The panelists answer questions on C/C++ and Java performance, contrasting the virtues of native vs. managed code.
Delivering Performance Under Schedule and Resource Pressure: Lessons Learned at Google and Microsoft
Ivan Filho shares lessons learned during the development and release of several large scale services at Microsoft and Google from the perspective of a performance manager.
Ashley Puls methods and tools that can be used to uncover and resolve performance problems arising in Java web applications that use the Spring Framework.
Gil Tene examines the core issues that have historically kept Java environments from performing well in low latency environments and how it can perform now without trade-offs and compromises.
Kiran Prasad discusses what impact mobile has on architecture, explaining how HTML5 and Node.js can help, and sharing how to use these technologies effectively at scale.
Todd Montgomery proposes a new approach to marshalling in Java using FIX/SBE, new marshalling API approaches, and the extensive application of mechanical sympathy to this problem domain.
Zach Allaun shows how to build a functional and persistent vector, hash map, and set on top of the same data structure, and how to optimize the code for performance.
Martin Thompson discusses Java, concurrency, operating systems, and functional programming in the context of designing and testing high-performance systems.
Ryan Vanderwerf explains setting up Terracotta and clustering an applications using Ehcache, HTTP Session in Tomcat, and Quartz.
Martin Thompson overviews Java's evolution, comparing it with C++'s, discussing the challenges of pushing the performance limits.
Matt West explains how to use technologies like CloudStack, Beanstalk, Gearman, mod_gearman, Nagios, nagconf and other tools to monitor large web applications at scale deployed in the zCloud.
Xavier Amatriain discusses the machine learning algorithms and architecture behind Netflix' recommender systems, offline experiments and online A/B testing.
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