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This cluster covers platforms and approaches for workflow automation and no-code/low-code development enabling rapid application and process creation.
Defines the standardized monitoring structure for no-code/low-code workflows: metrics, log groupings, alert categories, basic visualization components, aggregation windows and recommended retention periods. It specifies the content of default monitoring representations and the boundary to extended diagnostic data. Raw traces, raw event streams and export formats are excluded.
Concept for observing AI/ML systems in production, combining metrics, logs and model signals to track performance, drift and fairness.
Monitoring of workflow and pipeline execution, state and performance to detect errors and SLA violations early.