High-Frequency Analytics Terminal
*CASE STUDY*

High-Frequency Analytics Terminal

WASM-Compiled High-Performance Dashboard visualizing active edge grids

TypeScriptRust WASMThree.js
*THE CHALLENGE*

The Opportunity

Visualizing massive node graphs of globally distributed servers in real-time caused heavy CPU spikes, making control dashboards sluggish and failing high-speed trades.

fintech-dashboard Mockup
*OUR APPROACH*

The Methodology

STAGE 1

Discovery & Planning

Comprehensive analysis of requirements, user needs, and technical constraints.

STAGE 2

Development & Execution

Softcr8ors compiled a custom Rust-based data parser into WebAssembly to parse server health statistics locally on the browser, rendering the results using hardware-accelerated WebGL charts.

STAGE 3

Testing & Launch

Rigorous quality assurance, performance optimization, and seamless deployment.

fintech-dashboard Mockup
*KEY FEATURES*

The Solution

Rust WASM-compiled engines parsing live transactional network logs.

Rust WASM-compiled engines parsing live transactional network logs.

Hardware-accelerated Three.js WebGL charting for real-time graphs.

Hardware-accelerated Three.js WebGL charting for real-time graphs.

Strict WebSockets streaming protocol managing server health updates.

Strict WebSockets streaming protocol managing server health updates.

Optimized Docker container architecture deploying to multiple edge regions.

Optimized Docker container architecture deploying to multiple edge regions.

TECHNOLOGIES

Tech Stack

Modern technologies and frameworks used to build this solution.

TSTypeScriptRust WASMThree.jsDockerTailwind CSS