← All selected work
Performance and cost
Health-data storage redesigned around access patterns
Moved the right sensor payloads out of the primary database while preserving the product workflows that depended on them.
Primary evidence75%
less database storage
Situation
What the system needed to change
A health-tech platform serving more than 150,000 users was retaining large sensor payloads in its primary database, increasing disk use and operational cost.
Constraints
The boundaries mattered.
- 01
Existing product behavior could not break during migration
- 02
Large asynchronous payloads still needed reliable processing
- 03
The solution had to remain understandable to the product team
Decisions
The important engineering choices
- Separated frequently queried relational state from large object payloads
- Moved suitable data to S3-backed storage
- Kept the database as the source of truth for product-facing metadata
Outcome
What the work left behind
- Reduced database disk usage by 75 percent
- Preserved product access to historical sensor data
- Created a more durable boundary between transactional and object storage