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 (e.g., "CPU usage > 90%").
• Relative alerts: Triggers based on a percentage change over a time window (e.g., "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.

Service maps

For services monitored by a Better Stack collector with eBPF enabled, ask AI SRE to "generate a service map."

This visualizes the connections between your services and shows key metrics like error rates and request rates on every edge. Inspect the colored edges and metrics to spot services with unusually high error rates or low request volumes.