NimbusGuard applies deep reinforcement learning with LSTM forecasting to deliver proactive Kubernetes autoscaling that outperforms reactive controllers like HPA and KEDA on performance and cost.
Machine learning- based auto-scaling for containerized applications,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.DC 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
NimbusGuard: A Novel Framework for Proactive Kubernetes Autoscaling Using Deep Q-Networks
NimbusGuard applies deep reinforcement learning with LSTM forecasting to deliver proactive Kubernetes autoscaling that outperforms reactive controllers like HPA and KEDA on performance and cost.