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Artificial Intelligence in Cloud Computing

Scalegrid

This article delves into the specifics of how AI optimizes cloud efficiency, ensures scalability, and reinforces security, providing a glimpse at its transformative role without giving away extensive details. Predictive analytics, powered by AI, enhance business processes and optimize resource allocation according to workload demands.

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Modern observability is no longer optional on the path to digital transformation

Dynatrace

With increased scalability, agility, and flexibility, cloud computing enables organizations to improve supply chains, deliver higher customer satisfaction, and more. That’s why, in part, major cloud providers such as Amazon Web Services, Microsoft Azure, and Google Cloud Platform are discussing cloud optimization.

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Designing Instagram

High Scalability

Architecture. We have chosen this NoSQL based solution over relational databases as it provides the scalability to have hierarchies which go beyond two levels and extensibility due to the schema-less behavior of NoSQL data storage. Sending and receiving messages from other users. High Level Design. Streaming Data Model.

Design 334
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Why Use “Real-Time Digital Twins” for Streaming Analytics?

ScaleOut Software

And how are they different from streaming pipelines like Azure Stream Analytics and Apache Flink/Beam? What Problems Does Streaming Analytics Solve? To understand why we need real-time digital twins for streaming analytics, we first need to look at what problems are tackled by popular streaming platforms.

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What is container orchestration?

Dynatrace

Part of its popularity owes to its availability as a managed service through the major cloud providers, such as Amazon Elastic Kubernetes Service , Google Kubernetes Engine , and Microsoft Azure Kubernetes Service. Likewise, Kubernetes is both an enterprise platform and managed services with Red Hat OpenShift.

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Using Real-Time Digital Twins for Aggregate Analytics

ScaleOut Software

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time. The list goes on.

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Using Real-Time Digital Twins for Aggregate Analytics

ScaleOut Software

When analyzing telemetry from a large population of data sources, such as a fleet of rental cars or IoT devices in “smart cities” deployments, it’s difficult if not impossible for conventional streaming analytics platforms to track the behavior of each individual data source and derive actionable information in real time. The list goes on.