What Kubernetes’ “monolith” lesson means for AI agent harnesses
The New Stack 2 weeks ago 45
Road to KubeCon argues that AI agent harnesses should move from laptop-style, local setups to cloud-native designs that separate the agent loop from supporting infrastructure and services. Koordinator was used by Zhuoyu Technology to push on-Kubernetes GPU allocation above 95% and GPU utilization above 55%, addressing inefficiencies from the default Kubernetes scheduler. As a result, agent and workload management becomes more distributed and scalable, with better scheduling outcomes for AI and other microservice workloads.