The Patented AI-powered DataProphet Recommendation Engine is Revolutionizing Cloud Operations and Cost Management


Consider a world in which cloud operations are constantly optimized with the same level of intelligence and personalization as recommendation engines on social media and shopping websites. These recommendation engines have made our lives easier by recommending relevant content, products, or connections based on our preferences and behavior, allowing us to tailor our online experiences. ProphetStor’s DataProphet Recommendation Engine applies the same intelligent recommendation technology to cloud computing, transforming the way we manage cloud operations, providing businesses with unrivaled value, and addressing the growing need for efficient cloud cost management.

In this white paper, we will look at the challenges that businesses face when managing cloud operations and introduce ProphetStor’s revolutionary DataProphet Recommendation Engine. This engine is the foundation for, a cutting-edge solution that optimizes cloud operations and integrates seamlessly with a variety of market solutions. We will also discuss the significance of ProphetStor’s recently granted patent and how it enhances the DataProphet Recommendation Engine’s capabilities. Finally, we’ll look at how’s FinOps benefits enable efficient cloud cost management, addressing concerns raised in a recent Wall Street Journal article.

Part 1: Challenges in Cloud Operations Management

In the era of cloud computing, managing cloud operations has become increasingly complex. Businesses must ensure cost-effective, resilient operations while also requiring comprehensive stack visibility. As organizations transition to Cloud Native architectures and Kubernetes-based container environments, these challenges intensify.

1.1 East-West Dynamics and North-South Perspectives

Effective cloud IT infrastructure management necessitates a deep understanding of North-South Insight (IT infrastructure layers from application to server/cloud instance) and East-West Dynamics (how applications/microservices respond to workload dynamics). This knowledge is vital for enhancing performance, reducing latency, and ensuring cost-effectiveness.

1.2 Time-Based Analysis

To maximize the benefits of the cloud, businesses must have insight into their operations’ dynamics. Time-based analysis is essential for forecasting and planning for future changes in infrastructure, workloads, and resource requirements.

Part 2: DataProphet Recommendation Engine and Patented Technology

The DataProphet Recommendation Engine revolutionizes cloud operations management. It transforms the passive management style of waiting for problems to arise into a proactive resource orchestrator in the IT journey to Cloud Native, addressing both resilience and operational costs.

2.1 Comprehensive Platform

The DataProphet Recommendation Engine offers a solid foundation for collaboration with other market solutions. It provides North-South Insight, East-West Dynamics, and time-based analysis to organizations, enabling them to gain a comprehensive understanding of their past, present, and future operations.

2.2 Continuously Enhancing Cloud Operations

At the core of, the DataProphet Recommendation Engine analyzes collected metadata and delivers intelligent operation recommendations. In on-premises, hybrid cloud, or MultiCloud environments, this accelerates applications, enables planning, eliminates uncertainty, and reduces operating costs.

2.3 Patented Technology for Enhanced Capabilities

ProphetStor recently obtained US Patent No. 11579933 for a “Method for Establishing System Resource Prediction and Resource Management Model through Multi-layer Correlations.” This patented technology is essential for enhancing the DataProphet Recommendation Engine’s accuracy and minimizing the computation needed to produce results. It also underpins the operation metadata analysis that forms the core of DataProphet.’s patented multi-layer correlation technology and machine learning capabilities enable it to predict application workloads and build correlation models with resources, facilitating just-in-time resource orchestration and allocation. This approach ensures application resilience while reducing operating costs and meeting corporate/application KPIs in a computationally feasible manner.

Part 3: Managing Cloud Costs with's FinOps Advantages

A recent Wall Street Journal article highlighted technology executives’ growing concerns about cloud cost management. Controlling cloud spending has become a top priority as businesses increasingly invest in cloud computing. According to a Flexera Software LLC survey, the most significant cloud challenge for 82% of enterprises is managing cloud spending. According to International Data Corp., budget constraints and digital business complexities will drive 70% of enterprises to become more adept at managing cloud spending by 2024.’s FinOps benefits help businesses manage their cloud costs more effectively by providing AI-powered recommendations and insights. helps businesses avoid overspending on cloud services they don’t use and paying a premium for usage above their contracted limits by continuously optimizing cloud operations.

