Tue.Sep 03, 2024

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Why business resiliency depends on unified observability and security

Dynatrace

The world is more connected than ever before. With global e-commerce spending projected to reach $6.3 trillion this year 1 , more than two-thirds of the adult population now relying on digital payments 2 for financial transactions, and more than 400 million terabytes of data being created each day 3 , it’s abundantly clear that the world now runs on software.

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MLOps: How To Build a Toolkit To Boost AI Project Performance

DZone

Numerous AI projects launched with promise fail to set sail. This is not usually because of the quality of the machine learning (ML) models. Poor implementation and system integration sink 90% of projects. Organizations can save their AI endeavors. They should adopt adequate MLOps practices and choose the right set of tools. This article discusses MLOps practices and tools that can save sinking AI projects and boost robust ones, potentially doubling project launch speed.

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What are Kubernetes Pods? A Deep Dive

Percona

You might have driven a car, but have you ever wondered how the engine works? Similarly if you have used Kubernetes and if you are interested to know how a pod works, this blog post is the right place to start with.

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How We Optimized Read Performance: Readahead, Prefetch, and Cache

DZone

High-performance computing systems often use all-flash architectures and kernel-mode parallel file systems to satisfy performance demands. However, the increasing sizes of both data volumes and distributed system clusters raise significant cost challenges for all-flash storage and vast operational challenges for kernel clients. JuiceFS is a cloud-native distributed file system that operates entirely in user space.

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Reader Q&A: What’s the best way to pass an istream parameter?

Sutter's Mill

Here’s a super simple question: “How do I write a parameter that accepts any non- const std::istream argument? I just want an istream I can read from.” (This question isn’t limited to streams, but includes any similar type you have to modify/traverse to use.) Hopefully the answer will be super simple, too! So, before reading further: What would be your answer?

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Confusion Matrix vs. ROC Curve: When To Use Which for Model Evaluation

DZone

Model performance has to be evaluated in machine learning and data science in order to come up with a model that is reliable, accurate, and efficient in making any kind of prediction. Some common tools for this are the Confusion Matrix and the ROC Curve. Both have different purposes and knowing exactly when to use them is critical in robust model evaluation.