Sergey Odinokov is a seasoned software leader and founder with 13 years of experience building and scaling backend systems, currently serving as CEO of Hangfire OÜ from Thailand. He founded Hangfire and has deep expertise in .NET, multithreading, background job processing, Redis and SQL Server, pairing hands-on development with product leadership. An active open-source contributor, Sergey has made performance-focused improvements to widely used projects like Hangfire and the Cronos cron-expression library, optimizing parsing and serialization for real-world reliability and DST-aware scheduling. His background ranges from Delphi desktop systems to PHP startups and system administration, reflecting a practical full-stack systems mindset and an eye for performance engineering. Notably, he blends CEO responsibilities with continued low-level optimization work, demonstrating rare technical depth in a senior executive.
An easy way to perform background job processing in .NET and .NET Core applications. No Windows Service or separate process required
Role in this project:
Back-end Developer
Contributions:145 releases, 48 reviews, 3520 commits in 9 years 7 months
Contributions summary:Sergey primarily focused on enhancing the Hangfire framework, demonstrating a strong understanding of backend development principles. Their contributions involved moving type serialization logic to a dedicated class, adding new features such as a CompatibilityLevel switch, and optimizing date serialization for improved performance. Additionally, the user made code changes to address bugs and enhance the functionality of the Dashboard UI.
A fully-featured .NET library for working with Cron expressions. Built with time zones in mind and intuitively handles daylight saving time transitions
Role in this project:
Back-end Developer
Contributions:9 releases, 5 reviews, 92 commits in 5 years 9 months
Contributions summary:Sergey made several performance optimizations and refactorings to the `Cronos` library. They focused on improving parsing speed and efficiency through the use of aggressive inlining, fast bit operations, and optimized range parsing. Additionally, they added new benchmark methods to assess the performance of different parsing scenarios. The user's contributions centered around enhancing the library's core functionality and performance characteristics.
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