Migrating Global Logistics Data to Azure with Zero Downtime
Modernizing complex supply chain data ecosystems with Azure, SingleStore, Airflow, and Kafka for scalability, security, and analytics readiness.
Migrating Global Logistics Data to Azure with Zero Downtime
Modernizing complex supply chain data ecosystems with Azure, SingleStore, Airflow, and Kafka for scalability, security, and analytics readiness.
Modernizing Complex Supply Chain Data Environments
The supply chain organization operated a highly complex on-premises data environment supporting critical operational workflows. Key challenges included legacy infrastructure with limited scalability and high maintenance costs, multiple interconnected systems, dependency-heavy workflows, tight delivery timelines, and risk of operational disruption during migration.
Technical Complexity & Business Requirements
The complexity of maintaining mission-critical supply chain operations while modernizing infrastructure created significant technical and business risks. Hundreds of interconnected data pipelines across domains with complex dependency chains required careful migration planning while maintaining zero tolerance for supply chain operational disruptions.
Phased Migration & Cloud Modernization Approach
Edstem employed a phased, agile delivery methodology with close collaboration with client and PwC teams. Each system was assessed based on business criticality, data size, dependencies, and migration risk to build a flexible 18-24 month roadmap.
Technology Stack
Cloud-Native Data Platform & Orchestration
Edstem delivered a comprehensive cloud-first solution with Azure cloud-native architecture, robust data engineering pipelines, DevOps & security enablement, and infrastructure monitoring via Datadog.
Cloud-Native Platform
Scalable, reliable, and secure architecture supporting operational and analytical workloads
Data Engineering & Orchestration
Robust pipelines, Airflow workflows, and Python/SQL transformations for consistent and reliable data processing
DevOps & Observability
CI/CD automation, secure infrastructure, and Datadog monitoring for operational reliability
Cloud-Native Architecture
Scalable and secure platform on Azure
Data Orchestration
Airflow, Python, SQL pipelines
Security & Governance
Role-based access and Key Vault integration
Monitoring & Observability
Datadog dashboards and alerts
Impact & Outcomes
Successful phased cloud migration minimized disruption, enhanced technical capabilities with elastic scalable data pipelines, strengthened security and governance, improved collaboration and efficiency, and built a future-ready data foundation for advanced analytics and AI/ML.
Before
- Legacy infrastructure with limited scalability
- Complex interconnected pipelines across domains
- High risk of operational disruption
- Manual processes and limited governance
After
- Cloud-native platform on Azure with SingleStore
- Elastic, reliable, and secure data pipelines
- Automated CI/CD workflows and DevOps enablement
- Full monitoring and observability with Datadog
MORE PROJECTS
