Geo-temporal Flux is a powerful tool for analyzing time series data with geolocation capabilities. It uses S2 Geometry library to derive geo-temporal powers, allowing users to efficiently analyze data at scale. Geo-temporal analysis requires only latitude and longitude, but tagging data with S2 Cell Identifiers (IDs) helps to improve efficiency. Calculating S2 Cell IDs can be done at query time or as the data is written to InfluxDB, but this takes time and affects cardinality. The earthquake Lambda calculates and tags earthquakes with level 9 S2 Cell IDs at ingest time, striking a balance between granularity and cardinality. Geo-temporal Flux examples include real-time analysis of USGS earthquake data, using boxes, circles, and general polygons to filter rows and count earthquakes within specific regions or distances from events. InfluxDB's emerging geo-temporal capabilities are explored further in Tim Hall's InfluxDays roadmap presentation and can be used in various versions of InfluxDB Cloud 2.0, InfluxDB Enterprise 1.8, and InfluxDB OSS 2.0.