Overview

The Elastic GPU Service (EGS) is a multi-cluster GPU orchestration platform for Kubernetes environments. It confronts the critical global shortage of high-performance GPUs, such as NVIDIA A100, H100, B100, and B200, which are essential for advanced AI and ML workloads.

Many Large Language Model Operations (LLM-Ops) tools focus on model lifecycle management, including development and deployment, as well as scaling and monitoring. However, they often lack cross-cluster GPU scheduling and granular allocation across multiple users and pipelines. Conventional Kubernetes schedulers are also typically limited to in-cluster job scheduling and do not provide enterprise-wide GPU orchestration. This gap has generated significant demand among cloud providers, particularly those serving large and medium-sized enterprises, for a solution that offers centralized allocation, optimized provisioning, and automation of GPU resources.

EGS simplifies GPU lifecycle management, improves resource efficiency, and enables scalable, enterprise-grade AI/ML operations. It provides a unified platform for managing GPU resources across multiple Kubernetes clusters, ensuring that users can efficiently access and utilize GPU capacity for their workloads.