A scientific analysis platform, from fragile to production-grade in 33 days.
A venture-backed biotech ran its day-to-day science on an internal analysis platform that had quietly become hard to change and easy to break. In just over a month, I turned it into something the team could deploy, scale, and trust.
A platform the science depended on, that no one could safely change.
The platform was critical to everyday scientific work, but years of accumulated technical debt had made it fragile. There were no tests and no CI, no authentication or user tracking, and no real separation between development and production. Deployments were done by hand, large jobs failed often, and all the compute was pinned to fixed infrastructure.
The team needed it to become reliable, scalable, and maintainable, without pausing the science to get there.
- No automated testing or CI
- No authentication or user tracking
- No split between dev and production
- Limited operational visibility
- Manual deployments
- Compute locked to fixed infrastructure
- Frequent failures on large jobs
- A platform they could rely on
- Faster, safer engineering
- Less operational risk
- Compute that scales with demand
- A foundation to build on
Five fronts, in just over a month.
Engineering foundations
- 700+ automated tests
- Over 50% code coverage
- Validation on every pull request
- A structured release process
For the first time, the platform could be changed safely and with confidence.
Platform reliability
- Silent failures eliminated
- Structured logging
- End-to-end operational visibility
- Health monitoring and deploy automation
Engineers could diagnose issues in minutes instead of investigating by hand.
Infrastructure modernization
- Autoscaling CPU and GPU workers
- Queue-based asynchronous processing
- Infrastructure validation tooling
- Environment-specific configuration
Compute now scales with demand instead of hitting a fixed ceiling.
Security and access control
- Single sign-on and authentication
- User activity tracking
- Secret management
- Full environment isolation
Development and production are now completely separated.
Performance
- Peak memory cut by roughly 77%
- Large processing jobs stabilized
- More reliable job queue
- Failure recovery built in
The biggest jobs, the ones that used to fail outright, now finish.
Before and after.
| Metric | Before | After |
|---|---|---|
| Automated tests | 0 | 700+ |
| Code coverage | 0% | 52%+ |
| Authentication | None | SSO |
| Environments | 1 | 2 isolated |
| Deployment | Manual | Automated |
| Worker scaling | Fixed capacity | Autoscaling |
| Peak memory usage | 22+ GB | 5 GB |
A fragile system became a platform the team can build on.
In just over a month, the platform went from a fragile, manually operated system to a production-grade scientific platform: automated testing, scalable infrastructure, real operational visibility, deployment automation, and modern engineering practices throughout.
The team got immediate operational relief, and a foundation that future work can stand on rather than fight against.
Carrying production without a platform team?
Start with a 15-minute intro call, or send an email. We’ll talk through where your systems are today and what it would take to make them reliable.
Pick a time that works and it’s booked: a quick call to see whether I’m the right fit for what you’re building.
Pick a timePrefer email? Send a note about your team and systems and I’ll get back to you, usually the same day.
brent@brentmillsllc.com Send an email