Problem and Anomaly Detection with Zabbix

This one-day advanced training course is designed for engineers who are already using Zabbix and want to explore intelligent, data-driven monitoring techniques using anomaly detection.

This training focuses on leveraging Zabbix’s built-in capabilities for detecting unusual behavior and trends across monitored systems. It covers advanced trigger functions, baseline monitoring, trend prediction, statistical thresholds, machine learning integration possibilities, and how to distinguish between normal fluctuations and real anomalies. The course is ideal for those looking to reduce false positives and increase the accuracy of alerts in dynamic environments.

The course includes a combination of theoretical explanation and practical exercises, all performed in a virtual lab environment provided by our team. You’ll work through configuring anomaly-based triggers, using time-shift functions, applying historical data analysis, and fine-tuning detection thresholds. The exercises are designed around real-world use cases to provide both technical skills and conceptual understanding. The lab environment remains accessible during the course and for 24 hours after it ends, allowing you extra time to explore or repeat the exercises.

Comprehensive course materials will be provided, including slides, guided lab instructions, and example configurations, giving you both a reference and a toolkit for applying what you’ve learned in your own Zabbix instance.

Upon completion of the Advanced Anomaly Detection with Zabbix training, participants will have the skills and knowledge to implement proactive monitoring strategies, reduce alert fatigue, and improve the quality of incident detection. This course is especially useful for engineers responsible for maintaining complex or high-volume environments where early detection of performance or behavioral anomalies is critical.