KARMA uses four cooperating reinforcement-learning agents, each guided by a role and mission, to autoscale a Kubernetes cluster, and beats three existing autoscalers in a single-node simulation across failure scenarios.
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Streamlining Resilient Kubernetes Autoscaling with Multi-Agent Systems via an Automated Online Design Framework
KARMA uses four cooperating reinforcement-learning agents, each guided by a role and mission, to autoscale a Kubernetes cluster, and beats three existing autoscalers in a single-node simulation across failure scenarios.