Thousands of stores on one platform
Extending IT to remote locations can be a challenge for any enterprise. The store around the corner might be a good example.
Chain retailers increasingly use data to offer new services, improve in-store experiences, and keep operations running smoothly. But most stores aren’t equipped with large amounts of computing power. And for pharmacies that keep patient records, data security is a paramount concern.
For these kinds of enterprises, it makes sense to centralize the data storage while extending a uniform app environment out to remote locations. Edge for retail could mean anything from a store manager who uses AI tools for staff scheduling, a pharmacist with a tablet who can visit patients in their homes, or restaurant workers prepping mobile orders ahead of the lunch rush.
The challenges inherent in distributed IT deployments—whether they involve stores, restaurants, branch offices, transit stations, or other types of remote locations—are the kinds of problems that edge computing is built to solve.
Machine learning on the factory floor
The shop floor is pulsing with data, and Industrial Internet of Things (IIoT) sensors provide an unblinking view of factory conditions. That data, analyzed in real time, is leading to new levels of operational and business efficiency.
Achieving these benefits requires an underlying platform that can unify disparate data systems—especially because manufacturing systems traditionally have been isolated from each other.
Red Hat’s blueprint for edge and artificial intelligence and machine learning (AI/ML) in manufacturing calls for a unified ecosystem of Linux® container management with Red Hat® OpenShift®, application services, and storage. Software rollouts can be consistent, following CI/CD and GitOps practices. Analysts can take advantage of artificial intelligence and machine learning model training through a scalable service platform.
Edge computing is helping manufacturers solve problems faster by transforming operations to make plants even more productive.
Fast, advanced mobile networks
As 5G networks spread around the world, service providers are updating their networks to be more efficient and reduce latency, ushering in a new era of apps and improved services for customers.
Many changes are invisible to the mobile user, but enable providers to add capacity fast and reduce costs. Network functions virtualization (NFV) helps providers run network software in virtualized environments on general purpose hardware, rather than on expensive specialized components. In a similar shift, networks are virtualizing their radio access networks (a technology abbreviated as vRAN), which lowers costs and makes upgrades and scaling easier.
Additionally, providers are moving mobile workloads closer to the end user, through an architecture called mobile edge computing or multi-access edge computing (MEC).
Telcos around the globe have adopted unified edge platforms with Red Hat OpenShift to meet these challenges.