Efficient Microservices Scaling: Kubernetes, Autoscaling, and Load Balancing

Abstract

This article addresses the issue of efficient scaling of microservice architecture under variable load conditions and limited resources. Special attention is given to the use of automatic scaling mechanisms in Kubernetes, such as the Horizontal Pod Autoscaler and Vertical Pod Autoscaler, as well as the selection and interpretation of load metrics that form the basis for scaling decisions. It explores how different scaling approaches affect system performance and infrastructure operating costs. It also investigates how scaling strategies, the degree of automation, and load balancing configurations influence service stability, resource utilization, and the overall quality of distributed system operation.