Blog post co-author and Timescale engineer here.

Thanks for the advice. FWIW, though, TimescaleDB supports multi-dimensional partitioning, so a specific "hot" time interval is actually typically split across many chunks, and thus server instances. We are also working on native chunk replication, which allows serving copies of the same chunk out of different server instances.

Apart from these things to mitigate the hot partition problem, it's usually a good thing to be able to serve the same data to many requests using a warm cache compared to having many random reads that thrashes the cache.