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Alibaba is moving toward one of the most efficient cloud infrastructures for global online shopping. On the 2017 Double 11 Global Shopping Festival, Alibaba’s cloud platform achieved total sales of more than 25 billion dollars and supported peak volumes of 325,000 transactions and 256,000 payments per second. Most of the cloud-based eCommerce transactions were processed by hundreds of thousands of Java applications with above a billion lines of code.

It is challenging to achieve comprehensive and efficient performance troubleshooting and optimization for large-scale online Java applications in production. We proposed new approaches to method profiling and code warmup for Java performance tuning. Our fine-grained, low-overhead method profiler improves the efficiency of Java performance troubleshooting. Moreover, our approach to ahead-of-time code warmup significantly reduces the runtime overheads of just-in-time compiler to address the bursty traffic. Our approaches have been implemented in Alibaba JDK (AJDK), a customized version of OpenJDK, and have been rolled out to Alibaba’s cloud platform to support online critical business.

Presenter: Kingsum Chow, Jonathan Lu, and Sanhong Li
On November 11, 2017, Alibaba smashed its own online transaction record once again: the peak number of transactions per second reached 325,000. This talk describes how it achieved comprehensive and efficient performance profiling for large-scale applications by building tools based on OpenJDK.

Event Timeslots (1)

Room 2 – 2/21
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