In this lesson, the Enterprise Architect’s role as an orchestrator shifts from simply connecting systems to actively deciding where workloads should run. In hybrid landscapes, this means balancing physical and logical placement while considering data gravity, latency, and resilience across various environments, ensuring that workloads are aligned with both technical constraints and business priorities.
To manage this complexity at scale, architects rely on the SAP Architecture Center as a strategic reference point for guidance. Instead of designing custom solutions, they use SAP Reference Architectures as pre-validated reference architectures. These patterns help make complex hybrid landscapes—spanning hyperscalers and legacy data centers—understandable to the business and easier to implement as repeatable, low-risk deployments, supporting consistent decision-making across architecture teams.
Core Deployment Patterns: Mechanics and Implementation
Hybrid landscapes usually follow a small set of recurring deployment patterns. In this section, we examine two common patterns that Enterprise Architects use to connect on-premise systems, cloud platforms, and distributed data—each addressing a specific architectural challenge.
Pattern 1: Cloud + On-Premise Integration (The Resilient Edge)
Many enterprises continue to run critical systems on-premise—such as SAP ECC or legacy mainframes—while adopting cloud services for innovation. In these scenarios, architects can use the Edge Integration CellRA0008to bridge on-premise environments with SAP BTP, enabling secure and reliable integration between core systems and cloud-based innovation.
Pattern 2: Multi-Cloud Integration (The Best-of-Breed Fabric)
Some organizations combine services from different hyperscalers—for example, SAP systems on Azure, analytics on AWS, and AI services on Google Cloud. In such scenarios, architects need a design approach that helps limit fragmentation and reduces unnecessary data movement. Using SAP Business Data Cloud (Datasphere) and the Delta Sharing protocol, hyperscaler AI services can, where appropriate, access SAP data products directly. This enables fast access while maintaining data integrity (RA0013), supporting scalable analytics and AI use cases without introducing unnecessary complexity.
Hybrid architectures rarely fail due to a lack of technology. They struggle when everyday architectural decisions are made inconsistently or without a shared framework of reference. In practice, Enterprise Architects are repeatedly asked to make the same kinds of choices: where workloads should run, how data should be accessed, and which integration style best fits a given scenario.
Lesson Summary
This lesson explored common hybrid deployment patterns and how Enterprise Architects use reference architectures to make consistent, informed decisions in complex landscapes. By examining cloud-to-on-premise and multi-cloud integration scenarios, you learned how patterns such as the Edge Integration Cell and SAP Business Data Cloud help reduce fragmentation and support governed data access. The lesson emphasized the importance of using shared architectural frameworks to guide workload placement, integration styles, and data access decisions across hybrid SAP environments, helping organizations scale their architectures in a controlled and predictable way.