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Sergiy is a research engineer at Microsoft Cloud and Information
Services Lab, where he is building large scale distributed systems for
big data and machine learning. He is a committer to the Apache REEF
project. Prior to Microsoft, Sergiy worked as a data research engineer
at Yahoo! Research, and tried his hand in building machine learning
systems at several Silicon Valley startups. Sergiy is interested in
machine learning, data stream processing, and high performance
distributed systems. His previous speaking experience includes high
profile conferences like UAI, MLDS, and HadoopSummit.

Abstract (Please help me to write a better one!):

Resource Managers like Apache YARN and Mesos have emerged as a
critical layer in the cloud computing system stack, but the developer
abstractions for leasing cluster resources and instantiating
application logic are very low-level. This flexibility comes at a high
cost in terms of developer effort, as each application must repeatedly
tackle the same challenges, like fault-tolerance, task scheduling and
coordination, and re-implement common mechanisms like caching and
bulk-data transfers.

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