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How platform engineering and IDP observability can accelerate developer velocity

Dynatrace

As organizations look to expand DevOps maturity, improve operational efficiency, and increase developer velocity, they are embracing platform engineering as a key driver. The goal is to abstract away the underlying infrastructure’s complexities while providing a streamlined and standardized environment for development teams.

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Automating Success: Building a better developer experience with platform engineering

Dynatrace

When it comes to platform engineering, not only does observability play a vital role in the success of organizations’ transformation journeys—it’s key to successful platform engineering initiatives. The various presenters in this session aligned platform engineering use cases with the software development lifecycle.

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

Dynatrace

Application observability helps IT teams gain visibility in their highly distributed systems, but what is developer observability and why is it important? In a recent webinar , Dynatrace DevOps activist Andi Grabner and senior software engineer Yarden Laifenfeld explored developer observability.

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How To Use BenchmarkDotNet: 6 Simple Performance-Boosting Tips To Get Started

DZone

As software engineers, we are always striving for high performance and efficiency in our code. Whether it’s optimizing algorithms or fine-tuning data structures, every decision we make can have a significant impact on the overall performance of our applications.

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Dynatrace Perform 2024 Guide: Deriving business value from AI data analysis

Dynatrace

AI data analysis can help development teams release software faster and at higher quality. These are the goals of AI observability and data observability, a key theme at Dynatrace Perform 2024 , the observability provider’s annual conference, which takes place in Las Vegas from January 29 to February 1, 2024.

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Key Application Performance Metrics From the Viewpoint of a Statistician-Turned-Developer

DZone

Without application performance monitoring in place, you can’t accurately determine how well things are going. Is the app performant? Now that you’ve deployed your code, it’s time to monitor it, collect data, and analyze your metrics. Are people using your app? Do the pages load quickly? Are your users experiencing any errors?

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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data. Flink is the best candidate when EOS guarantees are necessary.