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Predictive Datacenter Analytics with Strymon
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| by Vasia Kalavri Follow 0 Followers on Feb 16, 2018 |

Vasia Kalavri shares her research group’s ongoing work on Strymon: a system for predicting datacenter behavior in hypothetical scenarios using queryable online simulation. She highlights the challenges ETH Zurich Systems group is facing in building Strymon to support a diverse set of data representations, input sources, query languages, and execution models.

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Vasia Kalavri is a Postdoctoral researcher at the ETH Zurich Systems group, where she is working on distributed data processing, data center performance, and graph streaming. She is a PMC member of Apache Flink and a core developer of its graph processing API, Gelly.

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