Overview
A National Institutes of Health (NIH) research agency faced mounting challenges in supporting their scientific community’s growing computational demands. Their legacy on-premise infrastructure was creating bottlenecks, with scientists experiencing weeks-long wait times for computational resources. PiTech partnered with the agency to design and implement a secure, compliant cloud infrastructure that reduced resource provisioning time from weeks to hours while maintaining FISMA compliance.
Key Results :
- 95% reduction in infrastructure provisioning time (from 3+ weeks to 4 hours)
- 40% cost savings on storage infrastructure through optimized cloud storage tiers
- 300% increase in computational capacity for research workloads
- Zero security incidents during and after migration
- FISMA Moderate compliance achieved and maintained
Client Background
Organization Profile
- Industry: Federal Healthcare Research
- Agency Type:NIH Research Institute
- Staff Size: 850+ scientists and support staff
- IT Environment: Hybrid on-premise and legacy systems
- Annual Research Budget: $500M+
The Challenge
The agency’s Computer Technology Branch (CTB) was struggling to keep pace with the exponential growth in research data volumes and computational requirements. Their scientists were conducting cutting-edge genomic research, clinical trials analysis, and epidemiological studies that generated terabytes of data daily.
Primary Pain Points:
- Extended Provisioning Times: Scientists waited 3-4 weeks for new computational resources, significantly delaying research timelines and grant deliverables.
- Limited Scalability:On-premise infrastructure couldn't scale quickly enough to meet peak computational demands during critical research phases.
- Storage Constraints: The agency's existing storage infrastructure was reaching capacity, with growth rates of 40% year-over-year creating urgent expansion needs.
- Budget Pressures: Capital expenditure requirements for hardware refreshes were consuming substantial portions of the IT budget, limiting innovation.
- Compliance Complexity: Any new infrastructure had to meet stringent FISMA Moderate requirements, HIPAA compliance for certain datasets, and NIH security standards.
The Chief Information Officer (CIO) recognized that traditional infrastructure expansion wouldn’t solve these fundamental challenges. The agency needed a transformative approach that could deliver agility without compromising security or compliance.
The PiTech Solution
Strategic Approach
PiTech assembled a specialized team with deep expertise in federal cloud migrations, NIH compliance requirements, and scientific computing workloads. Our approach focused on three core pillars:
1. Cloud Strategy Development
We conducted a comprehensive 4-week assessment that included:
- Current state infrastructure analysis and application portfolio review
- Stakeholder interviews with 25+ scientists, IT staff, and leadership
- Workload characterization to identify cloud-suitable applications
- Cost-benefit analysis comparing cloud vs. traditional infrastructure expansion
- Risk assessment and compliance gap analysis
Our team developed a phased cloud adoption strategy that prioritized quick wins while establishing a foundation for long-term hybrid cloud operations.
2. Secure Architecture Design
We designed a Virtual Private Cloud (VPC) architecture in Amazon Web Services (AWS) that addressed the agency’s unique requirements:
- Network Architecture: Multi-tier VPC design with public, private, and data subnets across multiple Availability Zones for high availability
- Connectivity: AWS Direct Connect integration with existing on-premise data center, ensuring low-latency, secure connectivity
- Security Controls: Implementation of AWS security groups, network ACLs, AWS WAF, and GuardDuty for threat detection
- Identity Management: Integration with existing Active Directory through AWS Directory Service
- Encryption: End-to-end encryption for data at rest (AWS KMS) and in transit (TLS 1.2+)
- Monitoring: Comprehensive logging through CloudTrail, VPC Flow Logs, and CloudWatch
3. Big Data Infrastructure
For the agency’s scientific applications, we architected a scalable big data platform:
- Compute: Auto-scaling EC2 clusters using spot instances for cost-effective batch processing
- Storage Tiers: Intelligent data lifecycle management using S3 Standard, S3 Intelligent-Tiering, and Glacier for archival
- Analytics: EMR clusters for genomic data processing and analysis
- Databases: RDS for relational data and DynamoDB for high-velocity research metadata
Implementation Process
Phase 1: Foundation and Pilot (Months 1-3)
Planning and Authorization
- Obtained Authority to Operate (ATO) documentation requirements
- Developed detailed migration playbooks and runbooks
- Established governance framework and change management processes
- Created security baseline and compliance documentation
Pilot VPC Deployment
We implemented a pilot VPC environment to validate our architecture and build confidence with the CTB team:
- Deployed production-grade VPC infrastructure across US-East-1 region
- Established Direct Connect connection (1 Gbps) to on-premise data center
- Configured hybrid DNS using Route 53
- Implemented centralized logging and monitoring
- Deployed bastion hosts and secure administrative access
Pilot Application Migration
Selected a genomic sequencing analysis application as the pilot workload:
- Application served 45 researchers
- Required processing of 2-5 TB datasets per analysis run
- Previously took 8-12 hours on on-premise infrastructure
- Migrated successfully with 99.9% uptime during transition
Results Presentation
We conducted a comprehensive presentation to the CIO and CTB leadership team, demonstrating:
- 60% reduction in processing time for pilot application
- Detailed cost analysis showing 35% savings potential
- Security assessment confirming all controls were operational
- Scalability demonstration handling 3x normal workload
The pilot’s success secured approval for broader cloud adoption.
