A leading stock exchange responsible for managing billions in daily equity and derivatives transactions. The client operates in an extremely high-frequency trading environment where system performance, scalability, and stability are mission-critical — especially during peak trading windows.
With increasing trading volumes and heightened volatility driven by algorithmic trading, the client needed a robust solution to:
Legacy benchmarking tools were insufficient to simulate realistic high-load scenarios or to provide fine-grained analysis of system behaviour under stress. Legacy systems were not equipped to handle modern market dynamics - especially the bursty nature of algo-driven trading and the concurrent flow of equity and derivatives orders.
Additional challenges included:
Oneture partnered with the client to design and build a Custom Benchmarking Simulation Platform — combining our expertise in Capital Markets, high-performance computing, and real-time systems.
Oneture designed and deployed a fully air-gapped Kubernetes cluster optimized for concurrent, low-latency trade ingestion and multi-asset class (Equity + Derivatives) support. We built all services in Golang for performance and deployed a scalable, pod-based TCP ingestion system inside the cluster.
Key features of our engagement included:
Time-Warping of Historical Order Data
Massive Load Generation
Cloud-Native Architecture
Granular Observability
The architecture centers around a highly available Kubernetes cluster (RKE2) running on RHEL 9, with one control-plane node and 10 worker nodes. Key technical components:
a. Golang-based TCP Ingestion System
b. Kubernetes-Native Pod Scaling
c. Real-Time Monitoring and Visualization