Moeid Heidari
This research tackles the limitations of traditional autoscaling systems, which typically operate within a single cloud provider. We propose a new Kubernetes autoscaling operator that dynamically adjusts resources across multiple cloud platforms and on-premise systems. By integrating with various provisioning systems and allowing user-defined scaling strategies, this operator addresses the inefficiencies and vendor lock-in issues of conventional solutions. Our approach not only enhances scalability and system resilience but also improves cost-efficiency, as demonstrated by a significant increase in system availability. Metrics are collected and analyzed to predict scaling needs, ensuring optimal performance and resource utilization.
Moeid Heidari[node:field-speakers-institution]
With over 16 years of experience in the IT industry, I offer a broad and deep skill set in technology. I hold a Master’s degree in Computer Science and am currently pursuing a PhD focused on cloud computing, scalability, and high availability methods.
In my current role as a Cloud Engineer at Volvo Cars, I utilize my extensive knowledge of Kubernetes and AWS to optimize and manage cloud infrastructure. My career path includes significant experience as a DevOps Engineer at Robert Bosch Company and as a Tech Lead Architect in the IoT and telecom industries.
In addition to my cloud and DevOps expertise, I have a strong background as a software developer. My technical proficiency spans software development, compiler analysis, microarchitectural optimization, parallel computing, and high-performance computing (HPC). I also possess a solid foundation in grid computing.
My passion lies in advancing cloud technologies, improving system performance, and driving innovation in the field.
author = {Moeid Heidari},
title = {Multi-tier Kubernetes Cluster {Auto-Scaling}},
year = {2024},
address = {Dublin},
publisher = {USENIX Association},
month = oct
}