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5 key areas for tech leaders to watch in 2020

O'Reilly

It’s the single most popular programming language on O’Reilly, and it accounts for 10% of all usage. Software architecture, infrastructure, and operations are each changing rapidly. Software architecture, infrastructure, and operations are each changing rapidly. In programming, Python is preeminent.

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Microservices vs. monolithic architecture: Understanding the difference

Dynatrace

“This means reinventing IT around a distributed cloud infrastructure, public cloud software stacks, agile and cloud-native app development and deployment, AI as the new user interface, and new, pervasive approaches to security and trust at scale.” This is usually a relational database management system.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly

As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. On the one hand we have the long tradition of data-centric programming; on the other hand, we face the needs of modern, large-scale business applications.

DevOps 137
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Quantum computing’s potential is still far off, but quantum supremacy shows we’re on the right track

O'Reilly

Most of what we do on our computers—fancy graphics, email, databases, building websites, data analysis, digital signal processing—can’t be done with quantum computing. I was introduced to programming in 1972, on computers that were incredibly small by modern standards—but they were still useful. Certainly not now, and possibly never.

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5 tips for architecting fast data applications

O'Reilly Software

Google was among the pioneers that created “web scale” architectures to analyze the massive data sets that resulted from “crawling” the web that gave birth to Apache Hadoop, MapReduce, and NoSQL databases. We usually relate SQL to querying tables in relational databases. Determine requirements first. Leverage your SQL knowledge.

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Amazon EC2 Cluster GPU Instances - All Things Distributed

All Things Distributed

We believe that making these GPU resources available for everyone to use at low cost will drive new innovation in the application of highly parallel programming models. These trade-offs have even impacted the way the lowest level building blocks in our computer architectures have been designed. General Purpose GPU programming.

AWS 136