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Use the edge of the Internet for data processing and analytics
Edge computing is a distributed computing framework that brings enterprise applications closer to data sources, such as internet of things (IoT) devices, or closer to local edge servers. With edge computing, you place workloads as close to where the data is being created and where the actions are being taken.
An edge computing environment distributes and manages workloads beyond the data center or cloud, in or near the locations where an enterprise conducts business.
In this article, we will describe how we implemented the network layer of the edge computing architecture for the workplace safety use case we introduced in Part 2.
In this series, we examine what edge computing is, explore how edge computing can be used to create new opportunities, and discuss how edge computing can be implemented.
In this article, we will describe how we implemented a workplace safety use case involving the application and device layer of the edge computing architecture.
In this article, we explain what edge computing is, describe relevant use cases for the telecommunications and media industry while describing the benefits for other industries, and present what an end-to-end architecture that incorporates edge computing can look like.
Fine-grained autoscaling for event driven Kubernetes workloads. KEDA serves as a Kubernetes Metrics Server and allows users to define autoscaling rules using a dedicated Kubernetes custom resource definition.
A flexible open source solution for challenges associated with multi-cluster configuration management for edge, multi-cloud, and hybrid cloud use cases.
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