks
@@ -16,7 +16,7 @@ so we saw this as a great chance to test our integration by benchmarking AMD GPU
 [Hot Aisle :material-arrow-top-right-thin:{ .external }](https://hotaisle.xyz/){:target="_blank"}, who build top-tier 
 bare metal compute for AMD GPUs, kindly provided the hardware for the benchmark.
 
-<img src="https://github.com/dstackai/static-assets/blob/main/static-assets/images/dstack-hotaisle-amd-mi300x-prompt-v5.png?raw=true" width="750" />
+<img src="https://dstack.ai/static-assets/static-assets/images/dstack-hotaisle-amd-mi300x-prompt-v5.png" width="750" />
 
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docs/blog/posts/amd-on-runpod.md

@@ -106,7 +106,7 @@ cloud resources and run the configuration.
     If you specify `model` when running a service, `dstack` will automatically register the model on
     an OpenAI-compatible endpoint and allow you to use it for chat via the control plane UI.
 
-    <img src="https://github.com/dstackai/static-assets/blob/main/static-assets/images/dstack-control-plane-model-llama31.png?raw=true" width="750px" />
+    <img src="https://dstack.ai/static-assets/static-assets/images/dstack-control-plane-model-llama31.png" width="750px" />
 
 ## What's next?
 

docs/blog/posts/amd-on-tensorwave.md

@@ -3,7 +3,7 @@ title: Using SSH fleets with TensorWave's private AMD cloud
 date: 2025-03-11
 description: "This tutorial walks you through how dstack can be used with TensorWave's private AMD cloud using SSH fleets."  
 slug: amd-on-tensorwave
-image: https://github.com/dstackai/static-assets/blob/main/static-assets/images/dstack-tensorwave-v2.png?raw=true
+image: https://dstack.ai/static-assets/static-assets/images/dstack-tensorwave-v2.png
 categories:
   - AMD
   - SSH fleets
@@ -18,7 +18,7 @@ In this tutorial, we’ll walk you through how `dstack` can be used with
 [TensorWave :material-arrow-top-right-thin:{ .external }](https://tensorwave.com/){:target="_blank"} using 
 [SSH fleets](../../docs/concepts/fleets.md#ssh).
 
-<img src="https://github.com/dstackai/static-assets/blob/main/static-assets/images/dstack-tensorwave-v2.png?raw=true" width="630"/>
+<img src="https://dstack.ai/static-assets/static-assets/images/dstack-tensorwave-v2.png" width="630"/>
 
 <!-- more -->
 
@@ -28,7 +28,7 @@ training and inference.
 Before following this tutorial, ensure you have access to a cluster. You’ll see the cluster and its nodes in your
 TensorWave dashboard.
 
-<img src="https://github.com/dstackai/static-assets/blob/main/static-assets/images/dstack-tensorwave-ui.png?raw=true" width="750"/>
+<img src="https://dstack.ai/static-assets/static-assets/images/dstack-tensorwave-ui.png" width="750"/>
 
 ## Creating a fleet
 

docs/blog/posts/beyond-kubernetes-2024-recap-and-whats-ahead.md

@@ -3,7 +3,7 @@ title: "Beyond Kubernetes: 2024 recap and what's next for AI infra"
 date: 2024-12-10
 description: "Reflecting on key milestones from 2024, and looking ahead to the next steps in simplifying AI infrastructure orchestration."  
 slug: beyond-kubernetes-2024-recap-and-whats-ahead
-image: https://github.com/dstackai/static-assets/blob/main/static-assets/images/beyond-kubernetes-2024-recap-and-whats-ahead.png?raw=true
+image: https://dstack.ai/static-assets/static-assets/images/beyond-kubernetes-2024-recap-and-whats-ahead.png
 categories:
   - AMD
   - NVIDIA

docs/blog/posts/cursor.md

@@ -3,7 +3,7 @@ title: "Accessing dev environments with Cursor"
 date: 2025-03-31
 description: "TBA"
 slug: cursor
-image: https://github.com/dstackai/static-assets/blob/main/static-assets/images/dstack-cursor-v2.png?raw=true
+image: https://dstack.ai/static-assets/static-assets/images/dstack-cursor-v2.png
 categories:
   - Dev environments
 ---
@@ -17,7 +17,7 @@ Previously, support was limited to VS Code. However, as developers rely on a var
 we’ve expanded compatibility. With this update, dev environments now offer effortless access for users of 
 [Cursor :material-arrow-top-right-thin:{ .external }](https://www.cursor.com/){:target="_blank"}.
 
-<img src="https://github.com/dstackai/static-assets/blob/main/static-assets/images/dstack-cursor-v2.png?raw=true" width="630"/>
+<img src="https://dstack.ai/static-assets/static-assets/images/dstack-cursor-v2.png" width="630"/>
 
 <!-- more -->
 
@@ -73,7 +73,7 @@ To open in Cursor, use this link:
 Clicking the provided URL will prompt your desktop Cursor IDE to automatically connect to the remote machine via the SSH
 tunnel created by the `dstack apply` command, allowing you to securely work with your dev environment.
 
