Hi, one more result from the Cloud-TM project that we thought might be interesting for the Infinispan community (and possibly OpenShift). Our last effort is a system for automating elastic scaling for Infinispan, which we named TAS: Transactional Auto Scaler. TAS uses a hybrid methodology combining analytical modelling, for forecasting the effects of data contention, and machine learning techniques (we experimented both with Radial Basis Functions Aritificial Neural Networks and Regression Decision Trees), for forecasting the effects of contention on hardware resources. Applications of TAS range from on-line self-optimization of in-production applications, to the automatic generation of QoS/cost driven elastic scaling policies, and support for what-if analysis on the scalability of transactional applications. Results look pretty good, probably even better than we were originally hoping! ;-) Cheers, Paolo

So from a CloudTM perspective, this is a part of the adaptive, self-tuning configuration aspect of things? Or is it auto-provisioning (i.e., adding/removing nodes to meet QoS parameters)? - Manik On 4 Dec 2011, at 13:37, Paolo Romano wrote: > Hi, > > one more result from the Cloud-TM project that we thought might be > interesting for the Infinispan community (and possibly OpenShift). > > Our last effort is a system for automating elastic scaling for > Infinispan, which we named TAS: Transactional Auto Scaler. > > TAS uses a hybrid methodology combining analytical modelling, for > forecasting the effects of data contention, and machine learning > techniques (we experimented both with Radial Basis Functions Aritificial > Neural Networks and Regression Decision Trees), for forecasting the > effects of contention on hardware resources. > > Applications of TAS range from on-line self-optimization of > in-production applications, to the automatic generation of QoS/cost > driven elastic scaling policies, and support for what-if analysis on the > scalability of transactional applications. > > Results look pretty good, probably even better than we were originally > hoping! ;-) > > Cheers, > > Paolo > _______________________________________________ > infinispan-dev mailing list > infinispan-dev(a)lists.jboss.org > https://lists.jboss.org/mailman/listinfo/infinispan-dev -- Manik Surtani manik(a)jboss.org twitter.com/maniksurtani Lead, Infinispan http://www.infinispan.org _______________________________________________ infinispan-dev mailing list infinispan-dev(a)lists.jboss.org https://lists.jboss.org/mailman/listinfo/infinispan-dev