Alinity

27,000 devices. Legacy infrastructure. FDA watching.

Abbott's Alinity diagnostic platform connects 27,000+ devices globally—blood analyzers, immunoassay systems, clinical chemistry instruments. Each device generates telemetry that feeds ML models for predictive maintenance and quality assurance.

The existing on-prem infrastructure was hitting limits. Model deployments took 6 months. The data pipeline couldn't handle burst traffic from new device rollouts. And an upcoming FDA inspection raised concerns about audit trail completeness.

I embedded with Abbott's data science and compliance teams. Mapped the existing architecture, identified HIPAA gaps, and documented every data flow that touched PHI.

AWS architecture built for FDA inspection.

Designed a 7-layer architecture on AWS that meets GxP (Good Practice) requirements for medical device software. Every design decision was documented in Architecture Decision Records for regulatory traceability.

Key architectural choices: VPC isolation for PHI workloads, encryption at rest and in transit, CloudTrail for complete audit logging, and infrastructure-as-code for reproducible deployments.

Zero-downtime migration. Zero audit findings.

Migrated the entire ML pipeline to AWS without disrupting device connectivity. Used blue-green deployment strategy with automatic rollback triggers.

Built comprehensive monitoring: real-time dashboards for device health, ML model performance tracking, and compliance metrics. Every component has defined SLOs with automated alerting.

From 6 months to 3 weeks.

Established CI/CD pipelines with automated compliance checks. Every deployment runs through validation gates that verify HIPAA controls, audit logging, and security configurations.

Trained 45+ data scientists on the new platform. Created runbooks for common operations, incident response procedures, and FDA audit preparation guides.

The Result

The FDA inspection came and went with zero findings. The audit team specifically commended the completeness of our logging and the traceability of our deployment process.

Model deployment time dropped from 6 months to 3 weeks—an 88% reduction. The platform now handles 150K+ events per second with 99.99% uptime, supporting Abbott's global diagnostic operations.