Benchmarking Apache Kafka: 2 Million Writes Per Second (On Three Cheap Machines)
Benchmarking Apache Kafka: 2 Million Writes Per Second (On Three Cheap Machines) I wrote a blog post about how LinkedIn uses Apache Kafka as a central publish-subscribe log for integrating data between applications, stream processing, and Hadoop data ingestion. To actually make this work, though, this "universal log" has to be a cheap abstraction. If you want to use a system as a central data hub
Garbage Collection Optimization for High-Throughput and Low-Latency Java Applications
Garbage Collection Optimization for High-Throughput and Low-Latency Java Applications High-performance applications form the backbone of the modern web. At LinkedIn, a number of internal high-throughput services cater to thousands of user requests per second. For optimal user experience, it is very important to serve these requests with low latency. For example, a product our members use regularly
Leaving JSPs in the dust: moving LinkedIn to dust.js client-side templates
Leaving JSPs in the dust: moving LinkedIn to dust.js client-side templates This is first of the three blog posts talking about how we build scalable, feature-rich, front-end apps for LinkedIn with an emphasis on site speed, performance, and developer productivity. Today, we'll tell you about our move from server-side templates, such as JSPs, ERBs, and GSPs, to client-side JavaScript templates powe
Tuning Java Garbage Collection for Web Services
Since I've been declared the local Java Garbage collection guru[1], I've found myself answering the same kinds of questions over and over. "Why am I getting frequent GC pauses?", "How do I avoid long GC pauses?", "Concurrent mode failure - how bad is that?" In the spirit of teaching people to fish, I thought I'd get together a blog post on how you (yes, you!) can tune the garbage collector for som
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Visualizing LinkedIn's Site Performance
