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Hadoop, Spark, PowerGraph, ...
memcached, nginx, ...
Commodity network and servers
Modern data centres, web applications and big data analytics require systems software to operate at unprecedented scale.
CamSaS is our initiative to build a systems software stack for the 21st century warehouse-scale data centres.
Twitter: @CamSysAtScale
Our paper on Firmament has been accepted for publication at OSDI 2016. The paper shows that Firmament's scheduling logic scales to very large clusters of 12,000+ machines despite being fully centralized, and that Firmament makes substantially better placement decisions than other schedulers.
Blog: the evolution of cluster scheduler architectures
9 March 2016Together with firmament.io, we're starting a new blog series on cluster scheduling. Our first post, on "the evolution of cluster scheduler architectures", discusses how cluster schedulers have changed over the last few years, and where increasingly widely-used open-source orchestration frameworks fit in.
Blog: speeding up graph analytics with 10G networks
8 July 2015Frank McSherry visited CamSaS and we wrote a blog post, "The impact of fast networks on graph analytics", together. The post shows that graph algorithms such as PageRank can benefit hugely from 10G networks, and demonstrates a 20x speedup over a GraphX/Spark stack.
Blog: applications of QJump's guaranteed latency
12 May 2015Our first blog post, "QJump, or: how to be un-British in the data centre" discusses why the guaranteed latency communication offered by QJump is exciting, and what new applications it may enable.
We are presenting our Musketeer paper at EuroSys 2015 on April 22. Find us at the conference, or follow Kermit!