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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>quant.engineering</title><link>https://quant.engineering/</link><description>Software engineering at the edge:&lt;br /&gt;latency, failure and adversarial systems.</description><atom:link href="https://quant.engineering/feeds/all.rss.xml" rel="self"/><lastBuildDate>Sat, 21 Feb 2026 00:00:00 -0500</lastBuildDate><item><title>Inside DeFi's Hidden Economy: MEV, Mempools, and the Battle for Blockspace</title><link>https://quant.engineering/inside-defi-hidden-economy-mev-mempools-blockspace.html</link><description>&lt;p&gt;Step inside DeFi's hidden economy: how mempools, MEV and Flashbots turn transaction ordering into a latency-driven execution game where speed and visibility decide outcomes long before settlement.&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">rundef</dc:creator><pubDate>Sat, 21 Feb 2026 00:00:00 -0500</pubDate><guid>tag:quant.engineering,2026-02-21:/inside-defi-hidden-economy-mev-mempools-blockspace.html</guid><category>Decentralized Finance</category></item><item><title>From Blocks to State: A Mental Model for Blockchain Systems</title><link>https://quant.engineering/mental-model-for-blockchain-systems.html</link><description>&lt;p&gt;Blockchains are often explained through protocol-specific concepts like blocks or slots. This article reframes them as distributed state-transition systems, where ambiguity and delayed agreement exist to varying degrees across chains.&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">rundef</dc:creator><pubDate>Sat, 07 Feb 2026 00:00:00 -0500</pubDate><guid>tag:quant.engineering,2026-02-07:/mental-model-for-blockchain-systems.html</guid><category>defi-engineering</category></item><item><title>The Hidden DAG Behind Every Modern Trading System: How Market Data Is Ingested at Scale</title><link>https://quant.engineering/market-data-ingestion-dags-trading-system.html</link><description>&lt;p&gt;Modern trading systems rely on &lt;strong&gt;directed acyclic graphs (DAGs)&lt;/strong&gt; that branch, merge, and transform real-time feeds into many parallel consumers: matching engines, risk checks, analytics, surveillance, and storage. These ingestion DAGs exist to isolate failure, control fan-out, and preserve latency and correctness under extreme market conditions.&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">rundef</dc:creator><pubDate>Sat, 24 Jan 2026 00:00:00 -0500</pubDate><guid>tag:quant.engineering,2026-01-24:/market-data-ingestion-dags-trading-system.html</guid><category>dist-systems-in-finance</category></item><item><title>Flow Control in Low-Latency Systems: Batching, Conflation, and Backpressure</title><link>https://quant.engineering/flow-control-low-latency-batching-conflation-backpressure.html</link><description>&lt;p&gt;Low-latency systems fail when work becomes unbounded. Batching, conflation, and backpressure are mechanisms that keep systems stable under bursty, adversarial load. Without them, tail latency and cascading failures are inevitable.&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">rundef</dc:creator><pubDate>Sat, 10 Jan 2026 00:00:00 -0500</pubDate><guid>tag:quant.engineering,2026-01-10:/flow-control-low-latency-batching-conflation-backpressure.html</guid><category>low-latency-fundamentals</category></item><item><title>Observability at Scale: Distributed Telemetry for Modern Trading Infrastructure</title><link>https://quant.engineering/observability-at-scale-distributed-telemetry.html</link><description>&lt;p&gt;How do trading systems observe themselves in real time? This article breaks down the telemetry architecture that keeps distributed systems visible under extreme latency pressure.&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">rundef</dc:creator><pubDate>Sat, 13 Dec 2025 00:00:00 -0500</pubDate><guid>tag:quant.engineering,2025-12-13:/observability-at-scale-distributed-telemetry.html</guid><category>dist-systems-in-finance</category></item><item><title>How Exchanges Turn Order Books into Distributed Logs</title><link>https://quant.engineering/exchange-order-book-distributed-logs.html</link><description>&lt;p&gt;Every modern exchange is a distributed database in disguise. This article reveals how trading engines transform chaotic streams of buy and sell orders into a perfectly ordered, replayable log, ensuring fairness, determinism, and market data reliability.