Enhancing the Kubernetes Scheduler: A State-of-the-Art Review from Cloud to Edge
TL;DR
A comprehensive review of Kubernetes scheduling strategies published between January 2023 and January 2026 is presented and a multi-dimensional taxonomy is established that categorizes scheduling approaches based on common objectives, modification methods, optimization methodologies, targeted workloads, evaluation methods, scheduling scopes, and performance metrics.
Abstract
The rapid expansion of the cloud–edge continuum requires containerized applications to scale dynamically across highly heterogeneous and resource-constrained environments. As the de facto standard for container orchestration, Kubernetes (K8s for short) relies heavily on its scheduling subsystem to manage these complex distributed environments. However, default scheduling methodologies are inherently designed for homogeneous cloud data centers and bring substantial deployment challenges when used in edge topologies. While numerous custom schedulers, plugins, and extensions have been put forward to bridge this gap, a review of the state of the art is needed to evaluate existing approaches and capture recent trends. In this survey, we present a comprehensive review of Kubernetes scheduling strategies published between January 2023 and January 2026. We establish a multi-dimensional taxonomy that categorizes scheduling approaches based on common objectives, modification methods, optimization methodologies, targeted workloads, evaluation methods, scheduling scopes, and performance metrics. We investigate open challenges arising across different computing paradigms and highlight recent trends and possible directions for future research in Kubernetes scheduling.