# Cloud PricingOps: A Decision Support Framework to Explore Pricing Policies of Cloud Services
## 1 Introduction  
Cloud financial management, often referred to as Cloud FinOps (Financial Operations), is a strategic approach to managing and optimizing the financial aspects of cloud computing [1]. It is a cultural practice that is essential for organizations to ensure the efficient use of cloud resources, minimize idle resources, and align spending with business objectives. It enables organizations to derive maximum business value by helping engineering, finance, technology, and business teams collaborate on data-driven decisions [1]. The FinOps framework utilizes a set of domains and capabilities to ensure financial accountability in cloud environments. The domains of the FinOps framework describe the fundamental business outcomes organizations should achieve from the FinOps practice. In essence, practicing FinOps will allow organizations to understand their cloud usage and costs, quantify their business value, optimize both usage and rates paid, and manage effective practices [1]. Capabilities refer to the functional activities that can be performed within each domain, such as forecasting, budgeting, planning, and estimating [2]. A key concept in FinOps is leveraging financial aspects to empower engineering teams tomake data-driven decisions. FinOps emphasizes collaboration between finance, DevOps, and engineering teams to manage cloud spending effectively. Specifically, engineering teams are given detailed information about cloud resource costs. This visibility helps them understand how their technical decisions impact the overall budget. With real-time or frequent cost insights, teams can optimize their usage of cloud resources, scaling up or down based on demand, thus reducing waste and ensuring that resources are being used efficiently. Moreover, engineers are involved in forecasting cloud costs, ensuring that they can predict spending based on upcoming projects or scale needs, which is crucial for long-term planning [1]. The global cloud FinOps market is projected to grow from USD 13.5 billion in 2024 to USD 23.3 billion by 2029, with a compound annual growth rate (CAGR) of 11.4% over the forecast period [3]. In the coming years, several trends are expected to shape this market's growth. A key trend will be the increasing use of artificial intelligence (AI) and machine learning (ML) for analytics and cost forecasting, which will enhance the ability to predict cloud expenditures, identify potential cost-saving opportunities, and allocate resources more effectively based on real-time data and trends [3]. Major cloud providers are implementing mechanisms to manage cloud finance. They offer a suite of FinOps tools that solely focus on the services of each individual provider [4; 5]. However, there are third-party FinOps platforms that offer cloud financial management across multiple cloud providers [6; 7]. Different providers implement varying pricing policies for their products, and these policies evolve over time. As a result, many initiatives have been launched to examine the temporal evolution of prices for different cloud products, employing diverse decision-making methods and datasets. Towards this direction, we introduce a decision support framework called CloudPricingOps. This framework is designed to enhance decision-making by optimizing cloud costs through a comprehensive analysis of cloud pricing policies. CloudPricingOps includes three capabilities--price policy analysis, cost comparison, and price prediction--all aligned with FinOps culture. It enables decision-makers to make data-driven choices by leveraging well-established methodologies and a reusable dataset. Additionally, it empowers users to manage cloud costs more effectively, ensuring better cost control and strategic financial planning. The rest of this paper is structured as follows: Section 2 covers related works, followed by the introduction of the CloudPricingOps framework in Section 3.