Overview
A leading multinational corporation transitioned its on-premises SAP landscape to AWS and Azure through a phased multi-cloud approach designed for agility, scalability, cost efficiency, and long-term innovation.
Business Challenge
The organization needed to improve agility, scalability, and cost efficiency while transitioning an established on-premises SAP landscape.
The migration required careful handling of legacy SAP ECC dependencies, critical custom applications, real-time data replication, workload sequencing, and validation with minimal disruption.
SAI Technologies' Role
SAI Technologies supported a phased transformation of the established on-premises SAP landscape across AWS and Azure, with workload sequencing, automation, replication, and validation shaped around legacy dependencies and continuity requirements.
Solution Approach
A structured path from challenge to delivery
Assess
Complete a comprehensive assessment of the existing SAP cloud and application landscape.
Prioritize
Prioritize workloads based on criticality and the requirements of each SAP component, data store, server, and application stack.
Place
Use AWS for complex workloads and Azure for database operations according to the supplied multi-cloud strategy.
Secure
Protect the SAP cloud tenant and business data through the environment controls described in the source: ISO standards, SOC certifications, and continuous monitoring.
Migrate & Validate
Synchronize real-time data replication and apply robust validation mechanisms to support a controlled transition with minimal disruption.
Implementation / Architecture
Terraform and Ansible automated provisioning across AWS and Azure. During testing phases, this approach reduced deployment time by 60% and enabled faster iterations.
The migration required real-time data replication across continents. Robust validation mechanisms supported a seamless transition with minimal disruption.
Results & Business Value
Outcomes from this engagement
The multi-cloud transformation delivered immediate operational efficiencies and established a scalable foundation for future innovation.
The next phase described in the source focuses on advanced modernization use cases, including AI-driven analytics and serverless architectures.
Uptime
Redundant architecture across AWS and Azure ensured near-zero downtime in this use case.
Process Efficiency Increase
Process efficiency increased across lines of business after migration, with improved response time.
Cost Savings
Optimized resource allocation significantly reduced operational and overall costs.
Agility
Automated deployment pipelines allowed quicker scaling during peak demands.
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