-<img src="https://github.com/dstackai/static-assets/blob/main/static-assets/images/dstack-cursor-ide.png?raw=true" width="800"/>
+<img src="https://dstack.ai/static-assets/static-assets/images/dstack-cursor-ide.png" width="800"/>
 
 Using Cursor over VS Code offers multiple benefits, particularly when it comes to integrated AI coding assistance and
 enhanced developer experience.

docs/blog/posts/docker-inside-containers.md

@@ -2,7 +2,7 @@
 title: "Using Docker and Docker Compose inside GPU-enabled containers"
 date: 2024-10-30
 description: "The latest release of dstack allows for the direct use of Docker and Docker Compose within run configurations."
-image: https://github.com/dstackai/static-assets/blob/main/static-assets/images/dstack-docker-inside-containers.png?raw=true
+image: https://dstack.ai/static-assets/static-assets/images/dstack-docker-inside-containers.png
 slug: docker-inside-containers
 ---
 
@@ -82,7 +82,7 @@ One of the obvious use cases for this feature is when you need to use Docker Com
 For example, the Hugging Face Chat UI requires a MongoDB database, so using Docker Compose to run it is 
 the easiest way:
 
-<img src="https://github.com/dstackai/static-assets/blob/main/static-assets/images/dstack-docker-compose-terminal.png?raw=true" width="750"/>
+<img src="https://dstack.ai/static-assets/static-assets/images/dstack-docker-compose-terminal.png" width="750"/>
 
 ### docker build
 

docs/blog/posts/dstack-metrics.md

@@ -3,7 +3,7 @@ title: "Monitoring essential GPU metrics via CLI"
 date: 2024-10-22
 description: "dstack introduces a new CLI command (and API) for monitoring container metrics, incl. GPU usage for NVIDIA, AMD, and other accelerators."  
 slug: dstack-metrics
-image: https://github.com/dstackai/static-assets/blob/main/static-assets/images/dstack-stats-v2.png?raw=true
+image: https://dstack.ai/static-assets/static-assets/images/dstack-stats-v2.png
 categories:
   - AMD
   - NVIDIA
@@ -18,7 +18,7 @@ While it's possible to use third-party monitoring tools with `dstack`, it is oft
 track metrics out of the box. That's why, with the latest release, `dstack` introduced [`dstack stats`](../../docs/reference/cli/dstack/metrics.md), a new CLI (and API)
 for monitoring container metrics, including GPU usage for `NVIDIA`, `AMD`, and other accelerators.
 
-<img src="https://github.com/dstackai/static-assets/blob/main/static-assets/images/dstack-stats-v2.png?raw=true" width="725"/>
+<img src="https://dstack.ai/static-assets/static-assets/images/dstack-stats-v2.png" width="725"/>
 
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docs/blog/posts/efa.md

@@ -3,7 +3,7 @@ title: Efficient distributed training with AWS EFA
 date: 2025-02-20
 description: "The latest release of dstack allows you to use AWS EFA for your distributed training tasks."  
 slug: efa
-image: https://github.com/dstackai/static-assets/blob/main/static-assets/images/distributed-training-with-aws-efa-v2.png?raw=true
+image: https://dstack.ai/static-assets/static-assets/images/distributed-training-with-aws-efa-v2.png
 categories:
   - Cloud fleets
 ---
@@ -16,7 +16,7 @@ distributed training workloads across multiple GPUs and instances.
 
 With the latest release of `dstack`, you can now leverage AWS EFA to supercharge your distributed training tasks.
 
-<img src="https://github.com/dstackai/static-assets/blob/main/static-assets/images/distributed-training-with-aws-efa-v2.png?raw=true" width="630"/>
+<img src="https://dstack.ai/static-assets/static-assets/images/distributed-training-with-aws-efa-v2.png" width="630"/>
 
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docs/blog/posts/gpu-blocks-and-proxy-jump.md

@@ -3,7 +3,7 @@ title: Introducing GPU blocks and proxy jump for SSH fleets
 date: 2025-02-18
 description: "TBA"  
 slug: gpu-blocks-and-proxy-jump
-image: https://github.com/dstackai/static-assets/blob/main/static-assets/images/data-centers-and-private-clouds.png?raw=true
+image: https://dstack.ai/static-assets/static-assets/images/data-centers-and-private-clouds.png
 categories:
   - SSH fleets
 ---
@@ -21,7 +21,7 @@ Originally, `dstack` was focused on public clouds. With the new release, `dstack
 extends support to data centers and private clouds, offering a simpler, AI-native solution that replaces Kubernetes and
 Slurm.
 
-<img src="https://github.com/dstackai/static-assets/blob/main/static-assets/images/data-centers-and-private-clouds.png?raw=true" width="630"/>
+<img src="https://dstack.ai/static-assets/static-assets/images/data-centers-and-private-clouds.png" width="630"/>
 
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