Three Years. One Verdict: Leader and Outperformer.
Get the GigaOm Radar for Full-Stack Edge Deployments and see why Scale Computing™ is a Leader and Outperformer.
Scale Computing has been recognized again in the GigaOm Radar for Full-Stack Edge Deployments—this time as a Leader for the third year in a row and Outperformer for two years.
The report evaluates vendors across the capabilities that differentiate solutions (Key Features) and the business requirements that shape real-world value (Business Criteria).
This year’s Outperformer position reflects the strength of our expanded portfolio, bringing together secure edge infrastructure with edge networking and services capabilities, so organizations can run, protect, and manage distributed environments with less operational friction.
This Radar report offers an analyst view of what matters most: how platforms perform, how they scale, and how manageable they are in real deployments.
Use it to compare approaches, pressure-test requirements, and align stakeholders on a platform that can deliver consistently across hundreds (or thousands) of locations.
The report highlights why Scale Computing is a strong fit for organizations of many sizes and deployment models, and:
How SC//HyperCore™ virtualization suite supports efficient full-stack edge deployments with built-in resilience and simplified operations.
How SC//Fleet Manager™ edge orchestration software helps teams monitor and manage at scale, supporting centralized visibility, upgrades, and orchestration across large numbers of clusters.
How SC//Reliant™ Edge Computing as a Service supports the deployment and operation of applications across large, distributed environments.
How the combined Scale Computing portfolio strengthens full-stack edge outcomes with secure networking visibility and managed services for distributed operations.
Full-stack edge deployments are cloud-managed and cloud-connected hyperconverged solutions that provide all the tools needed to run applications at any customer's preferred location for local data collection and processing. That matters more than ever as organizations add computer vision, analytics, and other AI-powered workloads that benefit from low latency and local resiliency.
These solutions offer a cloud-like experience at edge locations, which would otherwise be challenging to manage at scale using traditional IT practices.