Back to the Future of Time Series Data
summary
Live demo uses InfluxDB + .NET + Grafana with line protocol, nanosecond timestamps and batch writes (20 points per cycle, 5s loop) to show writing high-throughput metrics and dashboarding. Queries use time bucketing and tight time filters to turn scans that could take minutes into ~600 ms. High‑cardinality is tamed by keeping high-cardinality fields as values, structured tag hierarchies and pre-aggregation, and multi‑tier retention; full demo + code on GitHub.
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chapters (11)
- 0:00Introduction
- 1:31Fundamentals of time series
- 3:21Understanding high cardinality
- 5:31Past analysis with SQL
- 9:11Pattern detection techniques
- 10:49Managing data growth
- 15:06Present monitoring and writes
- 20:00Taming cardinality
- 22:18Predicting the future
- 28:59DeLorean dashboard demo
- 44:03Advanced alerts and conclusion
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