From Claude with some prompting
This image illustrates the flow and process of a Time Series Database (TSDB) system. The main components are:
Time Series Data: This is the input data stream containing time-stamped values from various sources or metrics.
Counting: It performs change detection on the incoming time series data to capture relevant events or anomalies.
Delta Value: The difference or change observed in the current value compared to a previous reference point, denoted as NOW() – previous value.
Time-series summary Value: Various summary statistics like MAX, MIN, and other aggregations are computed over the time window.
Threshold Checking: The delta values and other aggregations are evaluated against predefined thresholds for anomaly detection.
Alert: If any threshold conditions are violated, an alert is triggered to notify the monitoring system or personnel.
The process also considers correlations with other metrics for improved anomaly detection context. Additionally, AI-based techniques can derive new metrics from the existing data for enhanced monitoring capabilities.
In summary, this flow diagram represents the core functionality of a time series database focused on capturing, analyzing, and alerting on anomalies or deviations from expected patterns in real-time data streams.
Lechuck Park 