Phase 2: Production Expansion (Months 4-8)
Workload Migration We migrated 12 additional scientific applications to the cloud environment:
- 3 genomic analysis pipelines
- 2 clinical trial data management systems
- 4 epidemiological modeling applications
- 3 research collaboration platforms
Each migration followed our proven methodology :
- Application assessment and dependency mapping
- Test environment setup and validation
- Parallel running period (2-4 weeks)
- Cutover with rollback procedures
- Post-migration optimization
Storage Infrastructure Assessment
Our team conducted a detailed review of the agency’s storage architecture:
- Current State: 850 TB of active research data across NetApp and Dell EMC arrays
- Growth Rate: 340 TB annual growth
- Access Patterns: 70% of data accessed within first 90 days, then rarely
- Compliance Requirements: 7-year retention for certain research datasets
Storage Roadmap Development
We created a comprehensive storage modernization strategy:
- Hot Tier: S3 Standard for actively accessed research data (first 90 days)
- Warm Tier: S3 Intelligent-Tiering for data with uncertain access patterns
- Cold Tier: S3 Glacier for compliance retention and rarely accessed archives
- Backup: S3 Glacier Deep Archive for long-term backup retention
Implementation of this tiered approach reduced storage costs by 40% compared to on-premise expansion plans.
Phase 3: Optimization and Knowledge Transfer (Months 9-12)
Performance Tuning
- Right-sized instances based on actual usage patterns
- Implemented Reserved Instances for stable workloads (35% cost reduction)
- Configured auto-scaling policies for burst workloads
- Optimized data transfer patterns to minimize egress costs
Training and Enablement
- Trained 15 CTB staff members on AWS services and management
- Developed standard operating procedures for common tasks
- Created self-service portal for scientists to request resources
- Established cloud center of excellence within the agency
Compliance Validation
- Completed full FISMA Moderate assessment
- Obtained Authority to Operate (ATO) from agency ISSO
- Documented security controls in agency's SSP
- Established continuous monitoring processes
Results and Business Impact
Quantifiable Outcomes
Operational Efficiency
- Infrastructure Provisioning: Reduced from 21 days to 4 hours (95% improvement)
- Application Performance: 40-60% faster processing for computational workloads
- System Availability: Achieved 99.95% uptime vs. 97.8% with legacy infrastructure
- Administrative Overhead: 50% reduction in time spent on infrastructure maintenance
Financial Benefits
- Year 1 Cost Savings:$1.2M compared to planned on-premise expansion
- Storage Cost Optimization:40% reduction through tiered storage strategy
- Capital Expenditure Avoidance: $3.5M hardware refresh deferred
- 3-Year TCO Reduction:28% lower than traditional infrastructure path
Research Impact
- Computational Capacity: 300% increase in available processing power
- Data Analysis Speed :Average analysis time reduced from 8 hours to 3 hours
- Research Projects Supported: 15 additional projects accommodated without infrastructure expansion
- Grant Competitiveness:Faster turnaround enhanced ability to meet grant deliverable timelines
Security and Compliance
- Zero Security Incidents: No breaches or compliance violations post-migration
- Audit Performance :Clean findings on first post-implementation FISMA audit
- Automated Compliance: 80% reduction in manual compliance reporting effort
- Incident Response:Mean time to detect security events reduced from 4 hours to 15 minutes
Qualitative Benefits
Enhanced Agility
The cloud infrastructure transformed how the agency responds to scientific needs. Scientists can now:
- Request computational resources through self-service portal
- Spin up development environments in minutes, not weeks
- Scale resources dynamically during peak analysis periods
- Experiment with new analysis techniques without long-term infrastructure commitments
Improved Collaboration
Cloud-based research platforms enabled better collaboration:
- Multi-institutional research projects with easier data sharing
- Remote researcher access during the COVID-19 pandemic
- Faster integration with external data sources
- Enhanced ability to participate in collaborative federal initiatives
Future-Ready Foundation
The VPC architecture established a platform for innovation:
- Foundation for machine learning and AI research initiatives
- Ability to rapidly adopt new AWS services as they become available
- Framework for additional workload migrations
- Model for other NIH agencies considering cloud adoption
Technology Stack Used
Cloud Platform
- Amazon Web Services (AWS) - Primary cloud provider
- AWS GovCloud - For sensitive workloads
- AWS Direct Connect - Hybrid connectivity
Core Services Implemented
- Compute: EC2, Auto Scaling Groups, EMR
- Storage: S3, EBS, EFS, Glacier
- Database: RDS (PostgreSQL, MySQL), DynamoDB
- Networking: VPC, Route 53, Transit Gateway
- Monitoring: CloudWatch, CloudTrail, VPC Flow Logs
- Management: Systems Manager, AWS Config, Service Catalog
Integration Technologies
- Directory Services: AWS Directory Service, ADFS
- Backup & DR:AWS Backup, cross-region replication
- Automation: CloudFormation, AWS CLI, boto3
Lessons Learned
Success Factors
- Executive Sponsorship: Strong support from the CIO was critical for overcoming organizational resistance and securing resources.
