Production Kubernetes for regulated medical imaging workloads.
Led platform engineering initiatives for enterprise healthcare AI and medical imaging workloads on GCP, modernizing legacy architectures to production Kubernetes under GxP and 21 CFR Part 11 compliance standards.
Modernizing healthcare workloads for scale and compliance.
Legacy Cloud Functions architectures lacked the operational scalability, fine-grained networking, and unified observability needed for enterprise medical imaging and AI services.
Workloads required strict adherence to GxP and 21 CFR Part 11 compliance standards, necessitating reproducible multi-environment infrastructure, rigorous audit logging, automated vulnerability scanning, and centralized identity federation.
GKE Platform Modernization & Security Lead
Led the infrastructure design and migration from legacy Cloud Functions to production-grade GKE clusters across Dev, UAT, and Production environments.
Enforced GxP compliance standards, integrated centralized Cloud Monitoring and alerts, and built reusable Terraform and Helm deployment pipelines.
Reproducible, compliant infrastructure as code.
Auditable delivery pipelines
Standardized GitOps releases with automated vulnerability scanning (Nessus), static analysis (SonarQube), and controlled release approvals.
Zero-drift environments
Declarative Terraform modules and Helm releases ensure Dev, UAT, and Production environments remain consistent and reproducible.
Centralized telemetry and SSO
Google Cloud Monitoring metrics with automated alert triggers, unified with Keycloak authentication and granular Kubernetes RBAC.
Migration from serverless to GKE
Transitioned compute-intensive medical imaging microservices to dedicated GKE clusters, improving memory headroom and request throughput.
Multi-region expansion
Deployed and supported GKE clusters across global regions, including launching Australia region infrastructure for healthcare AI services.
Identity federation with Keycloak
Configured centralized SSO, user management, and service-to-service authentication integrated with Kubernetes RBAC.
The choices behind the architecture.
A modernized, compliant foundation for medical AI workloads.
Successfully migrated legacy workloads to Kubernetes, achieved GxP compliance posture with automated Nessus scanning, and brought multi-region clusters online.