High Performance Trading Infrastructure for Low Latency and Resilient Systems

At the TradingTech Summit London 2026, our CTO Deepak Dhayatker joined the panel “High Performance Trading Infrastructure – The Blueprint for Speed, Trust and Competitive Edge.” Alongside Anthony Warden of Citi, Diana Stanescu of Keysight Technologies, and Vlad Ilyushchenko of QuestDB, the discussion explored how trading infrastructure is evolving in response to increasingly complex, automated, and high-volume markets.

This article summarises the key themes from that conversation, with a particular focus on Deepak’s perspective on what it takes to build truly high-performance trading infrastructure today.

Introduction

High-performance trading infrastructure is no longer defined by speed alone. As markets become more fragmented, automated, and continuously active, the expectations placed on trading systems have fundamentally changed. Today, firms need infrastructure that not only delivers low latency but also behaves predictably under stress, scales without degradation, and provides full transparency into every event.

From Rapid Addition’s perspective, building high-performance trading infrastructure starts with a simple principle: performance tests in controlled lab conditions mean nothing until they are replicated in real-world production environments.

High Performance Must Be Proven in Real Conditions

Typically, trading system performance is measured in controlled environments. But modern high-performance trading infrastructure needs to be judged under the conditions that actually matter during sustained volatility and peak market stress.

Focusing on average latency can be a mistake. Tail latency is critical as this indicates whether system performance degrades under pressure. When markets are volatile, is when performance matters most, both in terms of latency and how quickly systems recover when something goes wrong. A platform that performs well under normal conditions but introduces delays during volume spikes cannot be considered high performance.

This perspective forces a more realistic approach to testing and measurement, one that reflects production environments rather than idealised test bench and UAT setups.

The Problem with Jitter

One of the critical challenges in achieving consistency for high-performance trading infrastructure is jitter – unpredictable latency spikes that tend to appear at exactly the wrong moment.

What makes jitter particularly difficult is that it often originates outside the core application. Background processes such as garbage collection, operating system scheduling, network contention or microbursts can all introduce instability. These are not always visible to development teams, yet they directly impact service quality.

Addressing performance consistency requires a holistic view. Instead of optimising individual components in isolation, firms need to analyse the full trading workflow (from market data ingestion through to order execution) and remove sources of unpredictability across the entire stack.

Resilience Is Part of Performance

Resilience is no longer a secondary concern; it is central to what defines high-performance trading infrastructure.

In electronic markets, failure is inevitable at some level. What matters is how systems respond. Recovery time and recovery point objectives have become critical metrics, reflecting how quickly a platform can return to a consistent and operational state. Ideally, systems are architected for message persistence through state replication in a high-availability design.

Equally important is the ability to restart systems cleanly after releases or failovers without introducing new inconsistencies. In this sense, resilience is a fundamental part of performance.

Scaling Without Breaking Performance

Expectations around scalability have also evolved. It is no longer sufficient to scale gradually over time. Trading systems are now expected to handle change in real time, whether that means onboarding new instruments, absorbing spikes in message volumes, or adding counterparties during the trading day.

High-performance trading infrastructure must support this kind of dynamic scaling without introducing latency or instability. The benchmark is no longer just scalability, but scalability without degradation, where performance remains consistent even as demand increases.

Why Traceability Matters

Another defining feature of high-performance trading infrastructure is traceability. If a system cannot clearly explain what happened, when it happened, and in what order, it becomes a risk.

This is increasingly important not only for regulatory compliance but also for operational visibility and issue resolution. Accurate, high-resolution timestamping allows firms to reconstruct events precisely, understand system behaviour, and diagnose issues far more effectively.

In practice, traceability turns infrastructure into a trusted system, not just a fast one.  

Removing Accidental Complexity

A common misconception is that achieving both speed and transparency requires trade-offs. In reality, the biggest obstacle to both is unnecessary complexity.

Over time, many trading environments accumulate layers of inconsistency because of the different operating systems, network configurations, deployment models, and tooling. This ‘accidental’ or ‘inherited’ complexity makes systems harder to optimise and understand, and therefore more difficult to fix and expensive to run.

Simplifying infrastructure through standardisation changes that dynamic. When environments are consistent and predictable, performance improves, debugging becomes easier, and systems become inherently more auditable and stable.

In many cases, high-performance trading infrastructure is the result of disciplined simplification rather than additional innovation.

A More Deliberate Use of Cloud

The role of cloud in trading infrastructure is often misunderstood. It is not about moving everything into the cloud, but about placing specific workloads where they make the most sense.

Latency-sensitive components, such as market data processing, signal generation, and order execution, still need to sit as close as possible to the venue on deterministic infrastructure. At the same time, workloads like analytics, risk management, and reporting benefit significantly from the scalability of cloud environments.

A hybrid approach allows firms to balance performance with flexibility, managing costs, and ensuring that critical paths remain optimised while less time-sensitive functions can scale efficiently.

Deterministic Transparency as the End Goal

Looking ahead, the direction of travel for high-performance trading infrastructure is deterministic transparency. This gives organisations the ability to produce a complete, accurate, and provable record of system behaviour at any point in time, including when systems fail or are recovering from failure.

This means knowing exactly what happened, when it happened, and in what sequence, across the entire trading environment. It provides a single, consistent version of the truth that can be used for compliance, analysis, and decision-making.

More importantly, it creates confidence. Confidence that systems behave as expected, that issues can be diagnosed quickly, and that growth will not introduce hidden risks.

Conclusion

High-performance trading infrastructure is no longer defined by raw speed or benchmark results.

It is defined by how systems behave in real conditions – under stress, at scale, and in moments of peak volatility. It requires consistency as much as speed, resilience as much as performance, and transparency as much as efficiency.

Firms that embrace this broader definition will be better equipped to compete in increasingly complex and liquid electronic markets. High-performance trading infrastructure shouldn’t be the fastest in theory, but a reliable, predictable, and provable one when it matters most.