LG Uplus Automates AI Lifecycle With Hybrid GPU Infrastructure
LG Uplus introduced an AI infrastructure automation platform on April 10 that connects on-premise GPUs with AWS cloud services. The company presented the system at Amazon Web Services' "2026 Modern Agentic Application Day," demonstrating how to manage the full AI development cycle in a single pipeline.
The platform unifies data collection, model training, deployment, and live operations into one workflow. This structure keeps AI models ready for immediate deployment rather than requiring separate handoffs between teams.
How the Infrastructure Works
LG Uplus built the system on Amazon EKS, AWS's managed Kubernetes service. On-premise GPUs function as hybrid nodes within EKS clusters, while AWS handles the control plane management.
This hybrid approach reduces infrastructure overhead. Teams focus on platform stability and service quality instead of managing underlying systems.
Dynamic Resource Allocation Replaces Fixed Assignments
The company shifted from allocating GPUs by hardware unit to distributing resources based on actual demand. The change cuts idle GPU time and improves efficiency for both model training and production services.
Kwon Ki-deok, head of the AX Engineering Lab at LG Uplus, said the system integrates data collection, model deployment, operations, and GPU management into a unified workflow.
For development teams managing AI infrastructure, this approach addresses a core problem: reducing the gap between isolated development environments and production systems. The hybrid model also lets organizations use existing on-premise GPU investments alongside cloud resources.
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