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Cloud Migration and Scalable Deployment of Climate Analytics Platform for Global Market Expansion

eleks.com

Environmental Services

Climatology

Data Analytics

Climate Research

Legacy Infrastructure Limitations Hindering Commercialization

Existing deployment on Princeton University’s supercomputer lacked third-party accessibility, scalability, and commercialization capabilities despite its research excellence. The platform required cloud migration to enable global market access and support business-critical climate analytics.

About the Client

Provider of comprehensive climate data services combining gauge, satellite, and reanalysis datasets with advanced hydrological modeling for risk analysis and business intelligence

Strategic Migration Goals for Market Launch

Enable commercial market launch through secure cloud deployment
Ensure seamless accessibility of 70+ years of climate data for global users
Optimize analytics script performance in cloud environment
Establish foundation for future platform scalability and regional model expansion

Core System Capabilities

Historical precipitation data migration (70+ years)
Deployment of 21 analytics scripts with cloud-optimized execution
Climate monitor application containerization and orchestration
API integration for ecohydrological model access
Data security and access control framework

Target Technology Stack

Amazon Web Services (AWS)

Docker

Kubernetes

Python

PostgreSQL

System Interoperability Needs

University supercomputer data export interfaces
Global soil moisture modeling APIs
Third-party climate risk analysis tools
Enterprise SaaS analytics platforms

Operational Excellence Criteria

Petabyte-scale storage scalability
High-throughput data processing (ETL pipelines)
99.95% system availability SLA
NIST-compliant data security framework
Cross-region disaster recovery architecture

Business Transformation Outcomes

Successful AWS migration enabled global commercial access to critical climate data, supporting applications in water resource management, agricultural planning, and environmental risk assessment. The cloud infrastructure reduced time-to-insight by 60% while supporting 10x user growth compared to legacy system limitations.