Beyond FinOps: Cloud Cost Optimization Strategies Guide

Abstract

Organizations adopted public cloud services with intention to cut down on their on-premises spend and shift from a ‘CapEx’ to ‘OpEx’ model. However, post cloud adoption, they experienced cost overruns, leading them to explore options for optimization and reducing cloud spend. Typically, conversations around this revolved around a particular FinOps tool. However, from our perspective, cost optimization is not about a tool. It is a process and approach before and after implementation / moving to cloud. Typically, any organization approach starts their cloud journey by adopting infrastructure as a service (IAAS) cloud services, which mostly involved a lift and shift sort of migration from on-premises to cloud.

This paper examines how organizations can move beyond tool centric FinOps models to adopt a process and architecture led approach for sustainable cloud cost optimization.

Advance Modal Components
Move Beyond FinOps with Process Led Cost Optimization

Organizations cannot demand consistent 10-15% year-on-year savings from FinOps tools alone; It is just a source of governance and cost visibility.

Sustainable cost savings are achieved at the architecture and provisioning stages, not after workloads are deployed.

Significant cost savings can be achieved through re-evaluating cloud licensing and subscription models across platforms and vendors.

Kubernetes-native tools such as Kubercost, Karpenter, Kubegreen enable pod-level optimization, delivering meaningful and measurable cost efficiencies.

About the Author
Sakthivel Ramaiah
Group Practice Head-Platforms and Solutions, Tech Mahindra
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With over 25 years of experience across industries, specializes in IT infrastructure, applications, and cloud transformations. As VP/Global Head of Cloud Platforms, he drives competitive strategies for hybrid multi-cloud practice covering strategy, assessment, migration, Cloud Ops, FinOps, DevOps, and application modernization.

Amar Samarth
Principal Solution Architect, Tech Mahindra

With over 20 years of experience in building capabilities across various technologies in premises, private and public cloud domains. Currently responsible for partner management, automation, integration, for hybrid multi cloud environments while developing new value-added services using emerging technologies.

Prabhas Harlapur
Lead Solution Architect and Industrial Technical Specialist, Intel Corporation

Seasoned Solution Architect with deep expertise in Datacenter, Cloud, and AI technologies. He specializes in next-generation GenAI solutions using Intel Xeon and Gaudi platforms, covering the full lifecycle from inference services to fine-tuning and training. He is also focused on cloud resource optimization across that reduce total cost of ownership (TCO) and improve workload efficiency.

Moushumi Dash
Senior Solution Architect, Intel Corporation

Experienced Senior Solution Architect with expertise in Cloud Computing and Data Center AI solutions. Strong background in designing and architecting scalable, secure, and performance-optimized cloud , data center infrastructures and AI workloads across diverse industries. Expertise in driving technical sales, building relationships with key stakeholders, and collaborating with cross-functional teams to deliver tailored solutions.