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Overview

Watchdog Explains is an investigation assistant that detects anomalies on timeseries graphs and identifies which tags contribute to them. This allows you to immediately focus your investigation on problematic areas of your infrastructure or software stack.

To disable Watchdog Explains, see Disabling anomaly detection.

Watchdog Explains is available for Timeseries widgets with Metric data (avg, sum, min, and max aggregation).

How Watchdog Explains detects anomalies

Watchdog Explains applies anomaly detection to graphs on your dashboard by analyzing both the shape and value of the underlying timeseries. It identifies deviations from historical patterns, flagging spikes, dips, or gradual drifts that don’t align with expected behavior.

To account for seasonality, the algorithm looks back up to three weeks in time. For example, if a spike appears on a Monday at 9:00 a.m., Watchdog compares that datapoint against previous Mondays at the same hour. If similar patterns appear consistently, the spike is treated as seasonal and not flagged as an anomaly. This helps reduce false positives and ensures that only unexpected deviations are surfaced.

Anomalies can be sharp spikes or drops, but may also be more subtle trends like step changes or slope shifts.

Anomaly detection in Watchdog Explains works with Metrics data (avg, sum, min, and max aggregation).

Watchdog Explains isolates the cause with dimensional analysis

You can start your investigation from any timeseries graph that uses metric data. When Watchdog Explains detects an anomaly, it highlights the affected region with a pink box. To begin investigating, click Investigate Anomaly.

This opens a full-screen investigation view. Watchdog analyzes the anomaly and surfaces any tag groups that significantly contributed to the shape or scale of the anomaly. Click on a tag to see how removing or isolating that dimension affects the graph. Use this to identify root causes like specific customers, services, or environments.

Example: Surge in traffic from a single tenant

A spike in traffic is detected in the shopist-returns service. Watchdog surfaces a sharp increase in request volume, highlighted on the graph. Upon investigation, it attributes the anomaly to a single tag group: org_id:17728

A spike in Shopist Checkout Latency is quickly explained by Watchdog: the /apply-coupon route in eu-west-1 is the driver. This suggests that customers in that region experienced delays or were blocked when applying discount codes, directly impacting their ability to complete purchases.

Example of Watchdog Explains highlighting a root cause in a timeseries graph

At the same time, Shopist Payment Error Rate climbs. Watchdog Explains attributes the spike to payment_provider:adyen and a recent code change (version:2025.08.14). The release introduced errors that prevented some customers from completing payments, resulting in failed checkouts and revenue loss.

Tag breakdown in Watchdog Explains investigation

By automatically surfacing these contributors, Watchdog Explains narrowed the root cause from “checkout is slow” to “coupon submissions in eu-west-1 failed due to a recent code change on Adyen.” This clarity enabled a quick rollback and helped restore reliability.

Disabling anomaly detection

You can disable anomaly scanning on any dashboard. This only affects your view, other dashboard viewers still see anomalies unless they turn it off.
Disabling anomaly detection in Watchdog Explains

To disable anomaly detection on a dashboard, open Anomalies at the top of the dashboard and click Turn Off.

Further reading