Fitness Analytics Platform

Overview

A reference design I built for the analytics layer behind a fitness product — the piece that turns workout completions, goal updates, and membership events into coach-facing metrics and product-health reports.

Role

I modeled the events, wrote the reporting queries, scheduled the aggregation jobs, and built the API endpoints that internal dashboards read from.

Problem

Coaches and product teams needed quick reads on engagement trends, but running those queries against transactional tables is slow and expensive. Activity events also land at different points in the user journey, which makes reporting consistency tricky.

Solution

I kept transactional writes and analytics aggregation on separate paths. EventBridge routes activity events into serverless workers, PostgreSQL holds normalized reporting tables, and Redis caches the high-traffic dashboard summaries coaches open again and again.

Outcome

Product analytics that sits close to the backend architecture while keeping operational data, reporting data, and dashboard read models cleanly separated. It's a reference design — built to show that separation, not to report live usage.