Jun 2026· Annals of the Academy of Romanian Scientists Series on Economy, Law and Sociology· Vol 9, pp. 36-41· 0 citations· 21 references
TL;DR
Key approaches include optimizing data locality to ensure that workloads are executed in proximity to their associated datasets, leveraging dedicated interconnect services to achieve predictable bandwidth and reduced egress fees, and applying techniques such as caching, compression, and deduplication to minimize data transfer volumes.
Abstract
Hybrid cloud infrastructures offer organizations the flexibility to integrate on-premises resources with public cloud services; however, this integration introduces substantial challenges related to data transfer costs. Charges associated with data egress, inter-region communication, and continuous data replication can escalate rapidly, particularly in multi-cloud scenarios where workloads and datasets are distributed across heterogeneous environments. As a result, unmanaged data movement has the potential to undermine the economic benefits typically associated with cloud adoption. This study investigates strategies for managing and optimizing data transfer costs in hybrid cloud ecosystems, addressing architectural, operational, and financial dimensions. Key approaches include optimizing data locality to ensure that workloads are executed in proximity to their associated datasets, leveraging dedicated interconnect services to achieve predictable bandwidth and reduced egress fees, and applying techniques such as caching, compression, and deduplication to minimize data transfer volumes. Furthermore, workload placement policies and FinOps practices—supported by automation and policy-as-code mechanisms—are identified as critical enablers for enforcing cost-efficient operations and maintaining financial governance. The findings highlight that proactive monitoring, combined with cost-aware architectural design, is essential to balancing performance requirements with economic sustainability. Organizations that embed cost optimization principles into the design and operation of hybrid cloud infrastructures are better positioned to achieve long-term efficiency, scalability, and financial resilience.
The key design principles of an EDP, including data distribution, workload optimization, auto-scaling, and cost analytics, and how these can be implemented across multiple cloud providers are discussed.
Nimal Perera· International Journal of Dat...· 0 citations
This work outlines AutoSLO, a latency-SLO-aware work-load management framework for multi-cluster cloud data ware-houses that includes a periodic Policy Tuner that proactively plans resources using workload fore-casts, an SLO-aware reactive Autoscaler that adjusts the active cluster set based on the observed workload, a...
A comprehensive review of Kubernetes scheduling strategies published between January 2023 and January 2026 is presented and a multi-dimensional taxonomy is established that categorizes scheduling approaches based on common objectives, modification methods, optimization methodologies, targeted workloads, evaluation meth...
Mohammed Alhakimi, R. Latip· De Computis· 0 citations
Using empirical benchmarks and advancements made in cloud computing technology and scheduling, this article investigates the architectural approaches, infrastructure optimization methods, and performance techniques that contribute to enabling high throughput and energy efficiency in transactional systems operating in r...
Dasaradhi Eddula· International journal of com...· 0 citations
Organizations operating regulated database workloads across two or more public clouds should prioritize federated identity management, policy-as-code security baselines, centralized telemetry, and automated audit-evidence generation before expanding provider-specific security tooling.
Sai Krishna Vadlamudi· American Journal of Technolo...· 0 citations
This work proposes an adaptive resource allocation framework that leverages Digital Twins for real-time system monitoring and integrates Large Language Models to support context-aware decision-making under multi-objective constraints, enabling intelligent workload orchestration across heterogeneous data center environm...
Pedro Henrique Sachete Garcia, A. F. Lorenzon, M. Luizelli et al.· SN Computer Science· 0 citations
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