Efficient service mesh traffic management for cloud-native applications
Rizwan Ahmed, Shuyang Ren, Eunsam Kim, Choonhwa Lee
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.
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…
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Taxonomy
TopicsCloud Computing and Resource Management · Software System Performance and Reliability · Software-Defined Networks and 5G