Runtime Quality Foundation: Catch What Single-Column Monitoring Misses

ADOC 26.8.0 introduces runtime-quality capabilities intended to keep data trust signals current between catalog crawls and pipeline runs. Its new multivariate anomaly detection monitors relationships among selected groups of columns, automatically trains on historical data, and sends a single alert when correlated values drift, helping identify failures that column-by-column monitoring may miss while reducing alert volume. Unified key-value tagging consolidates tags and labels into a centrally managed system with automatic reconciliation, while Data Labelers classify new assets during discovery so patterns such as PII can be tagged before use in Data Products. Alert visibility is now automatically restricted to users’ assigned domains and resource groups, and Kafka-based asynchronous execution callbacks replace synchronous Control Plane calls to prevent completed jobs from being incorrectly recorded as errored during high load or outages. The release targets data engineers, platform teams, governance personnel, product owners, and domain stewards by improving anomaly detection, classification consistency, access-scoped incident visibility, and job-result reliability.

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