Monday,16 Mar 2026

Secrets to achieving sub-10ms response times in gaming and trading applications

1. Edge Computing Architecture and Bridging Geographic Distances
At GRAND, we believe that the speed of light is the primary obstacle; no matter how fast your code is, the geographical distance between the user and the server inevitably creates latency. To achieve response times of less than 10 milliseconds, we rely on an edge computing strategy, where backend logic is distributed across thousands of endpoints very close to the user, rather than depending on a single central server. Using services like Cloudflare Workers or AWS Wavelength, we process requests at the network edge, minimizing round-trip time. This architecture ensures that a video gamer or stock market trader can connect to a server just a few kilometers away, eliminating network latency and making interaction feel instantaneous.

2. Transport Layer Optimization (UDP vs. TCP) and Two-Way Protocols
Traditional protocols like HTTP/TCP rely on a "handshaking" system, which consumes valuable time verifying the arrival of each data packet. In Grand Theft Auto (GTA) gaming and trading applications, we move to faster protocols like UDP or QUIC, which send data without waiting for confirmation—a "fire and forget" approach. For applications requiring both stability and speed, we program high-performance WebSockets (gRPC) connections over HTTP/2, enabling a permanent, two-way communication channel between the client and server. This architecture eliminates the time spent opening and closing connections with each transaction and ensures real-time data streaming in fractions of a millisecond as soon as any market change or game move occurs.

3. In-Memory Processing & Zero-Disk IO
Access to the hard drive (even SSDs) is the enemy of speed in high-performance systems. At Grand, we design systems so that all critical operations take place exclusively within RAM. We use in-memory databases such as Redis or Aerospike, along with zero-copy technologies that prevent unnecessary data copying to the processor. In trading applications, the entire matching engine is located in RAM to ensure that thousands of trades are executed in seconds. This architecture ensures that the internal processing time within the server is only 1 or 2 milliseconds, leaving the majority of the time budget for data to travel across the network to the end user in less than 10 milliseconds.

4. Code Optimization and Low-Level Programming Languages ​​(Bare Metal Performance)
To achieve phenomenal performance, at Grand, we sometimes forgo high-level languages ​​that rely on garbage collection, such as Java or Python, in critical areas, and switch to languages ​​that offer complete memory control, such as C++ or Rust. We optimize the code to be cache-friendly, meaning that data is organized in memory in a way that allows the CPU to instantly find it in the L1/L2 cache without lengthy searches. Additionally, we use Kernel Bypass techniques that allow the application to access the network card directly, bypassing the operating system, saving crucial milliseconds. This extreme precision in code writing is what gives your application the raw power to handle millions of price updates or player moves simultaneously with absolute smoothness.

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