# Efficient service mesh traffic management for cloud-native applications

## TL;DR

This paper introduces a new method to manage traffic in cloud-native applications using service partitions to improve efficiency and reduce response times.

## Contribution

The novel use of service partitions with graph-based clustering to enhance traffic management and resource optimization in cloud-native applications.

## Key findings

- Service partitions reduce response times by up to 15% during high network latency.
- Graph-based clustering improves resource distribution and communication efficiency.
- The approach enhances performance and dependability of microservices in cloud-native environments.

## Abstract

The cloud-native architecture and microservice technologies are revolutionizing the design, development, and management of cloud applications and services by offering greater elasticity, scalability, and flexibility. However, managing service-to-service traffic and handling faults turn out to be more difficult for modern, sophisticated cloud-native applications. The research community responded to the technical challenges by exploring efficient scheduling schemes that deploy constituent services to a node. Despite those efforts, current solutions are unable to handle real-time traffic dynamics, which could lead to resource waste and unnecessary communication delays. In this work, service partitions are used to improve resource distribution and traffic control in microservice-based applications. This strategy uses graph-based techniques to effectively cluster services, optimize resource usage, and boost communication efficiency, while continually monitoring application behaviors. We found that it can reduce response times by up to 15% during times of high network latency. The performance and dependability of microservices in cloud-native environments can be significantly improved using the proposed approach.