Ryland Herrick is a Principal Software Engineer based in Madison, WI with 14 years of experience building secure, scalable backend systems and pragmatic front-end interfaces. He brings deep polyglot expertise (Ruby, JavaScript, Go, Elixir, Python and more) and a track record of shipping production features and security improvements for Elastic’s Kibana security solution, including ML alert suppression, rule import/export, and risk-scoring work for a widely used open-source stack. Ryland moves comfortably between hands-on engineering and technical leadership, having led Detections & Response teams and driven architecture as a principal at Elastic and earlier senior roles at boutique consultancies. He pairs rigorous testing and refactoring discipline with a curiosity for data and research—evident from early academic work in biology and statistics—to turn messy requirements into maintainable systems. Colleagues know him for thoughtful code hygiene, modular design, and quietly improving complex systems rather than chasing headlines.
13 years of coding experience
12 years of employment as a software developer
Bachelor of Science Biology Computer Science Mathematics, Bachelor of Science Biology Computer Science Mathematics at University of Wisconsin-Madison
Contributions:187 commits, 29 PRs, 33 pushes in 7 years 7 months
Contributions summary:Ryland focused on refactoring and improving the algorithmic logic used within the avatars-api-middleware. Their contributions involved simplifying the compute function, extracting and naming reduce functions, and adding tests to ensure the bucketing process worked correctly. They also worked on improving the modularity of the code, including renaming classes and extracting a hashing function into a separate module. They also set up a basic integration test.
Contributions:1148 reviews, 331 commits, 808 PRs in 2 years 4 months
Contributions summary:Ryland contributed to the security solution, focusing on rule engine improvements and security-related configurations. They developed code to improve the alert suppression for machine learning rules, and added support for the export and import of prebuilt rules. The user also fixed issues and added code for risk scoring calculations, including the use of asset criticality for alerts. Additionally, they implemented a system to make legacy indices compatible with the new alerts UI.
elasticdashboardskibanaobservabilitywindow
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Ryland Herrick - Principal Software Engineer at Elastic