- Pilot Approach: :Starting with a well-chosen pilot application built confidence and validated the architecture before broader commitment.
- Security First: Addressing compliance requirements upfront prevented delays and rework during production deployment.
- Knowledge Transfer: Investing in training created internal cloud expertise, enabling long-term sustainability.
- Stakeholder Engagement: Regular communication with scientists ensured the solution met real research needs, not just IT requirements.
Major Challenges We Overcame
Cultural Change Management
- Initial skepticism from researchers accustomed to traditional infrastructure
- Solution: Pilot success stories and hands-on demos showing improved performance
Compliance Documentation
- Extensive ATO requirements and security control documentation
- Solution: Leveraged AWS compliance frameworks and automated documentation tools
Network Performance Concerns
- Fears about latency and bandwidth for large dataset transfers
- Solution :Direct Connect implementation and transfer optimization strategies
Cost Visibility
- Need for clear cost allocation to research projects
- Solution :Implemented detailed tagging strategy and custom cost dashboards
Methodology and Project Management
Agile Delivery Framework
PiTech utilized an agile methodology adapted for federal cloud migrations:
- 2-Week Sprints : Iterative development and deployment cycles
- Daily Standups :Quick coordination between PiTech and CTB teams
- Sprint Reviews :Regular demonstrations of progress to stakeholders
- Retrospectives : Continuous process improvement
Risk Management
We maintained a proactive risk management approach:
- Weekly risk review meetings with project leadership
- Detailed rollback procedures for every migration
- Parallel running periods to validate functionality
- Comprehensive disaster recovery testing
Quality Assurance
Multi-layered QA processes ensured production readiness:
- Automated security scanning of all cloud resources
- Performance testing before production cutover
- User acceptance testing with scientist representatives
- Independent security assessment by agency ISSO
Looking Forward: Ongoing Partnership
Following the successful implementation, PiTech continues to support the agency through:
Managed Services
- 24/7 monitoring and support for cloud infrastructure
- Monthly optimization reviews and recommendations
- Quarterly security assessments and compliance reporting
- Ongoing cost optimization consulting
Strategic Initiatives
- Machine learning platform development for genomic analysis
- Container orchestration using Amazon EKS
- Serverless architecture for data processing pipelines
- Multi-cloud strategy assessment
Continuous Improvement
- Regular architecture reviews and modernization recommendations
- New AWS service evaluation and adoption planning
- Training and certification support for CTB staff
- Best practices sharing across NIH community
Why PiTech?
Federal Cloud Expertise
PiTech brings specialized capabilities for government cloud migrations:
- Deep Federal Experience: 15+ years supporting federal agencies including NIH, FDA, and CDC
- Compliance Knowledge: Expertise in FISMA, FedRAMP, HIPAA, and agency-specific requirements
- AWS Partnership: AWS Advanced Consulting Partner with Government Competency
- Cleared Personnel: Team members with federal security clearances
Scientific Computing Specialization
We understand the unique requirements of research computing:
- Experience with genomics, proteomics, and bioinformatics workflows
- High-performance computing (HPC) architecture expertise
- Big data processing and analytics capabilities
- Research data management best practices
Proven Methodology
Our structured approach minimizes risk and accelerates value:
- Phased implementation with early wins
- Comprehensive testing and validation
- Knowledge transfer and enablement
- Long-term partnership focus
Get Started with Your Cloud Journey
Is your organization struggling with legacy infrastructure constraints? Are scientists waiting too long for computational resources? PiTech can help you achieve the same transformative results.
Our Cloud Solutions Include:
- Cloud Strategy & Assessment: Understand your readiness and develop a roadmap
- Architecture Design: Secure, compliant, and scalable cloud infrastructure
- Migration Services: Proven methodologies for seamless workload migration
- Managed Services: Ongoing optimization, security, and support
- Training & Enablement: Build internal cloud expertise
