Home » Author Archives: Nikita Salnikov Tarnovski (page 2)

Author Archives: Nikita Salnikov Tarnovski

Java performance tuning survey results (part IV)

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This is the last post in series where we analyze the results of the Java Performance Tuning Survey we conducted in October 2014. If you have not read the first posts, I recommend to go through the following first:                 Frequency and severity of performance problems Most popular monitoring solutions Tools and techniques ...

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Java performance tuning survey results (part III)

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This is the third post in a series where we analyze the results of a survey conducted in October 2014. If you have not already done so, I recommend to start with the first two posts in the series: problem severity analysis and monitoring domain analysis. This post focuses on troubleshooting / root cause detection. The background to this survey ...

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Java performance tuning survey results (part II)

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This is a second post in series where we analyze the results of the performance tuning survey conducted in October 2014. If you have not read the first part yet, we recommend to start here. Second part will focus on monitoring Java applications for performance issues. In particular, we try to answer the following questions:           ...

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Java performance tuning survey results (part I)

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We conducted a Java performance tuning survey during October 2014. The main goal of the survey was to gathering insight into Java performance world to improve the Plumbr product offering. However, we are happy to share the interesting results with you as well. The data that we collected provided material for a lengthy analysis, so we decided to divide the results ...

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Guess, don’t measure

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I have lost count in how many occasions I have recommended to start all performance tuning activities by setting goals and measuring baseline instead of tuning random bits in your source code. In the current post I will give you a counterexample about what just happened. We have been revamping our own internal monitoring tooling to make sure our production ...

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Adaptive heap sizing

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While enhancing our test bed to improve the Plumbr GC problem detector,  I ended up writing a small test case I thought might be interesting for the wider audience. The goal I was chasing was to test JVM’s self-adaptiveness in regard of how the heap is segmented between eden, survivor and tenured spaces. The test itself is generating objects in ...

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Revealing the length of Garbage Collection pauses

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There are several ways to improve your product. One such way is to carefully track what your users are experiencing and improve based on that. We do apply this technique ourselves and have again spent some time looking at different data Besides many other aspects we were after, we also posed a question “what is the worst-case effect for latency ...

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Reducing the frequency of major GC pauses

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This post will discuss a technique to reduce the burden garbage collection pauses put on the latency of your application. As I have written couple of years ago, disabling garbage collection is not possible in JVM. But there is a clever trick that can be used to significantly reduce the length and frequency of the long pauses. As you are ...

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Garbage Collection: increasing the throughput

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The inspiration for this post came after stumbling upon “Pig in the Python” definition in the memory management glossary. Apparently, this term is used to explain the situation where GC repeatedly promotes large objects from generation to generation. The effect of doing so is supposedly similar to that of a python swallowing its prey in whole only to become immobilised ...

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