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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. Recovery time of the latency p90.

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Full visibility into your serverless applications with AI-powered Azure Functions monitoring (GA)

Dynatrace

As companies strive to innovate and deliver faster, modern software architecture is evolving at near the speed of light. It allows for the breaking up of heavy monolithic architectures into multiple serverless “functions.” Simplify error analytics. Understand and optimize your architecture. So stay tuned!

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Full visibility into your serverless applications with AI-powered Azure Functions monitoring (GA)

Dynatrace

As companies strive to innovate and deliver faster, modern software architecture is evolving at near the speed of light. It allows for the breaking up of heavy monolithic architectures into multiple serverless “functions.” Simplify error analytics. Understand and optimize your architecture. So stay tuned!

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5 tips for architecting fast data applications

O'Reilly Software

Considerations for setting the architectural foundations for a fast data platform. 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. Back in the days of Web 1.0, At least once?