Clear Clinica

Migrating HIPAA-compliant system

You need to migrate a clinical trial support system from aging Rackspace to AWS for better performance and scalability, and you can't afford downtime for critical research operations. How do you execute a seamless migration while maintaining high uptime?

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Clear Clinica had clinical trial support systems running on an outdated Rackspace setup.

The goal was clear - to proceed with supporting medical experiments, the infrastructure needed to be modernized and migrated to the cloud to improve performance, scalability, and reliability.

The challenge was executing this migration without disrupting ongoing clinical trials or compromising the uptime that researchers depend on. They needed to execute the transition smoothly while establishing a good foundation for long-term operations.

Quick facts

Clear Clinica

Life Sciences Clinical Trial Support

Clear Clinica provided technology solutions to medical professionals to conduct compliant clinical trials, requiring reliable, high-uptime infrastructure.

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Downtime during AWS migration

We executed Rackspace to AWS migration with minimal disruption to clinical systems, ensuring continuity of operations for critical medical research during the entire transition.

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The best couple
AWS + HIPAA

We designed a HIPAA-compliant infrastructure on AWS EKS for Node.js and PHP microservices, with Aurora, Redis, and S3 integrations.

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“ITSyndicate stands out because of their passion for problem-solving. Their efficiency and project management make them a valuable partner.”
Danny Lieberman

Danny Lieberman

CEO, Clear Clinica

What we did for Clear Clinica

Effort Distribution

“How do you migrate mission-critical systems without disruption?”

For Clear Clinica, this was a high-stakes cloud migration project requiring careful planning, expert execution, and ongoing operational support. Our process covered the full lifecycle: migration planning, cloud architecture design, performance optimization, and creating a dedicated support team to ensure long-term reliability for their clinical trial support systems.

  1. Planning and Executing the Migration. The engagement began with a detailed migration plan designed to minimize disruption. We architected a modern AWS environment using Amazon EKS (Kubernetes) to orchestrate their Node.js and PHP microservices, RDS (Aurora) for managed databases, Redis for caching, and S3 for scalable storage. The migration was executed smoothly, ensuring continuity of operations throughout the transition.
  2. Establishing a Robust DevOps Framework. For efficient ongoing development, we implemented a CI/CD pipeline integrated with BitBucket. The infrastructure was provisioned and managed entirely as code using Terraform, while Helm was used to deploy and manage Kubernetes applications. This automation reduced deployment times and ensured consistent, repeatable deployments.
  3. Performance Tuning and Optimization. Post-migration, we conducted comprehensive performance tuning to enhance infrastructure efficiency and application speed. This included optimizing resource allocation, fine-tuning the Kubernetes cluster, and leveraging Redis caching to reduce latency, resulting in a significantly improved user experience for researchers and clinical trial teams.
  4. Providing Dedicated 24-Hour Daily Support. To ensure high uptime essential for clinical research, we have established a dedicated support team that provides 24-hour daily coverage. This team operates in shifts to guarantee rapid issue resolution and proactive management of the system.
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HIPAA-readiness and proactive maintenance

By architecting the infrastructure with a "security by design" approach.

We start by mapping all Protected Health Information (PHI) data flows to understand where sensitive data lives and moves.

Based on this map, we isolate sensitive components into private subnets with strict IAM boundaries. We then enforce encryption for all data, both in transit (TLS) and at rest (using AWS KMS).

This is combined with comprehensive audit logging and least-privilege access policies, ensuring the platform aligns with HIPAA technical safeguards without slowing down developer velocity.

For Clear Clinica, we implemented end-to-end observability, providing not just real-time performance data, but a complete, immutable audit trail for compliance.

We implement a full suite of metrics, logs, and alerts covering the clusters, services, and databases. Besides, clear Service Level Objectives (SLOs) are established for key indicators like availability and latency.

So when an alert triggers, it's linked to a specific runbook that guides engineers to a faster resolution, reducing Mean Time to Resolution (MTTR).

For compliance, audit trails like AWS CloudTrail preserve a detailed history of every event.

No.

Backups are a component; true disaster recovery is a documented, practiced, and dependable capability that ensures clinical continuity.

Our process involves more than just automated snapshots. We define clear Recovery Point and Recovery Time Objectives (RPO/RTO) and document the full restore process.

Besides, we conduct regular recovery drills to test and validate these procedures, transforming the DR plan from a theoretical document into a proven, reliable process.

Through a combination of proactive FinOps practices and data-driven capacity planning.

The goal is to control spending without ever compromising the performance needed for clinical trials.

We implement right-sizing for compute resources, configure intelligent autoscaling policies, and use storage lifecycle policies to move data to more cost-effective tiers. This controls day-to-day spending.

For long-term planning, we create capacity forecasts based on current usage and projected trial workloads, ensuring the platform can scale smoothly to meet future demand.

By implementing a GitOps workflow, which establishes Git as the single source of truth for the entire system's desired state. This eliminates manual random changes made via the command line.

In this model, all changes to infrastructure or applications are made through pull requests (PRs) to a Git repository.

These PRs are subject to peer review and a series of automated CI checks. Only after being approved and signed are the changes automatically reconciled to the cluster.

Such a process provides a clear, auditable history of every change and allows for instant, reliable rollbacks.

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