Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/ogvalt/model-deployment-operator
Model Deployment Operator is a prototype system designed to automate the deployment and management of Nvidia Triton models on Kubernetes
https://github.com/ogvalt/model-deployment-operator
custom-resource-definition gitops json-schema kubernetes kubernetes-operator nvidia-triton python
Last synced: 4 months ago
JSON representation
Model Deployment Operator is a prototype system designed to automate the deployment and management of Nvidia Triton models on Kubernetes
- Host: GitHub
- URL: https://github.com/ogvalt/model-deployment-operator
- Owner: ogvalt
- Created: 2024-04-21T17:28:34.000Z (10 months ago)
- Default Branch: develop
- Last Pushed: 2024-06-04T17:34:00.000Z (8 months ago)
- Last Synced: 2024-10-01T04:43:19.132Z (4 months ago)
- Topics: custom-resource-definition, gitops, json-schema, kubernetes, kubernetes-operator, nvidia-triton, python
- Language: Python
- Homepage:
- Size: 334 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Model Deployment Operator
## Overview
The Model Deployment Operator is a prototype system designed to automate the deployment and management of Nvidia Triton models on Kubernetes. By using configuration files stored in a Git repository, the system ensures that model deployments are consistent, version-controlled, and easily auditable. This approach simplifies the process of updating models, rolling back changes, and maintaining a history of deployments, making it easier to manage machine learning models at scale.
## Features & Current State
- **Early Prototype**: The project is in its early prototype stage and may not work as expected.
- **Deployment Scripts**: Scripts for deploying models are included, but more features and refinements are planned.
- **Documentation**: Basic documentation is available, but will be expanded as the project evolves.
- **Custom CRD Generation**: Uses Pydantic models to easily create and manage Custom Resource Definitions (CRDs) for Kubernetes.
- **Triton Model Config JSON Schema**: Provides a pre-built JSON schema for configuring Triton models, generated from the official model configuration protocol.
- **Protobuf Conversion Tools**: Includes tools to convert protobuf messages into JSON or YAML formats, making it easier to work with different data formats.
## Getting Started
1. **Clone the Repository**:
```bash
git clone https://github.com/ogvalt/model-deployment-operator.git
```
2. **Navigate to the Directory**:
```bash
cd model-deployment-operator
```
3. **Follow the Examples**: Check the `examples` directory for sample configurations and deployment scripts.
4. **Deploy Using Helm**:
```bash
helm install model-deployment-operator ./helm
```
## Contributing
Contributions are welcome! Please open issues and pull requests to help improve this project.
## References
1. [How to check what branches a commit belongs to](https://stackoverflow.com/questions/7131703/how-to-know-which-branch-a-git-log-commit-belongs-to)
## Research
1. How to create CRD from pydantic model:
* https://github.com/nolar/kopf/issues/524
* https://github.com/asteven/kopf_resources/blob/master/kopf_resources/registry.py