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Kubernetes in the wild report 2023

Dynatrace

Java, Go, and Node.js Through effortless provisioning, a larger number of small hosts provide a cost-effective and scalable platform. Of the organizations in the Kubernetes survey, 71% run databases and caches in Kubernetes, representing a +48% year-over-year increase. Java, Go, and Node.js

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Static Analysis of Java Enterprise Applications: Frameworks and Caches, the Elephants in the Room

The Morning Paper

Static analysis of Java enterprise applications: frameworks and caches, the elephants in the room , Antoniadis et al., If you try running Soot , WALA , or Doop out of the box on a real-world Java enterprise application you’re likely to get very low coverage, or possibly even no results at all if the tool fails to complete the analysis.

Java 80
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Stuff The Internet Says On Scalability For July 20th, 2018

High Scalability

That means multiple data indirections mean multiple cache misses. Mark LaPedus : MRAM, a next-generation memory type, is being touted as a replacement for embedded flash and cache applications. crabbone : This is the prism through which Java programmers view the world. They are very expensive. They never question this belief.

Internet 121
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Radically speed up your code by fixing slow or frequent garbage collection

Dynatrace

Java Memory Management, with its built-in garbage collection, is one of the language’s finest achievements. However, garbage collection is one of the main sources of performance and scalability issues in any modern Java application. You should also be careful when adding any sort of cache or object reuse strategy.

Speed 165
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Progressive delivery at cloud scale: Optimizing CPU intensive code with Dynatrace

Dynatrace

This is a great example of how valuable Dynatrace is for diagnosing performance or scalability issues, and a great testimony that we at Dynatrace use our own product and its various capabilities across our globally distributed systems. One of them being a small cache that would have brought the initial startup time down by about 95%.

Code 244
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Use Parallel Analysis – Not Parallel Query – for Fast Data Access and Scalable Computing Power

ScaleOut Software

Hosted on commodity clusters or cloud infrastructures, IMDGs harness the power of distributed computing to deliver scalable storage capacity and access throughput, along with integrated high availability. Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities.

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Use Parallel Analysis – Not Parallel Query – for Fast Data Access and Scalable Computing Power

ScaleOut Software

Hosted on commodity clusters or cloud infrastructures, IMDGs harness the power of distributed computing to deliver scalable storage capacity and access throughput, along with integrated high availability. Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities.