Project summary
AI Runway is an abstract set of operators that enable easier deployments of a wide array of AI inferencing engines and models in Kubernetes.
Project description
AI Runway gives you a web UI and a unified Kubernetes CRD (ModelDeployment) to deploy models across multiple inference providers. Browse HuggingFace, pick a model, click deploy. The intention is to make it easier for the Kubernetes and cloud native ecosystem to deploy and learn about deploying various combinations of open source inference engines and models in Kubernetes.
At the moment, there are a wide array of inference engines and servers to host an inference endpoint, but each one requires specific installation process and mastering the very different details of each. This choice is a beautiful aspect of the ecosystem, but it also makes it harder to start building agentic and other applications in Kubernetes that use inference endpoints of various kinds until you've mastered the stack choice and the engine you end up choosing.
AI Runway helps break that logjam, getting deployments started easily with the widest possible array of choices from the ecosystem. The provider extension model means that AI Runway can add any current or future inference engine without modifying the deployment abstraction, and can be used locally or in any cloud native Kubernetes distribution. If successful, the project might serve as a useful exercise implementation for a future Kubernetes AI Inference API proposal.
Org repo URL (provide if all repos under the org are in scope of the application)
N/A
Project repo URL in scope of application
https://github.com/kaito-project/airunway
Additional repos in scope of the application
No response
Website URL
https://github.com/kaito-project/airunway
Roadmap
https://github.com/kaito-project/airunway/issues
Roadmap context
We are building a project page and will update the application as soon as it is completed.
Contributing guide
https://github.com/kaito-project/airunway/blob/main/CONTRIBUTING.md
Code of Conduct (CoC)
https://github.com/kaito-project/airunway/blob/main/CODE_OF_CONDUCT.md
Adopters
No response
Maintainers file
https://github.com/kaito-project/airunway/graphs/contributors?from=2%2F14%2F2026
Security policy file
kaito-project/airunway#279
Standard or specification?
N/A, though this is likely to change.
Business product or service to project separation
This is not part of any business product or service.
Why CNCF?
The CNCF is the open source foundation that houses the finest in cloud native projects the world can use forever. This project makes it possible to use with some ease the widest array of models with a wide array of stacks in a fully vendor-neutral, Kubernetes-native experience -- something that belongs in the CNCF.
Benefit to the landscape
There are no other similar projects in the CNCF at the moment, though we feel sure they will appear. The LF has a large array of projects in its AI organizations, but none of them are really aimed at the same market.
Cloud native 'fit'
it logically fits in https://landscape.cncf.io/?group=ai-native&view-mode=grid here, possibly in "AI Native Infra" or in Application Definition in the core map. As it "assembles" other projects into a deployment, possible "framework" might make sense......
Cloud native 'integration'
It currently can make use of Kaito, llm-d, vllm, ray, slurm, etc..... any part of the system can be added to the tool as a provider independently of any other. it is a true "integration" piece for CNCF AI tooling.
Cloud native overlap
it really doesn't, in that it's an integration and usability tool for other projects.
Similar projects
N/A
Landscape
Not yet.
Insights
Not yet.
Trademark and accounts
IP policy
Will the project require a license exception?
No.
Project "Domain Technical Review"
Not yet.
Application contact email(s)
ralph.squillace@microsoft.com,seozerca@microsoft.com,david.justice@microsoft.com
Contributing or sponsoring entity signatory information
If an organization:
| Name |
Address |
Type (e.g., Delaware corporation) |
Signatory name and title |
Email address |
| Microsoft Corporation |
One Redmond Way, Redmond WA 98052 |
US corporation |
Brendan Burns -- Corporate Vice President and Technical Fellow |
bburns@microsoft.com |
Or, if an individual or individual(s):
| Name |
Country |
Email address |
|
|
|
|
|
|
|
|
|
CNCF contacts
No response
Additional information
No response
Project summary
AI Runway is an abstract set of operators that enable easier deployments of a wide array of AI inferencing engines and models in Kubernetes.
Project description
AI Runway gives you a web UI and a unified Kubernetes CRD (ModelDeployment) to deploy models across multiple inference providers. Browse HuggingFace, pick a model, click deploy. The intention is to make it easier for the Kubernetes and cloud native ecosystem to deploy and learn about deploying various combinations of open source inference engines and models in Kubernetes.
At the moment, there are a wide array of inference engines and servers to host an inference endpoint, but each one requires specific installation process and mastering the very different details of each. This choice is a beautiful aspect of the ecosystem, but it also makes it harder to start building agentic and other applications in Kubernetes that use inference endpoints of various kinds until you've mastered the stack choice and the engine you end up choosing.
AI Runway helps break that logjam, getting deployments started easily with the widest possible array of choices from the ecosystem. The provider extension model means that AI Runway can add any current or future inference engine without modifying the deployment abstraction, and can be used locally or in any cloud native Kubernetes distribution. If successful, the project might serve as a useful exercise implementation for a future Kubernetes AI Inference API proposal.
Org repo URL (provide if all repos under the org are in scope of the application)
N/A
Project repo URL in scope of application
https://github.com/kaito-project/airunway
Additional repos in scope of the application
No response
Website URL
https://github.com/kaito-project/airunway
Roadmap
https://github.com/kaito-project/airunway/issues
Roadmap context
We are building a project page and will update the application as soon as it is completed.
Contributing guide
https://github.com/kaito-project/airunway/blob/main/CONTRIBUTING.md
Code of Conduct (CoC)
https://github.com/kaito-project/airunway/blob/main/CODE_OF_CONDUCT.md
Adopters
No response
Maintainers file
https://github.com/kaito-project/airunway/graphs/contributors?from=2%2F14%2F2026
Security policy file
kaito-project/airunway#279
Standard or specification?
N/A, though this is likely to change.
Business product or service to project separation
This is not part of any business product or service.
Why CNCF?
The CNCF is the open source foundation that houses the finest in cloud native projects the world can use forever. This project makes it possible to use with some ease the widest array of models with a wide array of stacks in a fully vendor-neutral, Kubernetes-native experience -- something that belongs in the CNCF.
Benefit to the landscape
There are no other similar projects in the CNCF at the moment, though we feel sure they will appear. The LF has a large array of projects in its AI organizations, but none of them are really aimed at the same market.
Cloud native 'fit'
it logically fits in https://landscape.cncf.io/?group=ai-native&view-mode=grid here, possibly in "AI Native Infra" or in Application Definition in the core map. As it "assembles" other projects into a deployment, possible "framework" might make sense......
Cloud native 'integration'
It currently can make use of Kaito, llm-d, vllm, ray, slurm, etc..... any part of the system can be added to the tool as a provider independently of any other. it is a true "integration" piece for CNCF AI tooling.
Cloud native overlap
it really doesn't, in that it's an integration and usability tool for other projects.
Similar projects
N/A
Landscape
Not yet.
Insights
Not yet.
Trademark and accounts
IP policy
Will the project require a license exception?
No.
Project "Domain Technical Review"
Not yet.
Application contact email(s)
ralph.squillace@microsoft.com,seozerca@microsoft.com,david.justice@microsoft.com
Contributing or sponsoring entity signatory information
If an organization:
Or, if an individual or individual(s):
CNCF contacts
No response
Additional information
No response