A landmark day for platform observability and data pipeline reliability. We shipped a fully wired Jobs monitoring page that surfaces all 13+ tracked job types, broke through a major ETL performance ceiling on the SynPUF dataset (17 hours → 14 minutes for drug_era builds), and closed out a cohort generation audit that uncovered eight discrete bugs across the SQL builders, API layer, and frontend.
A massive day on the ingestion front — 87 commits landed in Parthenon today, almost entirely focused on building out a brand-new end-to-end data ingestion pipeline. We now have a fully wired system for creating ingestion projects, uploading raw files, staging them into a schema-isolated PostgreSQL environment, and handing off to Aqueduct for ETL. This has been a long time coming.
A massive day on Parthenon with 193 commits landing across the platform. The headlining work: a near-complete publication/manuscript workflow that takes study analyses all the way to a formatted, auto-numbered document preview, plus a long-overdue rename of the R Analytics Runtime to Darkstar — the name it's been running under in Docker all along.
Today was one of those satisfying days where two major workstreams converged: we pushed the Ares data quality module from skeleton to a fully featured analytics suite with four distinct intelligence phases, and we permanently fixed a cluster of compounding bugs that had been making Achilles characterization runs fragile on large real-world datasets. Both efforts move Parthenon meaningfully closer to being a production-grade OHDSI research platform.
After months of a perpetually red CI pipeline, today marks a turning point for Parthenon: 92 commits, a full-spectrum codebase review, a complete AtlanticHealth patient synthesis pipeline, and — most satisfying of all — every CI job green. Here's how we got there.
A quieter day on the Parthenon platform — today's commits centered on documentation infrastructure rather than feature work, with automated help content synchronization and the daily development blog pipeline keeping the platform's knowledge base fresh and up to date.
Every platform has a weak link. For Parthenon, it was the R container.
PHP handled 200 concurrent API requests without breaking a sweat. Python served AI inference with async workers. PostgreSQL managed million-row queries across six schemas. Redis cached sessions at sub-millisecond latency. And then there was R — single-threaded, fragile, running bare Rscript as PID 1 with no supervision, no timeouts, and a health check that lied.
This is the story of how we tore it down and built Darkstar — a production-grade R analytics engine that runs OHDSI HADES analyses concurrently, recovers from crashes automatically, and executes 35% faster than the container it replaced.
A big architectural day on Parthenon: we shipped the new Workbench launcher experience and drafted the formal plan to collapse our multi-database mess into a single, schema-isolated parthenon database. A noticeably cleaner codebase on the other side.
A massive 116-commit push today centered almost entirely on maturing the Evidence Investigation workbench — from retiring the old FinnGen UI to hardening the investigation experience with proper navigation, KPI metrics, URL-synced state, and ARIA accessibility. We also landed multi-dataset support in Morpheus and set the stage for one of the most requested features on the roadmap: volcano plots powered by the newly-renamed Darkstar R runtime.
A big day on the quality and resilience front: 34 commits landed in Parthenon focused on a comprehensive codebase health audit, a major expansion of our Playwright E2E test suite, and a fork of the StudyAgent submodule. No flashy new features today — instead, we did the unglamorous but essential work of making sure what we've already built actually works, is safe to change, and won't silently break in production.