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 durations, which are critical for proactive scaling. By feeding this measured provisioning delay into a Model Predictive Controller, ADAPT optimizes replica counts and aims to minimize SLA violations, outperforming existing methods in evaluations. AI

IMPACT Improves efficiency and reliability of containerized AI workloads by optimizing resource allocation.

RANK_REASON Publication of an academic paper on a new autoscaling method for container orchestration. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.LG →

• EWMA estimator
• Himanshu Singh Baghel
• Model Predictive Controller
• MPC+LSTM
• MPC+Prophet
• Container Orchestration

• paper
• infra

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