Checking for outliers

Identify outliers and anomalies in your telemetry data using AI SRE's built‑in capabilities.

Query summaries

When you ask AI SRE to run a direct query on your logs or metrics, use the Summary output mode. The AI‑generated summary is specifically designed to highlight anomalies, including:

• Spikes and drops in values.
• Changes in error rates.
• Unusual periodic patterns.
• Capacity saturation.

The summary always points out "when" the anomaly occurred and "by how much" it deviated from the baseline.

Chart alerts

Create alerts on your dashboard charts with AI SRE. Choose from three types:

• Anomaly alerts: Uses a Robust Random Cut Forest (RRCF) model to learn the normal shape of your data and fires when current values look unusual. This is ideal for metrics with complex seasonal patterns.
• Threshold alerts: Triggers when a metric crosses a static value. For example, "CPU usage over 90%".
• Relative alerts: Triggers based on a percentage change over a time window. For example, "error rate increased by 50% in the last hour".

This is a proactive way to detect outliers, ensuring future anomalies automatically page the on‑call team.