Horizontal Pod Autoscaler
PulseAugur coverage of Horizontal Pod Autoscaler — every cluster mentioning Horizontal Pod Autoscaler across labs, papers, and developer communities, ranked by signal.
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Kubernetes autoscaling for AI inference: scaling on queue depth
This article details how to implement a Horizontal Pod Autoscaler (HPA) for AI inference services running on Kubernetes, specifically addressing the limitations of using CPU utilization as a scaling metric. It explains …
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vLLM autoscaling flapping fixed by choosing better signals
This article addresses the issue of "flapping" in vLLM autoscalers, where pods rapidly cycle between running and failing states, leading to increased costs and latency. The author explains that this problem often stems …
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New autoscaler ADAPT optimizes container replica counts using measured provisioning delay
Researchers have developed ADAPT, a novel self-calibrating autoscaler designed for container orchestration systems. This system uses an online EWMA estimator to dynamically track and adapt to varying cold-start duration…