Overcoming 3 key challenges with multi-cloud cost optimization for retail

Retail and e-commerce businesses increasingly rely on multi-cloud environments for scalability and flexibility. However, this complexity often leads to significant cloud cost optimization challenges. For FinOps teams, understanding and mitigating these issues is crucial for maintaining profitability. 

This blog focuses on 3 critical challenges: 

We’ll explore practical solutions to each, demonstrating how artificial intelligence (AI) and automation can improve control over cloud costs. Effective management requires a clear understanding of spending patterns, the ability to anticipate and respond to demand fluctuations, and a strategic approach to managing multiple cloud services. The goal of this blog is to provide actionable insights that empower FinOps teams to take control of their cloud spend, ensuring that technology investments directly support business objectives.

Challenge 1: Fragmented visibility across multiple cloud platforms

A major obstacle is the lack of a unified view of cloud spend across different cloud providers. Data dispersed across Amazon Web Services (AWS), Microsoft Azure, and Google Cloud leads to inaccurate cost allocation, missed optimization opportunities, and increased budget risks. Attributing costs to specific business units becomes difficult, and identifying redundant resources can be nearly impossible.

The solution is to implement a FinOps platform that consolidates data from all cloud providers into a unified dashboard. This enables real-time visibility, accurate cost allocation, and actionable insights. Instead of manually compiling reports, teams can use customizable dashboards to track spending and identify areas for improvement.

Challenge 2: Predicting and managing fluctuating demand during peak retail events

Retail experiences can result in dramatic demand fluctuations, especially during peak season. Over-provisioning leads to wasted resources during slow periods, while under-provisioning causes performance issues during peaks. And accurately forecasting demand is difficult, given the unpredictable nature of consumer behavior.

The solution is to use AI-powered predictive analytics that analyze historical data and market trends to forecast demand and automate resource scaling. This allows for dynamic adjustments, ensuring optimal performance without excessive costs. Instead of reactive adjustments, proactive scaling based on accurate predictions ensures that resources align with actual needs.

Challenge 3: Managing the complexity of diverse cloud services and pricing models

Identifying cost optimization opportunities in a multi-cloud organization is a key challenge. Cloud providers offer a wide range of services and pricing models, each with its own intricacies. For example, understanding the nuances between Reserved Instances, Savings Plans, and Spot Instances, while managing various service configurations, can be overwhelming. 

The solution is to employ cost optimization tools that incorporate AI to analyze service usage patterns and automate optimization strategies. This includes recommendations for cost-effective commitment discounts, intelligent resource rightsizing, and automated scheduling. Rather than manually sifting through billing data, cost optimization tools highlight opportunities for savings.

The path to effective cloud cost optimization in retail and e-commerce

Effectively managing cloud costs in retail and e-commerce hinges on solving these core challenges. Fragmented visibility, unpredictable demand, and complex service landscapes all present significant obstacles that can be addressed with AI and automation. 

By implementing solutions that consolidate data, predict demand, and optimize costs, FinOps teams can achieve greater control over their cloud spend. Ternary’s unified multi-cloud FinOps platform offers the tools needed to navigate these complexities, providing retailers with a comprehensive approach to cloud cost optimization. It helps to ensure that your cloud investments directly support business goals.