Microservices for information support of multi-agent systems: methods of collection, monitoring and decision-making

Purpose. The purpose of this article is to develop methods and algorithms of microservice implementation for information support of multi-agent systems that implement the functions of digital twins of the enterprise. Particular attention is paid to the implementation of data collection, monitoring, diagnostics and decision-making functions that ensure effective interaction between product agents and resource agents based on service level agreements (SLAs). Research methods. The research uses methods of building a microservice architecture to separate and autonomously perform functions such as data collection, monitoring and diagnostics in order to optimize SLA and increase system reliability. To increase the system's resilience to security threats, access control, data encryption, and anomaly analysis stages have been added to the algorithms. The methodology includes adaptive management of SLA parameters, the use of distributed data processing and the use of analytical algorithms for decision-making, as well as mechanisms to identify potential threats and unauthorized access. Results . The proposed methods and algorithms make it possible to create a flexible and scalable multi-agent system capable of adapting to changing conditions and ensuring stable and safe operation of digital counterparts. Using SLA to regulate the interaction of agents improves the consistency of their actions, increases the accuracy of monitoring and protects data, maintaining high reliability and security of the system. Conclusion . The results show that the microservice approach, the use of SLA and the integration of security measures significantly increase the efficiency and reliability of multi-agent systems, allowing agents to adapt to changes, respond promptly to deviations and prevent possible threats. The use of these methods can significantly improve asset management in network enterprises, maintaining their competitiveness, sustainability and security in the context of digital transformation.