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<metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>Monitoring of Distributed System Processing Application in Waste to Energy Plants</dc:title><dc:creator>Boncelj,	Tadej	(Avtor)
	</dc:creator><dc:creator>Bešter,	Janez	(Mentor)
	</dc:creator><dc:creator>Mali,	Luka	(Komentor)
	</dc:creator><dc:subject>System Monitoring</dc:subject><dc:subject>Distributed Systems</dc:subject><dc:subject>Elastic</dc:subject><dc:subject>Kibana</dc:subject><dc:subject>Docker</dc:subject><dc:description>In the evolving environment of distributed systems, the challenge isn't just about processing data, but also ensuring its smooth flow and timely observability. A system's efficiency and reliability consisting of multiple components - from cameras to servers and further down the line custom-made solutions and algorithms - relies heavily on its performance metrics, health status, and anomalies. This becomes especially critical when dealing with containerized systems like Docker, where each component plays a role.

This MSc Thesis focuses on the implementation and analysis of an integrated monitoring and observability solution using Kibana, aided by Filebeat and Heartbeat components, all encapsulated within Docker containers. Such a solution allows real-time and historical insights into each component of the system, ensuring its robustness and quicker resolution of potential issues.

The research seeks to understand the indicate the nature of system monitoring, its best practices, and the benefits of integrating observability tools in complex architectures. The aim is not just to detect issues but to predict and prevent them in advance, thus ensuring a smooth, uninterrupted data flow from source to sink. Through an automated approach, coupled with expert oversight, this research contributes to enhancing the reliability and efficiency of distributed systems.</dc:description><dc:date>2024</dc:date><dc:date>2024-03-28 11:20:01</dc:date><dc:type>Magistrsko delo/naloga</dc:type><dc:identifier>155381</dc:identifier><dc:identifier>VisID: 62653</dc:identifier><dc:identifier>COBISS_ID: 190879491</dc:identifier><dc:language>sl</dc:language></metadata>
