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Google has open-sourced AX, a Kubernetes-style orchestrator specifically engineered for stateful autonomous AI agents that exhibit bursty compute patterns and long idle periods. By treating agents as isolated actors on the Agent Substrate runtime, the system enables sub-second task suspension and resumption to eliminate cold-start latency and optimize resource utilization during waiting states. This architecture directly addresses the infrastructure challenges of scaling modern agent workloads beyond traditional microservice or batch processing models.
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Google Open-Sources AX a Kubernetes Style Orchestrator for Autonomous AI Agents

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Google has open-sourced AX, an orchestrator designed for managing autonomous AI agent workloads. AX operates on a runtime, Agent Substrate, treating agents as stateful actors. It provides resource-efficient task suspension and resumption to optimise performance and reduce latency in idle phases. It features a control plane with Kubernetes-style primitives for managing agent tasks and resources. By Olimpiu Pop

Google has introduced AX (hosted at agentexecutor.io and on GitHub as google/ax), an open-source, Apache 2.0-licensed orchestrator and declarative runtime designed to execute and scale autonomous AI agent workloads. Running on top of Agent Substrate, AX treats agents as stateful actors rather than microservices or batch jobs, offering sub-second task suspension and resumption alongside four core declarative primitives: Task, Workspace, Gateway, and…

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