Autosuppress

Autosuppress is a capability in information technology and data management that automatically reduces or silences certain outputs, such as alerts, logs, or notifications, when they meet predefined criteria. The goal is to minimize noise while preserving visibility into important events.

Common approaches include threshold-based suppression (suppress if a metric remains normal for a period), rate limiting (limit the frequency of repeated alerts), deduplication (suppress duplicates within a window), and contextual or machine-learning–based suppression (consider surrounding events or historical patterns). Suppression can be implemented with time-based windows, escalation policies, or suppression lists. The technique is often integrated into monitoring, logging, and alerting pipelines to balance informativeness with stability.

Applications span IT operations and observability to reduce alert storms; cybersecurity and SIEM systems to avoid analyst fatigue; industrial automation and SCADA to suppress nuisance alarms; and data processing pipelines to drop redundant notifications. Autosuppress is also used in logging practices to trade off detail for system stability, commonly with configurable retention and sampling.

Implementation and governance considerations include policy design, auditing, and version control to ensure reproducibility and compliance. Overly aggressive suppression can hide critical incidents, so ongoing monitoring of suppression effects and regular policy reviews are necessary. Best practices emphasize explicit suppression criteria, the ability to override when needed, and thorough documentation of when and why suppression occurs, along with metrics to verify that important signals remain detectable. See also suppression, alert fatigue, and noise reduction.