https://blog.turboawesome.win/tags/java/ Recent content in Java on Bits, Trades & Systems Hugo en-us Wed, 20 Feb 2019 11:33:00 +0000 https://blog.turboawesome.win/2019/02/go-for-the-seasoned-java-developer-what-feels-familiar-what-doesnt/ Wed, 20 Feb 2019 11:33:00 +0000 https://blog.turboawesome.win/2019/02/go-for-the-seasoned-java-developer-what-feels-familiar-what-doesnt/ After seven years of Java, switching to Go as a primary language. The frictions, the surprises, and what I'd tell my past self. https://blog.turboawesome.win/2018/06/backpressure-in-practice-keeping-fast-producers-from-killing-slow-consumers/ Thu, 14 Jun 2018 10:33:00 +0000 https://blog.turboawesome.win/2018/06/backpressure-in-practice-keeping-fast-producers-from-killing-slow-consumers/ 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's what the options look like in practice. https://blog.turboawesome.win/2018/05/project-loom-preview-virtual-threads-and-what-they-mean-for-server-code/ Thu, 24 May 2018 09:38:00 +0000 https://blog.turboawesome.win/2018/05/project-loom-preview-virtual-threads-and-what-they-mean-for-server-code/ Project Loom's virtual threads promise to fix Java's thread-per-request scalability problem by making millions of lightweight threads practical. Here's what the early design looked like and why it matters for server-side Java. https://blog.turboawesome.win/2017/11/from-java-8-to-java-11-in-a-regulated-environment-what-actually-broke/ Wed, 08 Nov 2017 11:23:00 +0000 https://blog.turboawesome.win/2017/11/from-java-8-to-java-11-in-a-regulated-environment-what-actually-broke/ Migrating a large financial institution's Java estate from Java 8 to Java 11 involved removing internal APIs, JPMS module system friction, and more dependency surprises than expected. What actually broke and how we fixed it. https://blog.turboawesome.win/2017/10/building-mifid-ii-trade-reporting-infrastructure-an-engineers-view/ Tue, 03 Oct 2017 11:45:00 +0000 https://blog.turboawesome.win/2017/10/building-mifid-ii-trade-reporting-infrastructure-an-engineers-view/ 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. https://blog.turboawesome.win/2017/09/stream-processing-with-kafka-streams-vs-flink-a-real-comparison/ Wed, 27 Sep 2017 14:02:00 +0000 https://blog.turboawesome.win/2017/09/stream-processing-with-kafka-streams-vs-flink-a-real-comparison/ 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. https://blog.turboawesome.win/2017/04/reading-gc-logs-like-a-detective/ Tue, 18 Apr 2017 09:11:00 +0000 https://blog.turboawesome.win/2017/04/reading-gc-logs-like-a-detective/ GC logs are the most information-dense diagnostic output the JVM produces, and most engineers never learn to read them properly. A guide to interpreting G1GC logs and using them to diagnose real production problems. https://blog.turboawesome.win/2016/11/threading-models-in-java-which-one-does-your-system-actually-need/ Wed, 09 Nov 2016 10:22:00 +0000 https://blog.turboawesome.win/2016/11/threading-models-in-java-which-one-does-your-system-actually-need/ Thread-per-request, event-loop, work-stealing, single-threaded with message passing — Java supports all of them, but each optimises for different things. Choosing the wrong model means fighting the runtime rather than working with it. https://blog.turboawesome.win/2016/08/heap-dumps-and-flight-recorder-diagnosing-jvm-memory-problems-in-production/ Wed, 24 Aug 2016 14:55:00 +0000 https://blog.turboawesome.win/2016/08/heap-dumps-and-flight-recorder-diagnosing-jvm-memory-problems-in-production/ Heap dumps and Java Flight Recorder are the two tools that diagnose production JVM memory problems. Understanding how to capture them without killing the service, and how to read what they tell you, is a gap in most JVM engineers' toolkits. https://blog.turboawesome.win/2015/11/five-years-in-high-frequency-trading-what-i-actually-learned/ Thu, 12 Nov 2015 16:03:00 +0000 https://blog.turboawesome.win/2015/11/five-years-in-high-frequency-trading-what-i-actually-learned/ Looking back at five years of low-latency systems work: what the environment teaches you that you can't learn elsewhere, and what habits it instils that don't always transfer cleanly to other