PID control based Cluster Autoscaling for Kubernetes

Padhi, Sagar Swarajya (2024) PID control based Cluster Autoscaling for Kubernetes. Masters thesis, Dublin, National College of Ireland.

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Abstract

Containerized cloud based microservices are deployed using Kubernetes framework in recent approaches in the industry. Kubernetes offers in-built autoscaling tools like the Horizontal Pod Auto-scaler and Vertical Pod Auto-scaler for provisioning resources based on demand. This research proposes a Control-based autoscaling method implementing the Proportional, Integral and Derivative control theory (PID).the PID control logic is used to address the dynamic resource allocation in an efficient approach. In this research the scaling requirement and decision is aggregated by analysing CPU utilization ,Memory Utilization and Error requests. By passing these metrics into the PID control loop to obtain a stable value for autoscaling the hardware. Kubeadm and terraform are used for deployment and the achieve horizontal and vertical scaling. This research highlights the potential of the PID Auto-scaler to achieve better scaling performance in container based microservices by achieving better cost-effectiveness, response-time and performance. In Future the PID control logic can be implemented on various other metrics together or individually on any number of metrics then calculate an aggregated mean, later the scaling output can be further refined by applying advanced mean models to obtain more stable and effective results.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Haque, Rejwanul UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Ciara O'Brien
Date Deposited:	16 Jul 2025 09:15
Last Modified:	16 Jul 2025 09:15
URI:	https://norma.ncirl.ie/id/eprint/8131

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