Building a java tracer

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rahulrevo

Technology Education

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What's hot

With its ninth version, the Java platform has shifted gear and introduced biyearly releases. This was followed by a license change where Oracle, the steward of Java, now publishes a commercial and a non-commercial release of the Java virtual machine while other vendors took more space to promote their alternative builds of the OpenJDK. And in another flood of news, the Java EE specification was terminated and resolved into the Jakarta EE namespace. A lot has been happening in the traditionally conservative Java ecosystem, to say the least, and many users are wondering if they still can rely on the platform. This talk gives an overview of the Java ecosystem, summarizes the changes that have been, that to expect and why the evolution of the platform is good news to the community.

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While most bugs reveal their cause within their stack trace, Java’s OutOfMemoryError is less talkative and therefore regarded as being difficult to debug by a majority of developers. With the right techniques and tools, memory leaks in Java programs can however be tackled like any other programming error. This talks discusses how a JVM stores data, categorizes different types of memory leaks that can occur in a Java program and presents techniques for fixing such errors. Furthermore, we will have a closer look at lambda expressions and their considerable potential of introducing memory leaks when they are used incautiously.

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micro(-service) components. While this approach to building software - if done correctly - can improve a system's maintainability and scalability, distributed applications also introduce challanges for operations. Where monolithic applications typically offered direct access to extensive monitoring dashbords, such easy overview is no longer available when multitude services are loosly connected over a network. But how to keep track of a system of such dynamic state? Distributed tracing is a method of connecting interaction of different services on a network. Collecting and processing such tracing information again allows for the observation of a distributed system in its entirety. This talk shares the presenter's insights gained by working on the JVM-support of distributed tracing for the APM tool Instana. Doing so, it introduces the landscape of distributed tracing on the JVM, discussing popular approaches such as Dapper, Zipkin or Brave/OpenTracing. In the process, it is discussed how byte code instrumentation can be used to capture systems without requiring a user to set up the software under observation. The presentation finishes with a discussion of typical problems of distributed tracing solutions and carefully examines the performance penalties APM tools entail.

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For years we’ve been told that the JVM’s amazing optimizers can take your running code and make it “fast” or “as fast as C++” or “as fast as C”…or sometimes “faster than C”. And yet we don’t often see this happen in practice, due in large part to (good and bad) development patterns that have taken hold in the Java world. In this talk, we’ll explore the main reasons why Java code rarely runs as fast as C or C++ and how you can write really bad Java code that the JVM will do a better job of optimizing. We’ll take some popular microbenchmarks and burn them to the ground, monitoring JIT logs and assembly dumps along the way.

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Writing software for a virtual machine enables developers to forget about machine code assembly, interrupts, and processor caches. This makes Java a convenient language, but all too many developers see the JVM as a black box and are often unsure of how to optimize their code for performance. This unfortunately adds credence to the myth that Java is always outperformed by native languages. This session takes a peek at the inner workings of Oracle’s HotSpot virtual machine, its just-in-time compiler, and the interplay with a computer’s hardware. From this, you will understand the more common optimizations a virtual machine applies, to be better equipped to improve and reason about a Java program’s performance and how to correctly measure runtime!

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Глубже стек-трейсов, шире хип-дампов Stack trace и heap dump - не просто инструменты отладки; это потайные дверцы к самым недрам виртуальной Java машины. Доклад будет посвящён малоизвестным особенностям JDK, так или иначе связанным с обоходом хипа и стеками потоков. Мы разберём: - как снимать дампы в продакшне без побочных эффектов; - как работают утилиты jmap и jstack изнутри, и в чём хитрость forced режима; - почему все профилировщики врут, и как с этим бороться; - познакомимся с новым Stack-Walking API в Java 9; - научимся сканировать Heap средствами JVMTI; - узнаем о недокументированных функциях Хотспота и других интересных штуках.

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