Profiling the energy consumption of PYTHON microservices using eBPF in LINUX containers in the construction industry
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Abstract
The modern construction industry is actively implementing information technologies to optimize business processes, which has led to the widespread adoption of microservice architecture based on containerization. Python, as one of the most convenient programming languages, is often used to develop such systems. At the same time, the energy consumption of the server infrastructure is becoming a critical aspect in the context of sustainable development and reducing the carbon footprint of construction companies. This study presents a comprehensive approach to profiling the energy consumption of Python microservices in Linux containers using eBPF (extended Berkeley Packet Filter) technology. A technique has been developed and tested to obtain detailed energy consumption metrics at the level of individual microservices used in information systems of the construction industry. An experimental evaluation using the example of typical software components of building information systems showed the possibility of reducing energy consumption by up to 26.8% when optimizing microservices based on the collected metrics. The proposed approach integrates with existing monitoring systems and provides tools for analyzing the energy efficiency of cloud infrastructure. The results of the study demonstrate the prospects of using eBPF to create energy-efficient systems for managing construction processes and monitoring energy consumption in buildings.
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References
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