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Managing Logs
Data Flow
Effective log management is one of the cornerstones of any secure IT infrastructure. Logs from servers, firewalls, switches, and applications provide valuable insights into system errors, security incidents, and unusual activities. Without centralized data acquisition, though, this information often goes unused. Unified analysis is crucial for detecting anomalies at an early stage, especially in heterogeneous environments comprising Windows, Linux, and network systems.
Graylog [1] is an open source tool that centralizes system and application logs with structured analysis and visualizes security-relevant events in real time. It runs stably on Ubuntu, does not require commercial components, and can be flexibly adapted to your individual requirements. In the daily grind, Graylog proves to be a scalable tool that aggregates, filters, and clearly presents logs from different systems. Before installing Graylog, it is helpful to understand the system architecture and correctly identify the components involved.
System Architecture Overview
Graylog comprises three central components: MongoDB stores the configuration data and user information, the Graylog Data Node handles indexing and communication with the OpenSearch search engine, and the Graylog server provides the web interface, REST API, and processing pipelines. Thanks to this structure, data streams can be managed separately and the search service scaled independently of the web component.
In a typical environment, MongoDB and Graylog run on the same host, and the Data Node resides on a separate server or virtual machine. This separation boosts performance and reduces the risk of indexing operations blocking the web service.
Integrating Graylog into the Network
Graylog supports flexible deployment: as a
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