domains. https://blog.turboawesome.win/2015/10/zgc-and-shenandoah-what-low-pause-gc-means-for-trading-systems/ Thu, 01 Oct 2015 09:44:00 +0000 https://blog.turboawesome.win/2015/10/zgc-and-shenandoah-what-low-pause-gc-means-for-trading-systems/ In 2015 the JVM GC landscape was about to change significantly. ZGC and Shenandoah were in development, promising sub-millisecond GC pauses regardless of heap size. Here's what the previews looked like and what they meant for latency-sensitive Java. https://blog.turboawesome.win/2015/05/understanding-safepoints-the-jvm-pauses-nobody-talks-about/ Wed, 27 May 2015 14:38:00 +0000 https://blog.turboawesome.win/2015/05/understanding-safepoints-the-jvm-pauses-nobody-talks-about/ GC pauses get all the attention, but safepoints are a broader category of JVM stop-the-world events that affect latency in ways GC tuning can't fix. https://blog.turboawesome.win/2015/04/memory-mapped-files-in-java-chronicle-and-the-art-of-zero-copy-i/o/ Wed, 15 Apr 2015 09:53:00 +0000 https://blog.turboawesome.win/2015/04/memory-mapped-files-in-java-chronicle-and-the-art-of-zero-copy-i/o/ Memory-mapped files let you treat disk storage as if it's RAM — the OS handles the mapping and caching transparently. Chronicle Queue uses this to give you a persistent ordered log with throughput approaching raw memory bandwidth. https://blog.turboawesome.win/2015/03/building-a-trade-blotter-that-doesnt-lie-under-load/ Wed, 04 Mar 2015 10:12:00 +0000 https://blog.turboawesome.win/2015/03/building-a-trade-blotter-that-doesnt-lie-under-load/ A trade blotter shows traders their current positions and recent executions. When the system is under load, naive implementations show stale, inconsistent, or missing data. Here's the design that kept our blotter honest. https://blog.turboawesome.win/2015/01/chronicle-queue-vs-kafka-choosing-a-persistent-journal-at-nanosecond-scale/ Wed, 21 Jan 2015 10:44:00 +0000 https://blog.turboawesome.win/2015/01/chronicle-queue-vs-kafka-choosing-a-persistent-journal-at-nanosecond-scale/ Both Chronicle Queue and Kafka provide persistent, ordered message logs. Their performance profiles, operational models, and use cases are almost completely different. https://blog.turboawesome.win/2014/12/end-of-year-architecture-review-what-held-what-failed-what-changed/ Wed, 10 Dec 2014 14:33:00 +0000 https://blog.turboawesome.win/2014/12/end-of-year-architecture-review-what-held-what-failed-what-changed/ 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'd make differently now. https://blog.turboawesome.win/2014/10/benchmarking-without-lying-jmh-coordinated-omission-and-honest-numbers/ Wed, 29 Oct 2014 10:14:00 +0000 https://blog.turboawesome.win/2014/10/benchmarking-without-lying-jmh-coordinated-omission-and-honest-numbers/ Most latency benchmarks are wrong in the same ways. JMH solves the JVM measurement problems; coordinated omission is the harder issue that lives above it. https://blog.turboawesome.win/2014/09/aeron-reliable-udp-multicast-for-market-data-distribution/ Wed, 17 Sep 2014 13:28:00 +0000 https://blog.turboawesome.win/2014/09/aeron-reliable-udp-multicast-for-market-data-distribution/ Aeron is a message transport library built around reliable UDP and memory-mapped files, designed for the sub-microsecond latency and high throughput that market data distribution demands. Here's what it looks like in practice. https://blog.turboawesome.win/2014/08/choosing-a-gc-collector-for-low-latency-java-a-practical-comparison/ Wed, 06 Aug 2014 10:18:00 +0000 https://blog.turboawesome.win/2014/08/choosing-a-gc-collector-for-low-latency-java-a-practical-comparison/ CMS vs G1 vs parallel GC vs no-GC strategies. The tradeoffs as they actually played out in a latency-sensitive financial application, with real numbers. https://blog.turboawesome.win/2014/05/busy-spinning-vs-blocking-thread-strategies-for-ultra-low-latency/ Wed, 14 May 2014 10:31:00 +0000 https://blog.turboawesome.win/2014/05/busy-spinning-vs-blocking-thread-strategies-for-ultra-low-latency/ Blocking a thread hands control to the OS scheduler and costs you microseconds on wake-up. Busy spinning wastes a CPU core. The right choice depends on your latency target and hardware budget.