Rick Reed shares scalability and reliability insights, techniques, and hacks used and learned developing WhatsApp on an Erlang/FreeBSD infrastructure.
Dave McCrory discusses what it takes to build an Enterprise Platform as a Service, covering data services, core application capabilities and design principles, CI, monitoring, coding standards, dependencies, security, and deployment.
Kirk Pepperdine explains how to use the G1GC logging to improve app performance while reducing its hardware footprint.
Joakim Recht discusses how Tradeshift moved from manual deployment processes to automation and what this means in terms of organizational scalability, technology, transparency, and culture.
Fabrice Aresu discusses the challenges faced using HTML5 and data visualization at a large European Investment Bank, covering performance, architectural & design choices, and lessons learnt.
Benoît Chesneau discusses creating, scaling and reusing HTTP connections, summarizing techniques used to reduce memory usage in Erlang and ways to handle massive client connections efficiently.
Sponsored by Basho. Sean Cribbs discusses the theory behind several rich data types introduced with Riak 2.0 and then walking through some example applications that use them in popular languages.
Andy Davies, Aaron Peters present how networks, browsers and the way sites are built affect user experience, and take a look at some of the latest techniques for measuring and improving performance.
Sponsored by Azul. Gil Tene discusses issues with dynamically optimized environments used for trading systems along with techniques for dealing with them, including JVM performance tune up tricks.
Martin Thompson discusses the major steps in the evolution of Java and how it contrasts to alternative technologies, and the challenges of pushing the limits of performance.
Jonas Bonér discusses four key traits of Reactive Apps: Event-Driven, Scalable, Resilient and Responsive, how they impact application design, how they interact, related technologies and techniques.
Sponsored by Goldman Sachs. Java 8 has Streams, Scala has parallel collections, and GS Collections has ParallelIterables. Since we use parallelism to achieve better performance, it's interesting to ask: how well do they perform? We'll look at how these three APIs work with a critical eye toward performance. We'll also look at common performance pitfalls.
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Featured Blog Posts
We get a lot of questions about our analytics-driven Application Performance Management (APM) collection and analysis technology. Specifically, people want to know how we capture so much detailed information while maintaining such low overhead levels. Read More.
Most technology folks have heard Marc Andreessen’s provocative statement, “Software is eating the world.” Whether you agree fully or not, you’re realizing that your business critical software applications increasingly drive both the top-line revenue growth and the bottom-line operational efficiency of your company – and often form the pillar of your business... Read More.
Wouldn’t do website load/performance testing any more without having an APM tool in place. Period. Full stop. End of story. I’ve been involved in website load testing for over 10 years, as a “end-user” when I was web operations manager for an online job board, as a team leader for a... Read More.
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