3.1 Collaboration with Monitoring Services collaborates with monitoring services such as Datadog, Sysdig, and Prometheus to transform visibility into continuous optimization in operations. With our multi-layer correlation and cascade causality analysis technology, the time-to-value is reduced from days to hours.

3.2 Implementing Service Mesh and Data Mesh Solutions enhances the capabilities of service mesh and data mesh solutions like Istio, Presto, and Kafka by providing comprehensive insight and predictions into application dynamics. It improves the main application’s performance by automatically scaling connected applications individually and eliminating bottlenecks.

3.3 Cloud Managed Service Providers (MSPs) Information enables MSPs to automatically provide value-added services and achieve customer obsession. By offering the necessary automation and intelligent workload placements, allows MSPs to optimize performance and cost without incurring additional technical resources.


Effective cloud operations management necessitates complete stack visibility and understanding of operation dynamics. The ProphetStor DataProphet Recommendation Engine is the core expertise that enables numerous essential services for smooth, cost-effective, and resilient operations in the next stage of the Cloud Native journey, as enhanced by the recently granted patent.

Businesses can use to not only continuously optimize their cloud operations by leveraging the power of AI-powered recommendations, but also manage their cloud costs efficiently, addressing the concerns raised in the Wall Street Journal article. Businesses can revolutionize their cloud operations and realize their full potential in the Cloud Native era by implementing this innovative and patented technology.


  1. ProphetStor Data Services, Inc. (2023, February 15). Solution Granted Patent for Application-Aware, Resilient, and Optimized IT Cloud Operations. Retrieved from
  2. Lin, B. (2023, March 3). Technology Chiefs Seek Help Wrangling Cloud Costs. The Wall Street Journal. Retrieved from
  3. Gartner, Inc. Gartner IT Glossary. Retrieved from
  4. CNCF Cloud Native Interactive Landscape. Cloud Native Computing Foundation. Retrieved from
  5. Flexera Software LLC. Flexera. Retrieved from
  6. International Data Corp. IDC. Retrieved from
  7. The FinOps Foundation. FinOps. Retrieved from
  8. Ricci, F., Rokach, L., Shapira, B., & Kanto, P. B. (Eds.). (2011). Recommender Systems Handbook. Springer.
  9. Schrage, M. (2022, April 27). The Recommender Revolution. MIT Technology Review. Retrieved from
  10. Schrage, M. (2020). Recommendation Engines. The MIT Press.
  11. Schrage, M. (2021, October 19). In Digital Transformation, Give KPIs a Leading Role. The Wall Street Journal. Retrieved from
  12. Schrage, M., Muttreja, V., & Kwan, A. (2022, March 8). How the Wrong KPIs Doom Digital Transformation. MIT Sloan Management Review. Retrieved from
  13. US Patent No. 11579933. (2023). Method for Establishing System Resource Prediction and Resource Management Model Through Multi-layer Correlations. US Patent Office. Granted December 2022 to ProphetStor.
  14. Groombridge, D. (2022, October 17). Gartner Top 10 Strategic Technology Trends for 2023. Gartner. Retrieved from
  15. Forecasting at Scale. Retrieved from
  16. Greykite: A Flexible, Intuitive, and Fast Forecasting Library. Retrieved from–a-flexible–intuitive–and-fast-forecasting-library
  17. Correlation-based Predictions for Kubernetes Resource Management. Retrieved from
  18. The Istio service mesh. Retrieved from
  19. What Is Data Mesh? Retrieved from
  20. Shahrad, M., et al. (2020). Serverless in the Wild: Characterizing and Optimizing the Serverless Workload at a Large Cloud Provider. In Proceedings of the 2020 USENIX Annual Technical Conference (USENIX ATC 20). USENIX Association, Boston, MA.
  21. Luo, S., et al. (2021). Characterizing Microservice Dependency and Performance: Alibaba Trace Analysis. In ACM Symposium on Cloud Computing (SoCC’ 21), November 1–4, 2021, Seattle, WA, USA. ACM, New York, NY, USA, 15 pages.