User activity monitoring and automated office IT infrastructure management system
This article presents the concept, architecture, and implementation of an intelligent microservice platform for monitoring user activity and automating the management of office IT infrastructure. In the context of rapid digital transformation and growing cybersecurity threats, the platform addresses...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Zhytomyr Polytechnic State University
2025-07-01
|
| Series: | Технічна інженерія |
| Subjects: | |
| Online Access: | https://ten.ztu.edu.ua/article/view/334873 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | This article presents the concept, architecture, and implementation of an intelligent microservice platform for monitoring user activity and automating the management of office IT infrastructure. In the context of rapid digital transformation and growing cybersecurity threats, the platform addresses the need for transparency, anomaly detection, and adaptive response across complex IT environments. A novel aspect of the proposed approach is the conceptualization of each personal computer as an active Internet of Things (IoT) node within a unified digital ecosystem.
The system is based on a multi-level, event-driven IoT architecture that employs an MQTT bus as the transport layer to ensure scalability, flexibility, and fault tolerance. It consists of three core layers: data collection agents, a message broker, and analytical-control microservices. These components enable behavior-based analytics, detection of unauthorized software, identification of third-party or potentially malicious processes (e.g., cryptominers), and real-time risk prediction. The platform integrates secure communication protocols, encryption, event caching, and mechanisms for privacy protection and data persistence during connectivity loss.
A detailed implementation of a Python-based software agent is provided, capable of gathering technical and behavioral parameters such as CPU load, user interaction, and network status. The architecture supports seamless integration with cloud-based analytics tools, AI modules, and cybersecurity systems, facilitating dynamic policy adjustment and proactive incident response.
The platform is designed to incorporate self-learning mechanisms, contextual awareness, and multi-agent coordination–supporting the transition from conventional monitoring tools to an adaptive, intelligent infrastructure aligned with Industry 4.0 paradigms, where each workstation functions as a smart sensor-actuator unit in the organizational IT landscape. |
|---|---|
| ISSN: | 2706-5847 2707-9619 |