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    <title>Architecture on Bits, Trades &amp; Systems</title>
    <link>https://blog.turboawesome.win/tags/architecture/</link>
    <description>Recent content in Architecture on Bits, Trades &amp; Systems</description>
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    <lastBuildDate>Wed, 16 Apr 2025 13:12:00 +0000</lastBuildDate>
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      <title>Distributed Consistency Models: What Your Service Actually Guarantees</title>
      <link>https://blog.turboawesome.win/2025/04/distributed-consistency-models-what-your-service-actually-guarantees/</link>
      <pubDate>Wed, 16 Apr 2025 13:12:00 +0000</pubDate>
      <guid>https://blog.turboawesome.win/2025/04/distributed-consistency-models-what-your-service-actually-guarantees/</guid>
      <description>Linearisability, serializability, eventual consistency, causal consistency — these terms are used loosely and understood imprecisely. Knowing what your data store actually guarantees determines whether your distributed system is correct.</description>
    </item>
    <item>
      <title>Cross-Team Technical Alignment at Scale</title>
      <link>https://blog.turboawesome.win/2024/11/cross-team-technical-alignment-at-scale/</link>
      <pubDate>Wed, 20 Nov 2024 10:30:00 +0000</pubDate>
      <guid>https://blog.turboawesome.win/2024/11/cross-team-technical-alignment-at-scale/</guid>
      <description>Getting multiple engineering teams to agree on technical direction is hard. The approaches that work — architecture forums, decision records, working groups — and why lightweight coordination beats heavy governance.</description>
    </item>
    <item>
      <title>Cache Design as a Reliability Practice, Not an Optimisation</title>
      <link>https://blog.turboawesome.win/2024/03/cache-design-as-a-reliability-practice-not-an-optimisation/</link>
      <pubDate>Wed, 27 Mar 2024 11:47:00 +0000</pubDate>
      <guid>https://blog.turboawesome.win/2024/03/cache-design-as-a-reliability-practice-not-an-optimisation/</guid>
      <description>Most engineers add caches to make things faster. At scale, the more important reason to design caches carefully is reliability — a cache failure should not cascade into a system failure. The patterns that prevent that are different from the patterns that optimise for speed.</description>
    </item>
    <item>
      <title>Kafka at Startup Scale</title>
      <link>https://blog.turboawesome.win/2022/05/kafka-at-startup-scale/</link>
      <pubDate>Wed, 18 May 2022 14:00:00 +0000</pubDate>
      <guid>https://blog.turboawesome.win/2022/05/kafka-at-startup-scale/</guid>
      <description>Running Kafka at a startup is different from running it at enterprise scale. The operational complexity is real, the defaults are wrong for small clusters, and the failure modes are different from what the documentation implies.</description>
    </item>
    <item>
      <title>Technical Debt Is a Balance Sheet Item, Not a Moral Failing</title>
      <link>https://blog.turboawesome.win/2021/10/technical-debt-is-a-balance-sheet-item-not-a-moral-failing/</link>
      <pubDate>Wed, 06 Oct 2021 10:18:00 +0000</pubDate>
      <guid>https://blog.turboawesome.win/2021/10/technical-debt-is-a-balance-sheet-item-not-a-moral-failing/</guid>
      <description>The language around technical debt is usually moral: &amp;#39;bad code&amp;#39;, &amp;#39;dirty shortcuts&amp;#39;, &amp;#39;cutting corners&amp;#39;. The financial metaphor it&amp;#39;s named after is actually more useful. Debt is a tool. Manage it like one.</description>
    </item>
    <item>
      <title>The Platform vs Product Tension in a Growing Startup</title>
      <link>https://blog.turboawesome.win/2020/08/the-platform-vs-product-tension-in-a-growing-startup/</link>
      <pubDate>Wed, 12 Aug 2020 10:45:00 +0000</pubDate>
      <guid>https://blog.turboawesome.win/2020/08/the-platform-vs-product-tension-in-a-growing-startup/</guid>
      <description>Every startup engineering team eventually faces the platform question: invest in the foundation or keep shipping features? The tension is real, the tradeoffs are non-obvious, and the wrong answer in either direction is costly.</description>
    </item>
    <item>
      <title>Building the First Production Service at a Startup: Decisions Under Uncertainty</title>
      <link>https://blog.turboawesome.win/2019/06/building-the-first-production-service-at-a-startup-decisions-under-uncertainty/</link>
      <pubDate>Wed, 26 Jun 2019 10:44:00 +0000</pubDate>
      <guid>https://blog.turboawesome.win/2019/06/building-the-first-production-service-at-a-startup-decisions-under-uncertainty/</guid>
      <description>The first production service sets patterns the team will follow for years. At a startup, you&amp;#39;re making these decisions without full requirements, under time pressure, with a team that&amp;#39;s still forming. Here&amp;#39;s what we decided and why.</description>
    </item>
    <item>
      <title>What Big-Bank Engineering Taught Me About System Design</title>
      <link>https://blog.turboawesome.win/2018/08/what-big-bank-engineering-taught-me-about-system-design/</link>
      <pubDate>Thu, 23 Aug 2018 13:51:00 +0000</pubDate>
      <guid>https://blog.turboawesome.win/2018/08/what-big-bank-engineering-taught-me-about-system-design/</guid>
