Technology analyst firm recognized Kubex as a Leader and Outperformer in Kubernetes Resource Management and a Leader and Fast Mover in Cloud Resource Optimization

TORONTO, March 24, 2026 /PRNewswire/ -- Kubex, a pioneer in automated resource optimization for Kubernetes, AI and Cloud, has been named a Leader in two GigaOm Radar reports: Kubernetes Resource Management and Cloud Resource Optimization. In both reports, GigaOm Radar positions Kubex in the Innovation/Platform Play quadrant, recognized as an Outperformer in the Kubernetes report and a Fast Mover in the Cloud Resource Optimization report.

GigaOm's annual Radar reports evaluate leading technology vendors across a defined set of key features, emerging capabilities and business criteria. The Kubernetes Resource Management report evaluated solutions across criteria such as automatic resource optimization, predictive scaling, dynamic resource recommendations and governed optimization aligned with policy guardrails and enterprise controls. The Cloud Resource Optimization report evaluated vendors on Kubernetes resource management depth, AI workload-aware GPU optimization, objective-based optimization and integration with DevOps and ITSM tooling.

"Being recognized as a Leader in both of these reports reflects what our customers already experience: precise, automated resource optimization across cloud, Kubernetes and AI workloads," said Andrew Hillier, co-founder and CTO at Kubex. "Organizations don't struggle with cost visibility any longer; it's the actual optimization that enterprises want to achieve. With reliable, safe automation, you can save massive amounts and eliminate manual optimization hassles."

Across both reports, GigaOm recognized Kubex for its governed automation framework and policy guardrails that enable safe, policy-aligned optimization within enterprise controls. The reports also highlighted Kubex's predictive scaling engine, which proactively sets resource configurations based on historical usage trends rather than reacting to spikes after they occur.

The Cloud Resource Optimization report specifically highlighted Kubex's AI workload-aware GPU optimization, including its patent-pending GPU Map and MIG-aware analysis, to reduce overprovisioning and maximize ROI on AI infrastructure. Kubex's Outperformer designation in the Kubernetes report was driven in part by its accelerated innovation roadmap, including the launch of the Kubex AI Agent and support for GPU optimization and the Model Context Protocol (MCP).

"The GigaOm evaluations validate what we hear from platform owners every day," said Chuck Tatham, CMO of Kubex. "The pressure to control costs is real, but so is the pressure not to break production environments. Our approach, which is autonomous, policy-governed and enterprise proven, gives teams the confidence to optimize at scale."

The dual recognition comes as enterprise demand for intelligent resource optimization accelerates. According to Kubex's research released in February, nearly half of Kubernetes platform teams still rely on manual review processes to manage cloud resources. A shift to automated, policy-driven optimization can deliver cost reductions of 10% to 30% or more.

For more information about Kubex, please visit kubex.ai.

About Kubex
Kubex (formerly Densify) develops technology that automates resource optimization across Kubernetes, AI infrastructure, and cloud environments. By combining deep analytics, verticalized AI, and automation, Kubex helps enterprises reduce manual effort and waste, improve performance, and significantly lower infrastructure costs.

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