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Java memory optimizations: 3x Jenkins performance improvement with Dynatrace

Dynatrace

In my last blog I covered how our Engineering Productivity (EP) and Infrastructure & Services (IAS) Teams are ensuring that our DevOps tool chain is running as expected, even while workloads have shifted as our global engineering teams are now working from home. But let’s start from the beginning: Step #1 – Switching to Java 11.

Java 252
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Unmatched scalability and security of Dynatrace extensions now available for all supported technologies: 7 reasons to migrate your JMX and Python plugins

Dynatrace

focused on technology coverage, building on the flexibility of JMX for Java and Python-based coded extensions for everything else. address these limitations and brings new monitoring and analytical capabilities that weren’t available to Extensions 1.0: available, and more are in the pipeline. Dynatrace Extensions 1.0

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Optimizing Java XPath CPU and memory overhead by 98%

Dynatrace

Solution : Use optimized methods to access / query for specific data, e.g.: getNodeByType resulted in 98% reduction of CPU usage, better performance, returned high availability and reduced operational costs. One suggestion I want to give them on their way is to look into the practices of Performance Testing and Chaos Engineering.

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Geek Reading - Week of June 5, 2013

DZone

Making Google’s CalDAV and CardDAV APIs available for everyone ( Google Developers Blog). Pandora launches new HTML5 site for TVs and gaming consoles, available now on PS3 and Xbox 360 ( The Next Web). Linux System Mining with Python ( Javalobby – The heart of the Java developer community). Java EE 7 is Final.

Java 244
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Enhanced AI model observability with Dynatrace and Traceloop OpenLLMetry

Dynatrace

Engineers today lack an easy way to track the tokens and prompt usage of their LLM applications in production. Resource consumption: Observing computational resource availability and saturation, whether deployed in cloud-native environments like Kubernetes or CPU-enabled servers. However, Python models are trickier.

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Dynatrace Runtime Vulnerability Analysis now covers the entire application stack

Dynatrace

DevOps teams, SREs (site reliability engineers), platform teams, and SecOps teams aren’t always working from a common source of truth: SAST tools (static application security testing) provide scanning code for vulnerabilities. Dynatrace extends its Runtime Vulnerability Analysis to Go on top of Java ,NET , Node.js How to get started.

Java 234
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Kubernetes in the wild report 2023

Dynatrace

Java, Go, and Node.js Most Kubernetes clusters in the cloud (73%) are built on top of managed distributions from the hyperscalers like AWS Elastic Kubernetes Service (EKS), Azure Kubernetes Service (AKS), or Google Kubernetes Engine (GKE). Java, Go, and Node.js Java Virtual Machine (JVM)-based languages are predominant.