Edge computing

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.

An open source edge and service proxy, designed for cloud-native applications

Enhance network application performance by pre-allocating essential resources

When you use Maximo Visual Inspection (MVI) for object detection, you might require additional categorization that is dependent on specific text on the object, such as recognizing brands or sub-brands. To help with this additional categorization, you can use MVI with an optical character recognition (OCR) solution if the confidence scores are low.

An edge computing environment distributes and manages workloads beyond the data center or cloud, in or near the locations where an enterprise conducts business.

A flexible open source solution for challenges associated with multi-cluster configuration management for edge, multi-cloud, and hybrid cloud use cases.

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 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.

In this article, we will discuss the steps to deploy the cloud-native infrastructure on the edge server.