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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.

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Use Digital Twins for the Next Generation in Telematics

ScaleOut Software

Rapid advances in the telematics industry have dramatically boosted the efficiency of vehicle fleets and have found wide ranging applications from long haul transport to usage-based insurance. Real-Time Digital Twins Can Add Important New Capabilities to Telematics Systems and Eliminate Scalability Bottlenecks.

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How architecture evolves into strategy

O'Reilly Software

It's a given that we must design a system, including a local software architecture, that actually runs, that is "solid." I love this definition of containing entropy because it offers something to both the software-minded and the business-minded architect (which I hope are two categories this book will help to collapse).

Strategy 100
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Microservices vs. monolithic architecture: Understanding the difference

Dynatrace

Therefore, DevOps teams can better control application performance, so applications can start faster and run more efficiently. Which software architecture suits your solution and business best? Teams want efficiency. With microservices, you’ll be able to deploy a highly efficient, easy-to-scale platform.

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Improving The Performance Of Wix Websites (Case Study)

Smashing Magazine

This includes building websites, hosting websites, managing campaigns, SEO, analytics, CRM, and much more. In order to create change across our entire organization, we needed to get all the relevant employees, partners, and even customers up to speed about performance quickly and efficiently. Creating A Performance Culture.

Website 128
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Cloud Adoption in 2020

O'Reilly

These services are also designed to function as gateway drugs to cloud services: e.g., Microsoft integrates its on- and off-premises Excel client experience with its PowerBI cloud analytics service, as well as with its ecosystem of Azure-based advanced analytics and machine learning (ML) services. Take observability , for example.

Cloud 141
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5 tips for architecting fast data applications

O'Reilly Software

Here are five considerations every software architect and developer needs to take into account when setting the architectural foundations for a fast data platform. Determine requirements first. We discussed how fast data applications and microservices converge on the conceptual and executional levels.