Rackspace empowers midmarket businesses with AI-driven cloud transformation, secure multicloud operations, and FinOps excellence ISG Multi Public Cloud Services - Managed Services - Midmarket Rackspace Technology Named a Leader in Managed Services - Midmarket in 2025 ISG Provider Lens™ Multi Public Cloud Services Report SAN ANTONIO, Dec. 15, 2025 (GLOBE NEWSWIRE) -- Rackspace Technology® (NASDAQ: RXT), a leading end-to-end hybrid cloud and AI solutions company, today announced it has been positioned as a ...

Core Insights - Apptio, an IBM company, has launched next-generation FinOps solutions aimed at enhancing visibility and optimizing cloud costs in AI-driven environments, addressing the increasing pressure on IT leaders to manage rising costs effectively [2][3] - IDC projects that global enterprise investments in AI infrastructure will reach $571 billion by 2026, yet 55% of business leaders report lacking the necessary information to evaluate technology spending effectively [2][3] FinOps Solutions - The new FinOps solutions are designed to provide organizations with real-time visibility, financial accountability, and management of cloud costs, thereby maximizing business value and collaboration [2][3] - Cloudability Governance, integrated with HashiCorp Cloud Platform and Terraform, empowers FinOps teams by automating cost compliance monitoring and applying organizational policies within engineering workflows [5][6] Cloud Cost Management - Cloudability Governance helps teams proactively understand cloud cost implications, forecast, and comply with internal policies before deploying infrastructure, enhancing financial oversight [6][7] - Kubecost 3.0 represents a significant evolution in Kubernetes cost management, providing advanced capabilities for managing cloud costs and optimizing resource utilization [8][11] Integration and Features - The integration of Cloudability with HashiCorp Terraform allows engineers to gain visibility into infrastructure costs and optimization opportunities directly within their workflows, promoting informed decision-making [8][9] - New features include automated container right-sizing, advanced GPU monitoring, and enhanced node group sizing insights, aimed at identifying inefficiencies and optimizing costs across workloads [11]

Core Insights - The increasing workloads of generative AI are leading to higher cloud budgets, prompting IT leaders to rethink their cloud cost management strategies [3][6]. Group 1: Cloud Cost Management Strategies - CIOs are adopting a multi-faceted approach to manage cloud spending, which includes negotiating commitment-based contracts for better cost transparency and capacity guarantees [4]. - The deployment of cost management tools is becoming essential for IT leaders to track usage and optimize resources [4]. - Practices like FinOps are being increasingly utilized to analyze cloud spending [4]. Group 2: Resource Optimization - A significant strategy involves "right-sizing cloud environments" to align resource allocation with workload requirements and implementing autoscale strategies to adjust capacity based on demand [5]. - These measures are aimed at ensuring efficient consumption and aligning cloud spending with financial goals as AI adoption accelerates [5]. Group 3: Demand for Tailored Cloud Products - Enterprises are seeking more value from cloud products, moving beyond basic services to tailored solutions that meet specific business needs [6]. - Hyperscalers are responding by investing billions into their cloud and AI infrastructure [6]. - Regulatory requirements for data sovereignty are increasing the demand for specialized or hybrid cloud products [6]. Group 4: Generative AI Spending Trends - A survey indicates that 42% of firms expect to allocate over 30% of their cloud budget to generative AI within the next three years [7]. - Nine out of ten leaders anticipate that generative AI use cases will account for 10% of their cloud budget [7]. - IT buyers' spending on generative AI workloads is projected to quadruple by 2028 [7].

Core Insights - The rise of On-Demand technologies is reshaping business operations, but increasing costs, complexity, and governance gaps are jeopardizing returns [2][4][5] - Organizations are transitioning from capital-intensive IT investments to flexible, consumption-based models, with On-Demand tech expected to grow from 29% to 41% of IT budgets in the next year [3][4] - Despite the benefits of On-Demand technologies, many organizations struggle with cost management and achieving expected returns on investment [5][6] Cost and Complexity Challenges - 82% of executives report significant increases in costs associated with cloud, SaaS, and Gen AI, driven by inflation and digital infrastructure demands [6] - 76% of organizations exceeded their public cloud budgets by an average of 10%, with 68% overspending on Gen AI and 52% on SaaS [6] - Underutilized resources and decentralized procurement are major contributors to budget overruns [6] Governance and Management Issues - 60% of organizations utilize cloud cost management tools, but only 37% assess their effectiveness [7] - 76% of organizations have or plan to establish FinOps teams, yet most remain narrowly focused and operational [7] - Only 2% of organizations with a dedicated FinOps function cover cloud, SaaS, and Gen AI holistically [7] Sustainability Considerations - 53% of organizations acknowledge that suboptimal usage of On-Demand tech leads to excessive energy consumption and increased carbon emissions [8] - Only 36% have a strategy for integrating sustainability into FinOps, despite the potential for cost reduction and carbon footprint minimization [8] Research Methodology - The Capgemini Research Institute conducted a survey of 1,000 executives from global organizations with annual revenues of at least $1 billion, focusing on On-Demand technologies across 12 sectors and 14 countries [9]