&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">rundef</dc:creator><pubDate>Sat, 06 Dec 2025 00:00:00 -0500</pubDate><guid>tag:quant.engineering,2025-12-06:/exchange-order-book-distributed-logs.html</guid><category>market-microstructure-global-systems</category></item><item><title>Latency Profiling in Python: From Code Bottlenecks to Observability</title><link>https://quant.engineering/latency-profiling-in-python.html</link><description>&lt;p&gt;Learn how to pinpoint where time disappears in Python systems, from CPU and I/O bottlenecks to Prometheus metrics and continuous profilers. Explore the tools that turn raw measurements into observability dashboards revealing real performance patterns.&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">rundef</dc:creator><pubDate>Sat, 29 Nov 2025 00:00:00 -0500</pubDate><guid>tag:quant.engineering,2025-11-29:/latency-profiling-in-python.html</guid><category>Low Latency</category></item><item><title>Understanding Latency: From Wire to Code</title><link>https://quant.engineering/understanding-latency-from-wire-to-code.html</link><description>&lt;p&gt;Every microsecond counts, but where do they actually go?&lt;br /&gt;&lt;br /&gt;This article traces the hidden journey of a message from the network wire to the application's code, revealing how the NIC, interrupts, syscalls, and runtimes introduce delay at every hop.&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">rundef</dc:creator><pubDate>Sat, 15 Nov 2025 00:00:00 -0500</pubDate><guid>tag:quant.engineering,2025-11-15:/understanding-latency-from-wire-to-code.html</guid><category>Low Latency</category></item><item><title>Dissecting the Infra of DeFi Protocols</title><link>https://quant.engineering/dissecting-infra-of-defi-protocols.html</link><description>&lt;p&gt;Most DeFi discussions stop at smart contracts. This article goes deeper: through the data pipelines, executors, keepers, and coordination layers that make protocols run. If you're a software engineer, you'll see how DeFi architecture mirrors the systems you already know.&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">rundef</dc:creator><pubDate>Sat, 08 Nov 2025 00:00:00 -0500</pubDate><guid>tag:quant.engineering,2025-11-08:/dissecting-infra-of-defi-protocols.html</guid><category>Decentralized Finance</category></item><item><title>What Database Scaling Looks Like When Milliseconds Mean Millions</title><link>https://quant.engineering/database-scaling-milliseconds-mean-millions.html</link><description>&lt;p&gt;Financial systems process billions of time-series data points with sub-millisecond query requirements: constraints that break traditional databases.&lt;br /&gt;&lt;br /&gt;Learn the architectural patterns that actually work: vertical scaling strategies, intelligent sharding schemes, and why market data demands different trade-offs than web applications.&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">rundef</dc:creator><pubDate>Sat, 01 Nov 2025 00:00:00 -0400</pubDate><guid>tag:quant.engineering,2025-11-01:/database-scaling-milliseconds-mean-millions.html</guid><category>Infrastructure</category></item><item><title>Introduction to DeFi Engineering</title><link>https://quant.engineering/introduction-to-defi-engineering.html</link><description>&lt;p&gt;An introduction to the engineering landscape in DeFi protocols: the distinct engineering roles (protocol, infrastructure, execution), the complete technology stack from smart contracts to off-chain systems, core primitives like liquidity pools and oracles, and what makes building in this space fundamentally different from traditional fintech.&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">rundef</dc:creator><pubDate>Thu, 23 Oct 2025 00:00:00 -0400</pubDate><guid>tag:quant.engineering,2025-10-23:/introduction-to-defi-engineering.html</guid><category>Decentralized Finance</category></item><item><title>How to Build Execution Systems for Crypto Trading at Scale</title><link>https://quant.engineering/build-execution-systems-crypto-trading-at-scale.html</link><description>&lt;p&gt;How do you execute $100M orders across 10+ crypto exchanges without moving the market? This deep-dive covers the infrastructure behind institutional trading systems: market data pipelines, smart order routing, execution quality metrics, and building for failure.