      <description>Three years at a large financial institution changed how I think about failure, compliance, and the relationship between constraints and good design. Not all of the lessons are obvious.</description>
    </item>
    <item>
      <title>Event Sourcing in Financial Systems: Real Benefits, Real Costs</title>
      <link>https://blog.turboawesome.win/2018/07/event-sourcing-in-financial-systems-real-benefits-real-costs/</link>
      <pubDate>Wed, 11 Jul 2018 11:03:00 +0000</pubDate>
      <guid>https://blog.turboawesome.win/2018/07/event-sourcing-in-financial-systems-real-benefits-real-costs/</guid>
      <description>Event sourcing is a natural fit for financial systems that require audit trails and point-in-time reconstruction. The costs are real too — projections, eventual consistency, and the event schema evolution problem.</description>
    </item>
    <item>
      <title>Backpressure in Practice: Keeping Fast Producers from Killing Slow Consumers</title>
      <link>https://blog.turboawesome.win/2018/06/backpressure-in-practice-keeping-fast-producers-from-killing-slow-consumers/</link>
      <pubDate>Thu, 14 Jun 2018 10:33:00 +0000</pubDate>
      <guid>https://blog.turboawesome.win/2018/06/backpressure-in-practice-keeping-fast-producers-from-killing-slow-consumers/</guid>
      <description>Every system has components that produce faster than consumers can handle under some conditions. Backpressure is the mechanism by which fast producers are slowed rather than dropping data or consuming unbounded memory. Here&amp;#39;s what the options look like in practice.</description>
    </item>
    <item>
      <title>Building MiFID II Trade Reporting Infrastructure: An Engineer&#39;s View</title>
      <link>https://blog.turboawesome.win/2017/10/building-mifid-ii-trade-reporting-infrastructure-an-engineers-view/</link>
      <pubDate>Tue, 03 Oct 2017 11:45:00 +0000</pubDate>
      <guid>https://blog.turboawesome.win/2017/10/building-mifid-ii-trade-reporting-infrastructure-an-engineers-view/</guid>
      <description>MiFID II required every trade to be reported within 15 minutes of execution. Building the infrastructure to meet that requirement across a large, heterogeneous estate taught us about the gap between regulatory requirements and production reality.</description>
    </item>
    <item>
      <title>Stream Processing with Kafka Streams vs Flink: A Real Comparison</title>
      <link>https://blog.turboawesome.win/2017/09/stream-processing-with-kafka-streams-vs-flink-a-real-comparison/</link>
      <pubDate>Wed, 27 Sep 2017 14:02:00 +0000</pubDate>
      <guid>https://blog.turboawesome.win/2017/09/stream-processing-with-kafka-streams-vs-flink-a-real-comparison/</guid>
      <description>We evaluated Kafka Streams and Apache Flink for a real-time trade enrichment and aggregation pipeline. The technical comparison produced a clear result; the operational comparison was more nuanced.</description>
    </item>
    <item>
      <title>When the Scale Changes: Moving into Institutional Finance</title>
      <link>https://blog.turboawesome.win/2016/01/when-the-scale-changes-moving-into-institutional-finance/</link>
      <pubDate>Wed, 06 Jan 2016 10:31:00 +0000</pubDate>
      <guid>https://blog.turboawesome.win/2016/01/when-the-scale-changes-moving-into-institutional-finance/</guid>
      <description>Four years in a latency-obsessed trading environment, then a move to a large financial institution where the problems — and the constraints — were completely different.</description>
    </item>
    <item>
      <title>Risk Aggregation in Real Time: Design Constraints from the Dealing Desk</title>
      <link>https://blog.turboawesome.win/2015/07/risk-aggregation-in-real-time-design-constraints-from-the-dealing-desk/</link>
      <pubDate>Wed, 08 Jul 2015 13:20:00 +0000</pubDate>
      <guid>https://blog.turboawesome.win/2015/07/risk-aggregation-in-real-time-design-constraints-from-the-dealing-desk/</guid>
      <description>Aggregating live risk across thousands of positions in real time is a different problem than batch risk. The constraints from the dealing desk — sub-second freshness, continuous availability, correct arithmetic — shaped everything.</description>
    </item>
    <item>
      <title>End-of-Year Architecture Review: What Held, What Failed, What Changed</title>
      <link>https://blog.turboawesome.win/2014/12/end-of-year-architecture-review-what-held-what-failed-what-changed/</link>
      <pubDate>Wed, 10 Dec 2014 14:33:00 +0000</pubDate>
      <guid>https://blog.turboawesome.win/2014/12/end-of-year-architecture-review-what-held-what-failed-what-changed/</guid>
      <description>A look back at three years of building HFT infrastructure: the components that held up under production load, the ones that were redesigned, and the architectural decisions I&amp;#39;d make differently now.</description>
    </item>
    <item>
      <title>FX Pricing Engine Architecture: From Feeds to Executable Quotes</title>
      <link>https://blog.turboawesome.win/2014/02/fx-pricing-engine-architecture-from-feeds-to-executable-quotes/</link>
      <pubDate>Wed, 19 Feb 2014 11:08:00 +0000</pubDate>
      <guid>https://blog.turboawesome.win/2014/02/fx-pricing-engine-architecture-from-feeds-to-executable-quotes/</guid>
      <description>End-to-end architecture of an FX pricing engine: LP feed ingestion, aggregation, spread logic, and quote distribution. The design choices that kept us under 500µs tick-to-quote.</description>
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