How does this scale for high-dimensional data? The example uses 2 dimensions - connections and latency - but real world (performance) data will often have many more associated variables. I don't know a lot about Bayesian methods but it seems like calculating joint posteriors would become slow.

But definitely a very interesting approach, and the Stan code is surprisingly readable!