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ServiMon is a scalable data collection and auditing pipeline designed for service-oriented, cost-efficient quality control in distributed environments, including the CTAO monitoring, logging, and alarm subsystems. Developed within a Docker-based architecture, it leverages cloud-native technologies and distributed computing principles to enhance system observability and reliability.

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At its core, ServiMon integrates key technologies such as Prometheus, Grafana, Kafka, and
Cassandra. Prometheus serves as the primary engine for real-time performance metric collection,
enabling efficient monitoring across multiple nodes. Grafana provides interactive, service-oriented
data visualization, facilitating system performance analysis. Additionally, Kafka and Cassandra
expose system metrics via the JMX Exporter, offering critical insights into infrastructure availability
and performance.

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This contribution exposes how ServiMon could provide an enhancement on scalability, security,
and efficiency in a distributed computing environment, such as the CTAO monitoring, logging,
and alarm subsystems. This integrated approach not only ensures robust real-time monitoring, but
also optimizes operational costs. Furthermore, ServiMon’s ability to generate large volumes of
diverse data over time provides a strong foundation for predictive maintenance. By incorporating
stochastic and approximate computing techniques, it enables proactive failure detection and system
optimization, minimizing downtime and maximizing telescope availability.

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