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SKP's Java/Java EE Gotchas: Clash of the Titans, C++ vs. Java!

DZone

Considering all aspects and needs of current enterprise development, it is C++ and Java which outscore the other in terms of speed. According to other comparisons [Google for 'Performance of Programming Languages'] spread over the net, they clearly outshine others in all speed benchmarks. JAVA SOLUTION (Will Be Uploaded Later).

Java 214
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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. Optimize your code by finding and fixing the root cause of garbage collection problems.

Speed 164
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Unlock end-to-end observability insights with Dynatrace PurePath 4 seamless integration of OpenTracing for Java

Dynatrace

Cloud-native technologies and microservice architectures have shifted technical complexity from the source code of services to the interconnections between services. Deep-code execution details. Dynatrace news. Always-on profiling in transaction context. Upgrade OpenTracing instrumentation with high-fidelity data provided by OneAgent.

Java 222
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Best of breed observability with Spring Micrometer and Dynatrace

Dynatrace

Spring also introduced Micrometer, a vendor-agnostic metric API with rich instrumentation options. Soon after, Dynatrace built a registry for exporting Micrometer metrics. Our data APIs, which ingest millions of metrics, traces, and logs per second, are reconciled using Micrometer-based metrics.

Metrics 187
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Application observability meets developer observability: Unlock a 360º view of your environment

Dynatrace

When an incident occurs, developers need to know what data to look at, where the incident occurred, and other relevant metrics. But developers need code-level visibility and code-level data.” That’s not how I envision code-level observability,” Laifenfeld said. KubeCon North America is this week.

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Optimizing Python code during development

Dynatrace

For this blog post I want to focus on how you can leverage Dynatrace to get a lot of insight into your plugin code. Part 1 – The code as it stood. The Juniper plugin is an ActiveGate Plugin written in Python, it consists of a script that connects to a Juniper Networks device and collects some facts and metrics about it.

Code 115
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Kubernetes Observability: Code Profiling With Flame Graphs

Percona

It shows which code paths are more busy on the CPU in given samples. The idea behind this is to speed up cluster resources such as garbage collection, reduce image transfer over the network, and accelerate the application launch. Flame graphs are a graphical representation of function calls.

Code 106