Server-Side Component for Centralized Log Collection and Storage in Distributed Computing Systems

Abstract

The objective of this study is to improve the efficiency and reliability of centralized collection and analytical availability of diagnostic data in distributed information systems. The study reviews local Syslog-based approaches, broker-based solutions, architectural styles, and relevant technology stacks. A centralized event logging system was developed that combines lightweight local log collection, asynchronous delivery, and scalable centralized storage. Compared with local Syslog solutions, it provides centralized accumulation and analytical access to logs; compared with broker-based platforms, it reduces deployment and operational complexity for medium- and low-load environments. The system is implemented in Go using the Gorilla framework. A sharded ClickHouse-based storage architecture with Round Robin load balancing is proposed. Experimental results confirm stable event collection, analytical availability of logs, and a balanced trade-off between throughput, reliability, and infrastructure complexity.