Uber’s modern edge: a paradigm shift in network performance and efficiency

This new architecture, developed through a 10-month collaboration between Uber and Google engineers, directs traffic from Google’s Global External Application Load Balancer — fronted by Google Cloud Armor for DDoS protection and Cloud CDN for caching — directly to Uber’s on-premises infrastructure via Cloud Interconnect.

The results of migrating to Hybrid NEG-based load balancers were immediate. By removing all edge VMs, the traffic path became significantly more efficient, allowing Google’s global network to handle the long-haul transit over optimized channels. This shift delivered a 2.6% latency improvement at the 50th percentile and 10% at the 99th percentile, directly improving service responsiveness.

The results: impactful improvement

The migration delivered substantial improvements across three key areas. After validating the design and shifting 99% of edge traffic, the project achieved:

• Significant cost reduction: Removing the entire fleet of edge Envoy VMs resulted in a significant cost savings.
• Improved performance and user experience: The streamlined traffic flow improved latency for Uber’s mobile app users by 2.6% at p50 and 10% at p99.
• Simplified operations: Decommissioning the edge VMs reduced operational overhead and improved reliability through more standardized tooling.

“At Uber, every millisecond defines the user experience for millions of people. By re-architecting our global edge with Google Cloud and Hybrid NEGs, we’ve created a more direct, lower-latency path for our services. This not only enhances today’s user experience but also provides the high-performance foundation necessary for our next generation of AI applications, all while significantly reducing operational overhead for our engineering teams.” – Harry Liu, Director of Networking, Uber.

Key takeaways for enterprise teams

Uber’s edge architecture transformation demonstrates what focused technical collaboration can achieve. By replacing a distributed Envoy VM fleet with a streamlined architecture using Google’s global network and Hybrid NEGs, Uber achieved significant improvements in performance, cost, and reliability.

This migration succeeded in under a year through close collaboration between Uber and Google engineers. Key success factors included:

• Architectural validation: Google’s insights into its load balancer architecture helped validate that fewer proxy locations would improve performance, reduce operational overhead.
• Performance modeling: Google engineers modeled production-scale results from Uber’s initial tests, saving benchmarking time and providing the confidence to proceed.
• Simplified design: Hybrid NEGs eliminated the need for Envoy proxy VMs in Google edge.