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Optimizing Java XPath CPU and memory overhead by 98%

Dynatrace

The system saw up to 800 application requests per second – far more than anticipated. More worrisome was a spike in CPU usage, resulting in severe service disruption as backend processing systems crashed due to the spike in load. Therefore, it was unsurprising to see a huge spike in traffic for Family Visa enrollment via Metrash.

Java 223
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Principles to Handle Thousands of Connections in Java Using Netty

DZone

In today's article, I'm going to discuss common principles that need to be followed if we want to build a scalable application that can handle thousands of connections. I will refer to Netty Framework, TCP and Socket internals and some useful tools if you want to get some insights from your application and underlying system.

Java 352
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Transform mainframe applications into z/OS Java services with end-to-end transaction visibility and anomaly detection (Preview)

Dynatrace

Business, finance, and administrative applications written in the common business-oriented language (COBOL) have run tirelessly on IBM Z systems since the early 1960s. COBOL applications must be processed on expensive general processors, while Java applications are eligible to run on IBM Z specialty processors such as zIIPs.

Java 179
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Kubernetes in the wild report 2023

Dynatrace

As Kubernetes adoption increases and it continues to advance technologically, Kubernetes has emerged as the “operating system” of the cloud. Kubernetes is emerging as the “operating system” of the cloud. Java, Go, and Node.js Kubernetes is emerging as the “operating system” of the cloud.

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Dynatrace and Google unleash cloud-native observability for GKE Autopilot

Dynatrace

Dynatrace’s collaboration with Google addresses these needs by providing simple, scalable, and innovative data acquisition for comprehensive analysis and troubleshooting. The CSI pod is mounted to application pods using an overlay file system. These CSI pods provide a unique way of solving a handful of infrastructure problems.

Google 220
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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

which is difficult when troubleshooting distributed systems. Troubleshooting a session in Edgar When we started building Edgar four years ago, there were very few open-source distributed tracing systems that satisfied our needs. We chose Open-Zipkin because it had better integrations with our Spring Boot based Java runtime environment.

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Kubernetes OOMKilled troubleshooting: Diagnosing out-of-memory issues automatically

Dynatrace

Robert runs a multi-tenant e-commerce system on a managed Kubernetes environment. Both backend and report service are implemented in Java, but Robert found no Java runtime-related issues, either. This data confirmed that the system was killing off the report service pods for lack of memory. An out-of-memory issue lurks.

Java 191