Data Archival Service

• Decreased cross-site data availability times by 85%, deleted 10% of the codebase, and ended a series of upload failures by eliminating the system's tight coupling with aging, failing hardware. For our team, this intervention decreased the system's operational burden and laid the groundwork for a cloud-based migration. For our customers, data were available minutes after upload, rather than days.

Browser-based Timeseries Plotting Library

• Reduced rendering time by 99.8%. This decrease allowed engineers to examine previously un-plottable timeseries, e.g., timeseries with 12 million points, which rendered in less than 300 milliseconds.

• Improved maintainability and reliability by modularizing the codebase and introducing tests on all state transitions. As a result, only three bugs were found during 1.5 years of daily use by hundreds of individuals.

Python Library for Timeseries Analysis

• Led transition from a restrictive, YAML-based DSL to a composable Python library by collecting customer feedback and gaining buy-in from stakeholders.