Error Intelligence
Pattern Clustering
Updated May 31, 2026 · today
Groups errors with similar templates so many variants of the same problem cluster into one alert. Surfaces brand-new clusters as they appear.
Example alert
Exact wording varies — the detector generates titles from the anomaly it finds. This is representative of what an alert looks like when it fires.
How it works
Template mining extracts the structural shape of each error message, reducing thousands of unique strings to a small set of recurring patterns. Semantic similarity then merges near-duplicates across services. New clusters surface the moment they first appear.
Availability
Runs on these tiers:
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Open alerts in the sandbox →Related detectors
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Catches errors that have never appeared in your 7-day baseline. On connect, the baseline seeds from your last 7 days of historical logs — push history for day-1 alerts, or wait a week for organic warm-up.