Brian Troutwine
Staff Engineer at Datadog
Oakland, California, United States
Summary
🤩
Rockstar🎓
Top SchoolBrian Troutwine is a Staff Engineer with 16 years building high-performance, fault-tolerant systems for memory- and CPU-constrained environments, currently focused at Datadog on single-machine performance and CI-friendly regression detection. He works primarily in Rust, Go, Erlang/OTP and C++, applies rigorous testing and benchmarking, and has driven measurable improvements in observability tooling such as the Vector pipeline. A published author of Hands-On Concurrency with Rust and frequent international speaker, he combines deep systems programming skills with practical devtools and infrastructure experience from startups to large cloud services. Based in Oakland, he’s known for finding and fixing hotspots at both algorithmic and atomic-instruction levels, making complex performance work accessible to non-experts.
15 years of coding experience
14 years of employment as a software developer
Bachelor of Science, Computer Science, Bachelor of Science, Computer Science at Portland State UniversityAssociate Degree of Science, Mathematics and Computing, Associate Degree of Science, Mathematics and Computing at Missouri Academy of Science, Mathematics and Computing
English
Stackoverflow
3,801reputation
193kreached
29answers
51questions
jenkins
top-5%
nginx
top-5%
Github Skills (21)
performance-optimization10
rust10
concurrency10
benchmark9
observability9
benchmarking9
nginx9
jenkins9
refactoring8
stream-processing8
refactor8
atomic8
atomics8
actor6
genserver6
Programming languages (17)
Github contributions (5)
vectordotdev/vector
Feb 2021 - Dec 2022
A high-performance observability data pipeline.
Role in this project:
Back-end Developer & Performance Engineer
Back-end Developer & Performance EngineerContributions:1139 reviews, 1167 commits, 534 PRs in 1 year 10 months
Contributions summary:Brian primarily focused on optimizing the performance of the Vector observability data pipeline by adjusting the atomics strength in the `gauge_add` function. They also made improvements to code quality by addressing clippy suggestions, and adding benchmarking to the `file-source` functionality, specifically the `read_until_with_max_size` function. Further, the user implemented performance improvements around the `to_alternative_strings` function, addressing a hotspot in the pipeline. The user made the further improvements to the performance and behavior of the codebase, including adjustments to metrics and testing.
stream-processingeventspipelinerustdata-observability
blt/Harmony
Jun 2010 - Aug 2010
Contributions:82 commits in 1 month
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