A Cloud Bigtable cluster is experiencing a hotspot and slow queries for globally distributed device data. How to fix and prevent hotspots?

Bigtable hotspots are typically caused by an uneven distribution of data across tablets, leading to some tablets receiving significantly more read/write requests than others. The most effective solution is to redesign the row key strategy to ensure keys are accessed in a random or evenly distributed pattern. This spreads the workload across all tablets and nodes, preventing hotspots. Using HBase APIs instead of Node.js APIs is irrelevant to hotspot prevention; the client library does not affect data distribution. Deleting old records might reduce overall data volume but doesn't address the fundamental issue of uneven access patterns on remaining data. Doubling the number of Bigtable nodes increases capacity but won't resolve hotspots if the row key strategy continues to direct traffic disproportionately to a few tablets.