Both MS and Google (whose respective faculty summits I attended these last 2 weeks) seem quite interested in Declarative Datacenter kinds of ideas.
Michael Isard at MSR Silicon Valley wrote about Autopilot in the most recent Operating Systems Review. It seems to deal with lower-level configuration aspects – ie it does not attempt to make policy decisions, nor (necesarily) provide a representation specifically designed to make representing those decisions easy.
Bob Coughran at Google says he’s very interested in this stuff and wants to visit us (RAD Lab) in fall to learn more about DDC. In particular, I was surprised that although they have some great machine-learning people, substantially all of them are working on apps (mostly search) but none(?) on using SML to improve datacenter operations. This isn’t to say they haven’t done interesting statistical analyses of data from their datacenters – the recent disk failures paper (FAST) and power management paper (ISCA) show this – but they don’t seem to be a part of a systematic framework for the “always-instrumented, always-analyzed” datacenter. An opportunity for us to engage Google better here.