Stephen Gelman is a Platform Architect with 13+ years building and operating large-scale, production infrastructure, currently leading platform efforts at Braintree and contributing as a Debian Developer. He combines deep systems engineering—spanning mail systems, virtualization, SANs, AD, Puppet, and cluster/HA tooling—with software skills in Python, Java, C and shell to automate and harden complex environments. A pragmatic leader who progressed from production engineer to group technical lead and architect, he’s shipped virtualization and Puppet-based provisioning that reduced costs and accelerated deployments. He’s an active open-source contributor with practical fixes to widely used projects like git-lfs and the Puppet Dashboard, showing attention to maintenance, dependency hygiene, and reporting correctness. Based in Chicago, he brings a rare mix of hands-on recovery experience (bare-metal Zimbra restores, PBX rebuilds) and long-term platform planning.
12 years of coding experience
16 years of employment as a software developer
Bachelor of Science, Computer Science, Bachelor of Science, Computer Science at Brandeis University
Contributions:16 commits, 13 PRs, 104 comments in 4 years 6 months
Contributions summary:Stephen primarily contributed to bug fixes and dependency updates within the git-lfs project. They addressed typos, replaced an outdated dependency (cheggaaa/pb) with a local function and updated the codebase to work with newer versions of dependencies like github.com/pkg/errors and spf13/cobra. The user also modified a parser for cookiejar files, replacing an existing one.
The Puppet Dashboard is a web interface providing node classification and reporting features for Puppet, an open source system configuration management tool
Role in this project:
Back-end Developer
Contributions:5 commits, 2 PRs, 10 comments in 6 months
Contributions summary:Stephen primarily focused on enhancing the Puppet Dashboard's reporting functionality. Their contributions include fixing YAML parsing exceptions, improving report sanitization processes, and adding support for new report formats introduced by different Puppet versions. They also added database columns to store report data and fixed the handling of Puppet 4.0 tags in reports.
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