Greg Mann is a software engineer based in Berkeley with 13 years of experience building and operating large-scale compute platforms, currently focused on compute infrastructure at Netflix. He has deep systems and orchestration expertise from roles at Twitter and Mesosphere, including commit-level contributions and tech leadership on Apache Mesos and DC/OS. Greg’s work spans low-level platform refactors and test automation for critical cluster services, demonstrating comfort working from bare metal to platform APIs. His background in physical chemistry and academic computational research gives him a quantitative, experimental approach to debugging and performance tuning. Notably, he’s contributed to foundational open-source projects (Apache Mesos) and led Mesos foundations efforts supporting enterprise customers.
13 years of coding experience
9 years of employment as a software developer
Master of Science - MS, Physical Chemistry, Master of Science - MS, Physical Chemistry at University of California, Berkeley
SFSU, CSUEB, UC Berkeley, the Peralta Colleges
Bachelor of Arts (B.A.), Music and English, Bachelor of Arts (B.A.), Music and English at Oberlin College
Contributions:344 commits, 10 PRs, 102 pushes in 5 years 1 month
Contributions summary:Greg primarily worked on refactoring and improving the codebase, updating calls to `os::getenv()` and related functions throughout multiple core files within the repository. This involved updating and modifying multiple system components, demonstrating a high level of knowledge of the internal APIs of the project. In addition, the user made modifications to various example files and the core libprocess library, indicating the developer is responsible for both code architecture and maintenance.
Contributions:2 reviews, 78 commits, 87 PRs in 3 years 6 months
Contributions summary:Greg contributed to the test suite, specifically focusing on Marathon pod deployments and associated metrics. They implemented and updated test cases to validate pod functionality, including health checks and metrics collection. Additionally, the user made modifications to improve the test infrastructure and fixed logging inconsistencies, ensuring tests are reliable. The user also addressed upgrade test issues.
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