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Kubernetes in the wild report 2023

Dynatrace

The report also reveals the leading programming languages practitioners use for application workloads. are the top 3 programming languages for Kubernetes application workloads. Kubernetes hosting decisions are guided by a set of parameters, including cost, ease of provisioning and scaling, data security, and regulatory compliance.

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The Need for Real-Time Device Tracking

ScaleOut Software

And it can maintain contextual information about every data source (like the medical history of a device wearer or the maintenance history of a refrigeration system) and keep it immediately at hand to enhance the analysis.

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Track Thousands of Assets in a Time of Crisis Using Real-Time Digital Twins

ScaleOut Software

An innovative new software approach called “real-time digital twins” running on a cloud-hosted, highly scalable, in-memory computing platform can help address this challenge. The computing system also has the ability to perform aggregate analytics in seconds on the continuously evolving data held in the twins.

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Track Thousands of Assets in a Time of Crisis Using Real-Time Digital Twins

ScaleOut Software

An innovative new software approach called “real-time digital twins” running on a cloud-hosted, highly scalable, in-memory computing platform can help address this challenge. The computing system also has the ability to perform aggregate analytics in seconds on the continuously evolving data held in the twins.

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Using Real-Time Digital Twins for Aggregate Analytics

ScaleOut Software

Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source.

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Using Real-Time Digital Twins for Aggregate Analytics

ScaleOut Software

Instead, most applications just sift through the telemetry for patterns that might indicate exceptional conditions and forward the bulk of incoming messages to a data lake for offline scrubbing with a big data tool such as Spark. Maintain State Information for Each Data Source.