L3: Latency-aware Load Balancing in Multi-Cluster Service Mesh

Microservice architectures and service meshes have become highly popular and face increasingly stringent scalability and dependability requirements. To achieve low-latency service execution and maximize performance, service providers of large-scale distributed systems deploy microservices geographically closer to their users in multi-cluster service mesh environments. However, inter-cluster service dependencies introduce additional latency, and effective load balancing across multiple replicas distributed across clusters is crucial. Addressing this challenge, we present L3, an adaptive latency-aware load-balancing mechanism for multi-cluster service meshes. We conduct extensive simulations on Amazon EC2, and our results of using the microservices of the DeathStarBench suite for three clusters show that L3 reduces the 99th percentile latency by 26% and 22% compared with round-robin and C3.

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Publication Details

Published
2024-11-27
DOI
https://doi.org/10.1145/3652892.3654793
Citations
5
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
3.90

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article

L3: Latency-aware Load Balancing in Multi-Cluster Service Mesh

Habib Mostafaei, Stefan Schmid, Olivier Michaelis
5 citations
Cloud Computing and Resource Management
3.90
article

L3: Latency-aware Load Balancing in Multi-Cluster Service Mesh

Habib Mostafaei, Stefan Schmid, Olivier Michaelis
article en
5 citations

Abstract

Microservice architectures and service meshes have become highly popular and face increasingly stringent scalability and dependability requirements. To achieve low-latency service execution and maximize performance, service providers of large-scale distributed systems deploy microservices geographically closer to their users in multi-cluster service mesh environments. However, inter-cluster service dependencies introduce additional latency, and effective load balancing across multiple replicas distributed across clusters is crucial. Addressing this challenge, we present L3, an adaptive latency-aware load-balancing mechanism for multi-cluster service meshes. We conduct extensive simulations on Amazon EC2, and our results of using the microservices of the DeathStarBench suite for three clusters show that L3 reduces the 99th percentile latency by 26% and 22% compared with round-robin and C3.

Fraunhofer Institute for Secure Information Technology (DE), Technische Universität Berlin (DE), Eindhoven University of Technology (NL)
Bundesministerium für Bildung und Forschung
Affordable and clean energy
Openalex Percentile: Top 5%
Cloud Computing and Resource Management
3.90
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L3: Latency-aware Load Balancing in Multi-Cluster Service Mesh — Habib Mostafaei, Stefan Schmid, et al. · (2024) | TGRS Research Map | TGRS