Solving the Challenges of Counter Metrics and Resets in PostgreSQL/TimescaleDB

This text discusses the challenges of handling counter metrics and resets in PostgreSQL/TimescaleDB when working with time-series data from network devices or similar sources. The main issues include loss of connectivity, data inaccuracy, and increased complexity in troubleshooting. To address these problems, the author suggests using TimescaleDB's continuous aggregates feature to pre-aggregate time-series data for faster querying. Additionally, they demonstrate how to handle counter resets by leveraging TimescaleDB's counter_agg and interpolated_rate functions. The text emphasizes the importance of understanding data nuances and being persistent in finding the right approach for specific scenarios when working with time-series data.