EGS SDK

The Elastic GPU Service (EGS) SDK provides tools and workflows for efficient GPU resource management across one or more Kubernetes clusters. It addresses critical gaps in LLM-Ops tools and schedulers by offering robust GPU scheduling, pre-configured GPU nodes and pools, and seamless resource management for cloud providers and users.

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Key Features 🚀

• Efficient GPU Scheduling: Manage GPU resources across multiple users and clusters seamlessly.
• Pre-configured GPU Nodes and Pools: Ready-to-use setups for fine-tuning jobs, enhancing GPU utilization and monetization.
• Self-Service Portal: Simplifies GPU resource management for a broader range of users.
• Premium Service Delivery: Enables cloud providers to offer white-glove services to larger customers.

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Installation 🛠️

To install the egs-sdk package, use the following command:

pip install git+https://github.com/kubeslice-ent/egs-sdk.git

If you wish to install a specific branch or version, specify it like this:

pip install git+https://github.com/kubeslice-ent/egs-sdk.git@<branch_or_tag_name>

Ensure you have Python 3.7 or higher installed on your system.

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Development 🧑‍💻

Clone the Repository

To clone the repository and set up the development environment:

git clone https://github.com/kubeslice-ent/egs-sdk.git
cd egs-sdk
pip install -e .

Run Tests

Tests are available to ensure the SDK works as expected. To run tests:

pytest

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Contributing 🤝

We welcome contributions! Please open an issue or submit a pull request with your changes. Ensure you follow the project's coding standards and test your changes before submitting.

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Support 💬

For issues, feature requests, or questions, please visit the GitHub Issues page.

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Resources 📚

• Documentation: https://docs.avesha.io/documentation/enterprise-egs/0.8.0/overview/
• Source Code: https://github.com/kubeslice-ent/egs-sdk
• Tracker: https://github.com/kubeslice-ent/egs-sdk/issues

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For more detailed information, refer to the Elastic GPU Service Overview