Work Summaries

ML Training Platform

March 15, 2026 · 446 tests · 5 PRs open

End-to-end ML training platform built on ATHENA — model artifact management, feature extraction, TF inference, TFX training pipeline, and ClearML experiment tracking. All services run locally via standalone dev server.

Pull Requests

#	PR	Service	Tests	Description
1	#1083	Model Artifacts	89	SavedModel versioning, exclusive tagging, REST API, browser UI
2	#1084	Feature Extraction	180	Feature registry, lineage tracking, model-feature mapping, access analytics
3	#1085	Evaluation	82	TF inference pipeline, LRU cache, logging, Docker integration tests
4	#1088	TFX Pipeline	25	9-component TFX pipeline, Jupyter notebook, model registration scripts
5	#1090	Experiment Tracking	70	ClearML offline tracking, experiment comparison, best-model selection
		Total	446

Architecture

Raw Data → Feature Service (extract) → Evaluation Service (inference) → Prediction
↑
TFX Pipeline (train) → Model Artifacts (register) → Evaluation Service (load)
↑
ClearML (track) → Experiment Service (compare) → Best Model → Tag as prod

Browser UIs

Homepage Model Artifacts Feature Registry Evaluation Experiments Swagger API

Key Design Decisions

SQLAlchemy ORM with dedicated Base per service (SQLite local, PostgreSQL prod) — separate from Snowflake
Self-contained — all services run without Redis, Snowflake, or other production deps
ClearML offline mode — no server required, stores experiment data locally
TFX on Linux/Colab only — Apple Silicon not supported (no ARM64 wheels for ml-metadata)
446 self-contained tests — in-memory SQLite, temp dirs, no local machine dependencies

Merge Order

#1083 → #1084 → #1085 → #1088 → #1090