Ditching Proxies Slashes AI Latency and Costs

Common proxy architectures for databases like Valkey add hidden costs and latency. A direct-access pattern can achieve microsecond speeds for AI workloads.

A presentation from InfoQ by engineer Dumanshu Goyal argues that a widely used architectural pattern is silently undermining the performance of modern AI systems. The culprit is the proxy layer, which sits between applications and databases like Valkey, an open-source fork of Redis. While intended to simplify connections, proxies introduce significant overhead. Goyal explains that this approach creates hidden CPU costs, increases the likelihood of slow user experiences due to high “tail latencies,” and concentrates risk into a single point of failure. Drawing a parallel with NASA’s redundant systems on the Space Shuttle, he advocates for a more resilient and performant design. This analysis suggests that for demanding, low-latency workloads such as AI feature stores, the conventional wisdom of using a proxy deserves serious reconsideration by engineering teams.

The core technical distinction lies between proxy-based and direct-access architectures. In a typical proxy setup, an application sends all its database requests to a single proxy server. This server then figures out which database node should handle the request and forwards it. This process adds an extra network hop and consumes CPU cycles on the proxy itself, introducing latency before the request even reaches the database. In contrast, a direct-access model uses a smart client library within the application. This client is “cluster-aware,” meaning it maintains its own map of the database topology. When the application needs to read or write data, the client connects directly to the correct Valkey node, completely bypassing any intermediary. This eliminates the proxy as a bottleneck, reducing network travel time and freeing up computational resources for more valuable work.

For developers, CTOs, and IT teams, the impact of this architectural shift is a dramatic leap in performance, moving from the millisecond to the microsecond range. This is not just a theoretical improvement; it is critical for real-time AI applications like fraud detection systems, ad-bidding platforms, and recommendation engines, where response time directly affects outcomes. Beyond speed, the direct-access model significantly improves system resilience. If a proxy server fails, it can take the entire application offline, creating a large “blast radius.” With direct access, the failure of a single database node is a contained event. The smart client simply detects the failure and reroutes traffic to a replica node, ensuring the application remains available and responsive with minimal disruption.

From a business perspective, adopting a direct-access Valkey architecture translates directly to competitive advantage and cost savings. Lower latency enhances the user experience, which can lead to increased engagement and revenue. For example, a faster recommendation engine can serve more relevant products, boosting sales. At the same time, eliminating the need for a separate fleet of proxy servers reduces infrastructure complexity and slashes cloud computing bills. This makes the overall system cheaper to build, operate, and scale. For founders and business leaders, this decision is more than a technical detail; it is a strategic choice that strengthens the product, improves operational efficiency, and directly impacts the company’s bottom line.

The timing of this discussion is significant, as Valkey emerges as a community-driven alternative to Redis following its recent license change. Backed by major industry players, the Valkey project is not just focused on maintaining compatibility but on pushing the boundaries of performance for modern data-intensive applications. Goyal's presentation highlights how the open-source community is actively refining best practices to meet the extreme demands of AI and machine learning. As companies build the next generation of intelligent applications, patterns like direct-access architecture will be crucial for building systems that are not only powerful but also efficient, resilient, and economically viable.