Uber de-risks hybrid AI with Cloud Interconnect
Uber adopted Google Cloud’s application-aware Cloud Interconnect to prioritize critical traffic during migrations and peak loads, reducing congestion risk and enabling a smoother transition to Google Cloud.
Uber collaborated with Google Cloud to deploy application awareness on Cloud Interconnect, an industry-first tool that prioritizes critical application traffic over less time-sensitive data in hybrid networks. This capability allowed Uber to classify and manage traffic using DSCP marking and queuing profiles, ensuring business continuity during high-traffic events and network congestion. The feature was tested in Phoenix, Arizona, and Ashburn, Virginia, before broader deployment across Uber’s infrastructure. By enabling real-time traffic prioritization, Uber maintained service reliability during planned and unplanned disruptions, a key requirement for its global operations.
Uber leveraged application awareness on Cloud Interconnect to optimize bandwidth utilization, avoiding the need for costly overprovisioning of network capacity. Instead of reserving excess bandwidth for peak usage, the tool aligned network resources with actual demand, reducing total cost of ownership for Uber’s infrastructure. This approach proved particularly valuable as Uber integrated AI workloads and data analytics, which require large-scale data transfers without compromising performance. The feature allowed Uber to handle massive data flows efficiently while protecting mission-critical applications from congestion.
The deployment of application awareness on Cloud Interconnect enabled Uber to migrate significant workloads to Google Cloud with reduced risk of service interruptions. By protecting critical applications from network congestion, Uber could proceed with its migration strategy while minimizing operational overhead. This migration supported Uber’s broader goals of modernizing its tech stack and embracing hybrid and multicloud strategies. The tool provided the stability needed to handle modern distributed applications and AI-driven workloads without compromising reliability.
Uber’s experience with application awareness on Cloud Interconnect serves as a blueprint for other enterprises facing similar hybrid cloud challenges. The core elements of this approach include ensuring business continuity, efficient bandwidth utilization, and unblocked workload migration. Harry Liu, Director of Engineering at Uber, emphasized the tool’s role in enabling strategic workload migrations and maintaining service reliability during peak demand. As enterprises increasingly adopt cloud-based AI models and distributed applications, the need for intelligent traffic prioritization becomes essential to avoid compromising critical services.