Inzent Adds AI Anomaly Detection to eXperDB Monitoring
Inzent upgraded eXperDB's integrated monitoring with AI-based anomaly detection, consolidated log collection, predictive diagnostics and MCP support.
Inzent announced on the 12th that it has upgraded the integrated monitoring features of its data platform eXperDB with AI, according to dailysecu.com. The upgrade adds AI-based anomaly detection to the platform's monitoring stack.
The system learns normal baselines and detects anomalies in metrics such as CPU and memory usage and response speed. Alerts are classified by severity and sent via email, Telegram and SMS.
Inzent also added consolidated log collection across multiple servers, so administrators can identify causes from a single screen. A deep diagnostic feature predicts when disk and memory resources will reach their limits, and results can be delivered as plain-language sentences by connecting a company's own generative AI or LLM.
eXperDB now supports MCP (Model Context Protocol), allowing other internal AI agents to query DB status, performance information and alert history.
Background
eXperDB is an integrated data platform based on the open-source database PostgreSQL that combines monitoring, backup and recovery, and migration functions. Previously, database administrators had to manually check multiple metrics and logs to determine whether something was abnormal. Inzent plans to link diagnostic results to automated response actions and add features such as an AI index advisor.
Quick answers
What did Inzent upgrade in eXperDB?
Inzent upgraded eXperDB's integrated monitoring with AI-based anomaly detection, severity-classified alerts via email, Telegram and SMS, consolidated log collection, predictive diagnostics and MCP support.
What is the deep diagnostic feature in eXperDB?
It predicts when disk and memory resources will reach their limits, and results can be received as plain-language sentences by connecting a company's own generative AI or LLM.
What does MCP support in eXperDB allow?
It lets other internal AI agents query DB status, performance information and alert history.