ReProbe: An Architecture for Reconfigurable and Adaptive Probes

TL;DR

The paper addresses the challenge of monitoring dynamic distributed systems where traditional external probes require costly redeployments to adapt data collection. It proposes ReProbes, a plug-in, hierarchical architecture with a Publishers Manager, Collectors Manager, Data Manager, and self-adaptive Collectors that embed Controllers, Metric Samplers, and Data Analyzers to enable runtime adaptation of data collection and analysis. The authors provide a qualitative evaluation, comparing ReProbe to several research and commercial tools, and demonstrate its ability to support API-driven reconfiguration and within-probe adaptation across multiple ingestion targets. The work suggests that ReProbe can reduce operational overhead and improve responsiveness in cloud, microservice, and IoT monitoring, representing a promising step toward more flexible and scalable monitoring architectures.

Abstract

Modern distributed systems are highly dynamic and scalable, requiring monitoring solutions that can adapt to rapid changes. Monitoring systems that rely on external probes can only achieve adaptation through expensive operations such as deployment, undeployment, and reconfiguration. This poster paper introduces ReProbes, a class of adaptive monitoring probes that can handle rapid changes in data collection strategies. ReProbe offers controllable and configurable self-adaptive capabilities for data transmission, collection, and analysis methods. The resulting architecture can effectively enhance probe adaptability when qualitatively compared to state-of-the-art monitoring solutions.

Figures (2)

• Figure 1: ReProbe architecture.
• Figure 2: Collector architecture.