Abbas Mohammed

As enterprises scale globally, self-managed streaming platforms often struggle with operational complexity, cost, and real-time data demands. In this session, we share how McDonald’s modernized its data streaming platform by migrating over 200+ workloads and 2,000+ topics across multiple kafka clusters processing over 300 million events/day (~25 TB/day) to a fully managed, cloud-native streaming service as part of a broader GCP transformation. Beyond the migration effort, we established a centralized Enterprise Data Highway as our foundation; designed to connect 40,000+ edge locations, digital channels, and IoT devices enabling real-time, event-driven data streaming across the enterprise where the data is always served fresh and fast while laying the groundwork for McDonald’s NEXT and proving the future of innovation is something we’re all lovin’. This session will highlight key architectural patterns, including bi-directional data replication, hybrid public/private cluster strategies, large-scale schema governance, future proofing, and robust edge-to-cloud synchronization with built-in offline resilience. Relevance to Real-World Data Streaming: Many enterprises face similar…