Case Study
A Leading Equities and Derivatives Firm Re-orchestrates Legacy Workloads on the Cloud to Deliver a Modern Streaming Architecture
The solution delivers a modern cloud-based streaming architecture, resulting in a scalable, high-performance data and computing fabric.
Overview
The client clears billions of options contracts per year across 16 exchanges and is the world’s largest clearing corporation for listed equities options. The client is the buyer to every seller and the seller to every buyer in the U.S. listed options markets, responsible for maintaining liquidity and the efficient flow of trade in these markets.
Challenge
Due to an explosion of volume in the equities market and listed equity derivatives, the client wanted to re-build their market risk and margining platform. The end system was to support new volumes not seen before, offer new reporting and risk-assessment capabilities, and increase transparency and insight for clearing members into exposures via ad-hoc queries and real-time processing.
Solution
Ness was chosen as a partner to transition the client’s Risk and Margining system from a batch-based overnight process to a near-time, event-based system. Ness led the architectural design phase and recommended AWS as an infrastructure solution to scale and deliver. Our solution quickly utilized a computational platform based on Kafka for market and trade data and Flink as a scalable messaging platform that provided a foundation for the client’s needs in the future.
Result
The new platform leveraged a modern cloud-based streaming architecture resulting in a scalable, high-performance data and computing fabric. It leveraged Infrastructure as Code to allow each developer to spin up and test variable configurations of a Kafka and Flink application in AWS using self-service tools. The platform provided massive and near-perfect scaling to allow “overnight” batches every 20 minutes and the capability to do micro-batches of calculations, calculating intra-day risk. Further, it demonstrated control order, aggregation, and impact on performance.