Analysis of the Overhead of Observability in Fog Computing

• Breno Costa UnB
• Aletéia P. F. Araújo UnB

DOI: https://doi.org/10.5753/eradco.2024.4526

Abstract

Observability in Fog Computing environments is of great importance for guaranteeing the SLAs agreed with the users. This study aims to evaluate strategies to reduce the overhead caused by the use of tools that provide increased observability in the platform. Using the practical scenario of Mobile IoT-RoadBot, a smart city application, we evaluated the overhead of increasing observability in a test environment composed of IoT devices and a Fog node, employing open-source tools such as Prometheus and the ELK stack for management, logging, and tracing. An analysis of the overhead revealed that, although the impact on IoT devices is minimal, in Fog nodes the CPU and memory usage is significantly higher, highlighting the need for effective strategies to reduce the volume of data and improve the configuration of the tools. The results achieved represented an 80% increase in the total volume of observability data stored in the Fog node, without increasing the level of observability. The increase caused by the increase in observability in the volume of data managed by the Mobile IoT Roadbot was less than 1%.

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