KubeCon + CloudNativeCon Europe 2025

As Bloomberg’s usage of AI continues to grow rapidly, it is critical to ensure that those workloads with high business impact are prioritized to use the firm’s available GPU resources. As a result, Bloomberg’s Data Science Platform engineering team has implemented Karmada’s Priority and Preemption feature to efficiently manage the sequencing of machine learning (ML) workloads using a multi-cluster scheduling system.

This talk will discuss the challenges of balancing resource allocation between high-priority and lower-priority ML batch jobs, and how Karmada helps ensure that business-critical workloads are not starved of resources during periods of high contention. Attendees will gain practical insights into configuring and managing multi-cluster environments, ensuring timely execution of ML jobs while maintaining cluster efficiency. This session is ideal for Kubernetes' administrators and engineers who are managing large-scale ML workloads.