Michael Bautin
Software Engineer at Google
Sunnyvale, California, United States
Summary
🤩
Rockstar🎓
Top SchoolMichael Bautin is a software engineer with 14 years of experience specializing in databases and distributed systems, currently working on Cloud SQL at Google. He founded and architected core components at YugaByte, contributed production-hardened features to Apache HBase and Spark, and has hands-on experience across startups and finance at ClearStory Data and D. E. Shaw. His PhD in Computer Science underpins a track record of improving storage engines, transaction logging, and cluster resilience—work that includes shoring up HFile performance and stabilizing distributed SQL internals. An active open-source contributor, he’s patched widely used projects (Spark, Chef knife-ec2) and focused on robustness and operability in real-world deployments. Based in Sunnyvale, he combines deep systems research with practical engineering for high-scale cloud databases.
14 years of coding experience
17 years of employment as a software developer
B.Sc., specialist, Mathematics, B.Sc., specialist, Mathematics at State University of Nizhni Novgorod named after N.I. Lobachevsky (UNN)Ph.D., Computer Science, Ph.D., Computer Science at Stony Brook University
Github Skills (25)
ec10
spark10
c-language10
postgresql10
spot-instances10
databases10
distributed-computing10
scala10
ruby10
chef-client10
amazon-ec210
chef-solo10
cprogramming-language10
concurrency10
database10
Programming languages (13)
Github contributions (5)
mesos/spark
Nov 2012 - Aug 2013
Lightning-fast cluster computing in Java, Scala and Python.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:14 commits in 9 months
Contributions summary:Michael contributed to the Spark project by addressing specific issues and enhancing existing functionality. They focused on modifying the core components, including `Utils.scala`, `TaskSetManager.scala`, `ApplicationInfo.scala`, `HadoopRDD.scala`, and `NewHadoopRDD.scala`. The changes primarily revolved around improving IP address configuration, logging preferred hosts, and making HadoopRDD configuration accessible, contributing to the project's overall robustness and usability.
pythoncluster-computinglightningsparkscala
chef/knife-ec2
Jan 2016 - Jan 2016
Chef knife plug-in for AWS EC2
Role in this project:Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:6 commits, 1 PR, 1 comment in 2 days
Contributions summary:Michael primarily focused on enhancing the functionality related to AWS EC2 spot instances. Their contributions included adding the capability to specify whether to wait for spot instances through the command line, refining how the system handles different wait modes, and fixing minor grammatical errors. The user also updated the codebase to treat empty or nil values for the spot wait mode the same as the "prompt" option.
ec2knifeplug-inawsplug
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