https://github.com/interlink-hq/interLink
InterLink aims to provide an abstraction for the execution of a Kubernetes pod on any remote resource capable of managing a Container execution lifecycle
https://github.com/interlink-hq/interLink
Last synced: 8 months ago
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InterLink aims to provide an abstraction for the execution of a Kubernetes pod on any remote resource capable of managing a Container execution lifecycle
- Host: GitHub
- URL: https://github.com/interlink-hq/interLink
- Owner: interlink-hq
- License: apache-2.0
- Created: 2023-07-05T13:18:15.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-06-27T12:44:51.000Z (9 months ago)
- Last Synced: 2025-07-05T03:59:01.450Z (8 months ago)
- Language: Go
- Homepage: https://interlink-hq.github.io/interLink/
- Size: 79.7 MB
- Stars: 80
- Watchers: 7
- Forks: 17
- Open Issues: 28
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Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: .github/CODE_OF_CONDUCT.md
Awesome Lists containing this project
- awesome-repositories - interlink-hq/interLink - InterLink aims to provide an abstraction for the execution of a Kubernetes pod on any remote resource capable of managing a Container execution lifecycle (Go)
README
# Welcome to the interLink Project
[](https://img.shields.io/github/license/interlink-hq/interlink)
[](https://goreportcard.com/report/github.com/interlink-hq/interlink)
[](https://join.slack.com/t/intertwin/shared_invite/zt-2cs67h9wz-2DFQ6EiSQGS1vlbbbJHctA)
interLink is an abstraction layer for executing Kubernetes pods on remote resources capable of managing container execution lifecycles.
It facilitates the development of provider-specific plugins for the [Kubernetes Virtual Kubelet interface](https://virtual-kubelet.io/), enabling resource providers to leverage Virtual Kubelet capabilities without deep Kubernetes internals knowledge.
## Architecture
The project consists of two main components:
- **Virtual Kubelet (Virtual Node)**: Translates Kubernetes pod execution requests into remote calls to the interLink API server
- **interLink API Server**: A modular, pluggable REST server with provider-specific plugins (sidecars) for different execution environments
## Key Features
- **Plugin-based Architecture**: Extensible sidecar system for different remote providers
- **Multiple Deployment Patterns**: Edge-node, in-cluster, and tunneled configurations
- **Built-in Observability**: OpenTelemetry integration with distributed tracing and metrics
- **Secure Communication**: TLS/mTLS encryption and authentication between components
- **Authentication**: OAuth2 integration and bearer token support
- **Standard Kubernetes API**: Maintains full compatibility with existing K8s tooling
interLink is hosted by the
[Cloud Native Computing Foundation (CNCF)](https://cncf.io).
## Getting Started
For usage and development guides please refer to
[our site](https://interlink-hq.github.io/interLink/)
## Development
```bash
# Build all components
make all
# Run tests (uses Dagger for containerized testing)
make test
# Generate OpenAPI specifications
make openapi
# Clean build artifacts
make clean
```
## Adopters
Please find all our current adopters [here](./ADOPTERS.md)
## Contributing
Our project welcomes contributions from any member of our community. To get
started contributing, please see our [Contributor Guide](./CONTRIBUTING.md).
## Supported Providers
interLink supports a wide range of remote execution environments through its plugin architecture:
- **HPC Batch Systems**: SLURM, HTCondor with Apptainer, Enroot, or Singularity containers
- **Virtual Machines**: On-demand VMs with Docker, Podman, or other container runtimes
- **Remote Kubernetes**: Offload workloads to external Kubernetes clusters
- **Serverless**: Lambda-like services for event-driven container execution
- **Custom Providers**: Extensible plugin system for any container-capable remote resource
## Use Cases
### In Scope
- **HPC Workloads**: AI training, ML inference, scientific simulations requiring specialized hardware
- **GPU-intensive Tasks**: Remote execution on powerful GPU resources for ML training, data analysis, rendering
- **Batch Processing**: On-demand container execution with specific compute requirements
- **Hybrid Cloud**: Workload distribution across multiple infrastructure providers
### Out of Scope
- **Long-running Services**: Persistent services with continuous availability requirements
- **Kubernetes Federation**: Multi-cluster resource management and federation
## Communications
- [](https://join.slack.com/t/intertwin/shared_invite/zt-2cs67h9wz-2DFQ6EiSQGS1vlbbbJHctA)
## Resources
[](https://www.youtube.com/watch?v=bIxw1uK0QRQ)
[](https://www.youtube.com/watch?v=vTg58Nd7_58)
[](https://www.youtube.com/watch?v=M3uLQiekqo8)
## License
This project is licensed under [Apache2](./LICENSE)
## Conduct
We follow the [CNCF Code of Conduct](./CODE_OF_CONDUCT.md)