Scalable Cloud Infrastructure and Automated CI/CD Pipeline for Clinical Research Platform

The client faced limitations in scaling and automating their cloud-based clinical research platform due to legacy infrastructure and manual deployment processes. These challenges threatened their ability to maintain competitiveness, increased regulatory compliance risks, and risked system failures disrupting ongoing trials, thus compromising data integrity and patient safety.

A large healthcare technology provider offering cloud-based solutions for clinical research, enabling efficient study startup, pipeline management, and data analysis for research institutions, CROs, and sponsors.

• Achieve 20–25% reduction in total cost of ownership for computing services and databases.
• Reduce database costs by 30–40% through migration to more cost-efficient instances.
• Enhance load capacity by 3–4 times to support long-term growth over 3–5 years.
• Significantly decrease deployment times via automated CI/CD pipelines.
• Improve platform high availability and reliability with resilient infrastructure components.
• Eliminate existing bottlenecks using auto-scaling and clustered architecture.

• Migration of existing applications to a clustered architecture across multiple availability zones for high availability and scalability.
• Implementation of an Application Load Balancer for efficient traffic distribution.
• Integration of centralized, scalable file storage solution (such as EFS) for application data access.
• Secure management of credentials and secrets using a secrets management service.
• Deployment of session management support via in-memory caching systems (such as ElastiCache).
• Establishment of an automated CI/CD pipeline utilizing Infrastructure as Code (IaC) tools (e.g., Terraform) and automation workflows (e.g., GitHub Actions).
• Provisioning automation for new client environments to accelerate onboarding.
• Automated horizontal scaling via auto-scaling groups to adapt to demand fluctuations.
• Migration of legacy build and deployment scripts to modern, maintainable languages (e.g., Python).
• Implementation of managed database services with replication and failover capabilities.

• Secure integration with identity and access management systems
• Connection to external APIs for trial data and analytics
• Secure data transfer mechanisms for regulatory compliance
• Monitoring and alerting systems for infrastructure health
• Data storage and backup solutions

• System availability of 99.9% uptime with failover capabilities
• Scalability to support 3–4x current load capacity
• Deployment automation reducing release times by at least 50%
• Security standards including encrypted secrets management and data encryption at rest and in transit
• Cost efficiency targeting 20–25% reduction in overall TCO
• Compliance with relevant healthcare data regulations and standards

The project is expected to deliver a 20–25% reduction in total cloud infrastructure costs, a 30–40% decrease in database expenses through efficient instance selection, and a 3–4 times increase in load handling capacity. Additionally, automation will significantly decrease deployment times, improving platform reliability, reducing downtime, and supporting long-term growth, thus maintaining and enhancing the client’s competitive position in the clinical research industry.