Leading through Complexity: Decision-Making Frameworks for Multi-Cloud Integration and Platform Scalability

Modern enterprises face increasing complexity when adopting multi-cloud technologies and managing distributed computing environments. Organizations struggle with inconsistent governance models, vendor lock-in risks, and integration challenges that hinder operational efficiency. This paper presents five structured decision-making frameworks that address these challenges: cloud-agnostic evaluation matrices for comparing provider capabilities across workload requirements, service compatibility, compliance standards, network performance, and cost metrics; Infrastructure-as-Code standards that ensure consistency and reduce security risks across diverse cloud environments; federated integration architectures using event-driven patterns to connect legacy systems with modern cloud services; comprehensive observability solutions that provide unified monitoring and automated incident response; and a PACE layering model that systematically prioritizes modernization efforts. Implementation of these frameworks across fintech, pharmaceutical, healthcare, retail, and manufacturing organizations resulted in 40% reduction in deployment inconsistencies, 60% faster incident resolution, and 25% improvement in cost optimization. The frameworks enable technology leaders to shift from isolated technology selection to coordinated ecosystem orchestration, achieving both operational excellence and business agility.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-09-08
DOI
https://doi.org/10.52783/jisem.v10i58s.12801
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Leading through Complexity: Decision-Making Frameworks for Multi-Cloud Integration and Platform Scalability

Bhargav Sai Pillati
Journal of Information Systems Engineering & Management
Big Data and Business Intelligence
article

Leading through Complexity: Decision-Making Frameworks for Multi-Cloud Integration and Platform Scalability

Bhargav Sai Pillati
article en

Abstract

Modern enterprises face increasing complexity when adopting multi-cloud technologies and managing distributed computing environments. Organizations struggle with inconsistent governance models, vendor lock-in risks, and integration challenges that hinder operational efficiency. This paper presents five structured decision-making frameworks that address these challenges: cloud-agnostic evaluation matrices for comparing provider capabilities across workload requirements, service compatibility, compliance standards, network performance, and cost metrics; Infrastructure-as-Code standards that ensure consistency and reduce security risks across diverse cloud environments; federated integration architectures using event-driven patterns to connect legacy systems with modern cloud services; comprehensive observability solutions that provide unified monitoring and automated incident response; and a PACE layering model that systematically prioritizes modernization efforts. Implementation of these frameworks across fintech, pharmaceutical, healthcare, retail, and manufacturing organizations resulted in 40% reduction in deployment inconsistencies, 60% faster incident resolution, and 25% improvement in cost optimization. The frameworks enable technology leaders to shift from isolated technology selection to coordinated ecosystem orchestration, achieving both operational excellence and business agility.

Journal of Information Systems Engineering & ManagementVol. 10(58s)
Openalex Percentile: Top 60%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.