Research of U.S. software developers exposes the gap between cost visibility and resource efficiency
TORONTO, Feb. 12, 2026 /PRNewswire/ — Kubex, a pioneer in automated resource optimization for Kubernetes, AI and Cloud, announces new research, Why AI infrastructure may be needlessly draining your budget, revealing a disconnect between executive demands for cost control and the manual management practices prevalent among Kubernetes platform owners. According to a survey of over 500 U.S. software developers managing modern cloud infrastructure, nearly half (47%) of teams still conduct weekly, bi-weekly or monthly manual reviews to optimize Kubernetes resources — an approach misaligned with the scale and complexity of modern cloud environments.
The operational gap comes at a steep price. While nearly 90% of organizations report increased executive oversight of Kubernetes costs, only 11% successfully keep waste below 10% of their budget. One in four organizations wastes more than 30% of their infrastructure spending due to slow or manual resource management and optimization practices.
“Kubernetes platform owners are caught between intensifying corporate pressure to optimize costs and overly manual processes that can’t keep pace with dynamic cloud environments,” said Andrew Hillier, co-founder and CTO at Kubex. “By relying on manual, periodic reviews, they run the risk of unnecessarily burning through budget due to oversized containers and suboptimal cloud instance choices. Manual methods are simply not good enough.”
The ROI data shows the urgency of modernizing management practices. Organizations that shift from manual reviews to automated, policy-driven optimization see measurable results: 44% achieve cost reductions of 10-20%, 26% realize savings of 20-30%, and 9% achieve savings of 30% or more.
The research also reveals how infrastructure fragmentation multiplies operational difficulties. Most organizations (65%) now operate hybrid infrastructure models, scaling Kubernetes across both on-premise and cloud environments. For platform owners managing these distributed systems, 51% cite multi-cluster or hybrid Kubernetes complexity as a key challenge, while top operational concerns include:
- 63% struggle with security, policy enforcement and compliance across environments
- 56% face storage and data consistency issues
- 46% resource allocation, cost optimization and efficiency
With AI now mainstream, 84% of respondents actively manage AI platforms and infrastructure, yet 44% admit to struggling with resource utilization and cost control for AI workloads. And even though the cost stakes have never been higher, 28% of organizations still operate with unlimited AI spending policies.
“The numbers in this survey are likely just the tip of the iceberg on AI spending practices and controls, as well as corporate attention to them,” said Chuck Tatham, CMO of Kubex. “We are in a stage where there is little questioning of the cost of AI as companies scramble to take advantage of the opportunities it brings. As with any tech adoption cycle, the cost concerns and the need for optimization will come.”
Looking ahead, 65% of organizations prioritize better observability and cost visibility for Kubernetes resources, while 53% plan to focus on automating workload optimization and rightsizing. Organizations that modernize their management practices by adopting automated optimization can capture millions in savings. At the same time, those continuing with manual approaches will lose ground as infrastructure complexity and costs escalate.
Kubex will be in attendance at KubeCon + CloudNativeCon Europe, the flagship conference from the Cloud Native Computing Foundation (CNCF), bringing together the cloud-native ecosystem — developers, maintainers, architects, and vendors — to share best practices, real-world case studies, and project roadmaps. Stop by Booth 589 March 23-26 to talk Kubernetes, GPUs, and AI workload optimization, and for prizes and giveaways.
The release of Kubex’s research follows the announcement of Kubex AI, which embeds Kubex’s analytics and optimization logic inside a conversational, AI-driven assistant. The full survey findings are available here.
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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SOURCE Kubex