The engine room of SaaS: leveraging multi-cloud, aiops, and finops for scalable and profitable enterprise data platforms

Enterprise data platforms form the backbone of modern SaaS businesses, requiring scalability, reliability, and cost-efficiency. This article explores the synergistic integration of multi-cloud architectures, AI Operations, and Financial Operations to build and maintain profitable enterprise data platforms. Organizations achieve higher availability and better performance by strategically distributing workloads across multiple cloud providers while optimizing costs through comprehensive financial governance. AI-enhanced operations automate monitoring, incident response, and capacity planning, creating self-optimizing systems that balance technical performance with financial constraints. The article provides a framework for designing such platforms, including case studies from financial services and healthcare sectors demonstrating tangible benefits in scalability, cost reduction, and improved service delivery. A phased implementation roadmap guides organizations through foundation building, advanced capabilities, optimization, and transformation stages to create data platforms that serve as engines of business growth rather than cost centers.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-31
DOI
https://doi.org/10.5281/zenodo.17364489
Primary Topic
Software System Performance and Reliability
Type
article
Field-Weighted Citation Impact
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article

The engine room of SaaS: leveraging multi-cloud, aiops, and finops for scalable and profitable enterprise data platforms

Zenodo (CERN European Organization for Nuclear Research)
Software System Performance and Reliability
article

The engine room of SaaS: leveraging multi-cloud, aiops, and finops for scalable and profitable enterprise data platforms

article en

Abstract

Enterprise data platforms form the backbone of modern SaaS businesses, requiring scalability, reliability, and cost-efficiency. This article explores the synergistic integration of multi-cloud architectures, AI Operations, and Financial Operations to build and maintain profitable enterprise data platforms. Organizations achieve higher availability and better performance by strategically distributing workloads across multiple cloud providers while optimizing costs through comprehensive financial governance. AI-enhanced operations automate monitoring, incident response, and capacity planning, creating self-optimizing systems that balance technical performance with financial constraints. The article provides a framework for designing such platforms, including case studies from financial services and healthcare sectors demonstrating tangible benefits in scalability, cost reduction, and improved service delivery. A phased implementation roadmap guides organizations through foundation building, advanced capabilities, optimization, and transformation stages to create data platforms that serve as engines of business growth rather than cost centers.

Zenodo (CERN European Organization for Nuclear Research)
REL (United States) (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 42%
Software System Performance and Reliability
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The engine room of SaaS: leveraging multi-cloud, aiops, and finops for scalable and profitable enterprise data platforms · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS