> The results were striking: compared to traditional fat-tree networks, RNG (Resilient Network Graphs) uses 69% fewer routers, delivers 33% higher throughput, cuts network power by 40%, and lowers operating costs by 27. In early 2026, RNG became the default design for most newly built Amazon data centers globally.

> For cabling, they developed the ShuffleBox—a passive optical device whose internal wiring combined with randomized ShuffleBox-to-ShuffleBox cabling yields “quasi-random” graphs that behave like truly random graphs.

This is pretty incredible, random layouts of networks that have on-average better properties...

I'm really curious about the long tail of performance though. What is the worst case scenario here? And are there some better case scenarios? Uniformity in Clos networks is pretty great, but many loads don't need uniformity, and if these RNG-based networks have non-uniformity, perhaps that has operational characteristics that can be helpful or harmful.

It's interesting to see it being done at the data centre level as well.

Edit: Answering my own question, Jellyfish proved theoretically that random networks can be better, and this is a working implementation based on that solves the problems with creating/operating random networks.

It's not cheap, and it's limited to `us-east-1`, but it's at least _possible_ now via AWS Interconnect: https://aws.amazon.com/interconnect/lastmile/pricing/

Although very interesting from a scientific point of view I always consider these use cases to be very unique to AWS / hyperscaler DC's and in no way a new 'blueprint' for how to build DC-networks/fabrics.