&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">rundef</dc:creator><pubDate>Sun, 12 Oct 2025 00:00:00 -0400</pubDate><guid>tag:quant.engineering,2025-10-12:/build-execution-systems-crypto-trading-at-scale.html</guid><category>building-real-trading-systems</category></item><item><title>Ring Buffers 101: The Building Block of Low-Latency Systems</title><link>https://quant.engineering/ring-buffers-101.html</link><description>&lt;p&gt;An introduction to ring buffers, a foundational data structure for low-latency systems. We'll cover how they work, why they're fast, common variants, and practical use cases in real-time applications.&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">rundef</dc:creator><pubDate>Sat, 04 Oct 2025 00:00:00 -0400</pubDate><guid>tag:quant.engineering,2025-10-04:/ring-buffers-101.html</guid><category>low-latency-fundamentals</category></item><item><title>Message-Oriented Architectures in Trading Systems: Patterns for Scalability and Fault Tolerance</title><link>https://quant.engineering/message-oriented-architectures-in-trading.html</link><description>&lt;p&gt;Explore how message-oriented architectures power modern trading systems. Learn patterns, delivery guarantees, and broker trade-offs for high-frequency finance.&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">rundef</dc:creator><pubDate>Sat, 20 Sep 2025 00:00:00 -0400</pubDate><guid>tag:quant.engineering,2025-09-20:/message-oriented-architectures-in-trading.html</guid><category>Software Architecture</category></item><item><title>Canton: A Distributed Ledger for Global Finance</title><link>https://quant.engineering/canton-distributed-ledger.html</link><description>&lt;p&gt;Traditional settlement takes 2-3 days because banks can't trust shared state. Canton Network changes this with domain-based consensus and cryptographic privacy.&lt;br /&gt;&lt;br /&gt;First article in our &lt;strong&gt;Distributed Systems in Finance&lt;/strong&gt; series: we examine how Canton's distributed ledger achieves real-time settlement without sacrificing confidentiality.&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">rundef</dc:creator><pubDate>Sun, 07 Sep 2025 00:00:00 -0400</pubDate><guid>tag:quant.engineering,2025-09-07:/canton-distributed-ledger.html</guid><category>Distributed Systems</category></item><item><title>Interdependence of returns across multiple strategies</title><link>https://quant.engineering/interdependence-of-returns-across-multiple-strategies.html</link><description>&lt;p&gt;Many trading strategies show low correlations on paper, but that doesn't mean they're independent. In this article, we will explore the hidden risks in trading portfolios by understanding the interdependence of strategies and the limitations of correlation as a sole risk measure.&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">rundef</dc:creator><pubDate>Mon, 03 Mar 2025 00:00:00 -0500</pubDate><guid>tag:quant.engineering,2025-03-03:/interdependence-of-returns-across-multiple-strategies.html</guid><category>Portfolio construction</category></item><item><title>Setting up an Ubuntu 24.04 EC2 instance for algorithmic trading with Interactive Brokers</title><link>https://quant.engineering/setting-up-an-ubuntu-2404-ec2-instance-for-algorithmic-trading-with-interactive-brokers.html</link><description>&lt;p&gt;This article walks through the steps of setting up a new EC2 instance for algorithmic trading using Ubuntu 24.04 and Interactive Brokers. Running trading algorithms on EC2 provides scalability, reliability, and cost efficiency and is suitable for both paper and live accounts.&lt;/p&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">rundef</dc:creator><pubDate>Fri, 28 Feb 2025 00:00:00 -0500</pubDate><guid>tag:quant.engineering,2025-02-28:/setting-up-an-ubuntu-2404-ec2-instance-for-algorithmic-trading-with-interactive-brokers.html</guid><category>Infrastructure</category></item></channel></rss>