VMware and Red Hat top 5G Telco Cloud native platforms ranking

VMware and Red Hat come out on top in ABI Research’s 5G Telco Cloud Native Platforms competitive ranking.
Kazakhstan mobile networkMarket Leaders: VMware, Red Hat

Mainstream: Nokia, ZTE, Canonical, Huawei, Google, Ericsson, Wind River

Followers: AWS, Microsoft Azure

Cloud-native platforms will make use of Continuous Integration/Continuous Deployment (CI/CD) pipelines, service meshes, Kubernetes-based container technology, and other cloud-native tools to host new applications including Containerized Network Functions (CNFs) and the new 5G Service-Based Architecture (SBA) Core.

Platform providers include incumbent Network Equipment Vendors (NEVs) who have traditionally sold end-to-end network infrastructure solutions with their platforms included in the software stack, as well as cloud computing platform providers who have recently entered the telecom space through the introduction of LTE and 5G networks.

“SPs are looking to enable cloud-native 5G capabilities through the deployment of a horizontal platform that can span their entire network from the core to RAN to edge. Some of the key criteria that CSPs are looking for include the ability to build a multi-vendor network and avoid vendor lock-in,” says Kangrui Ling, Industry Analyst at ABI Research.

VMware and Red Hat are assessed as leaders in the market, with VMware coming out on top due to their strong multi-vendor Network Function (NF) partnership program supporting more than 220 NFs. Red Hat follows closely behind with their Red Hat OpenShift Container Platform and hybrid cloud and multi-cloud capabilities.

VMware and Red Hat are also top innovators, with VMware offering a variety of telco-specific features, including RAN Intelligent Controller (RIC), SD-WAN, and orchestrators. Red Hat offers auto-scaling of clusters and zero-touch provisioning through solutions such as Red Hat Advanced Cluster Management for Kubernetes, Red Hat Ansible Automation Platform, and Operator Lifecycle Manager (OLM).