Cloud Cost Analysis Using Optimal Utilization Bands

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Solution Overview

Problem

Existing cloud cost optimization tools lack comprehensive insights into where costs are accruing and fail to provide actionable recommendations for optimizing cloud spend, often focusing on isolated resource analysis and neglecting systemic impacts, leading to either overload of anomalies or lack of meaningful insights for budget planning.

Innovation Solution

A method and system that utilize a sliding window approach to analyze cloud resource utilization metrics, calculate an optimal band using Root Mean Square Deviation (RMSD), and generate recommendations for converting resources to long-term or short-term reserve instance pricing models based on predefined thresholds.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If existing cloud cost optimization tools provide statistical analysis and dashboards, then cost visibility is improved, but actionable insights and comprehensive optimization recommendations are lacking

Engineering Contradiction:

Improvecost visibilityVSAvoidactionable insights

Core Design Contradiction:

Loss of informationVSMeasurement precision

Solution Approach 1:

The system implements feedback by continuously monitoring cloud resource usage patterns and comparing them against optimal pricing model thresholds. The sliding window approach provides ongoing feedback on utilization trends, enabling the system to generate actionable recommendations that evolve with changing usage patterns rather than providing static statistical snapshots.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent introduces an intermediary analysis layer that bridges raw cost data and actionable insights. The sliding window calculation and threshold-based classification system act as intermediaries that transform voluminous utilization data into prioritized optimization recommendations, preventing information overload while maintaining comprehensive analysis.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Difficulty of detecting and measuring

If sophisticated tools analyze resources in isolation, then individual resource anomalies are detected, but systemic impact and prioritization insights are lost

Engineering Contradiction:

Improveanomaly detectionVSAvoidsystemic impact

Core Design Contradiction:

Difficulty of detecting and measuringVSLoss of information

Solution Approach 1:

The patent merges individual resource analysis with systemic evaluation by applying the sliding window approach across multiple resources and time periods. This combination enables the system to detect both individual anomalies and broader utilization patterns, providing prioritized recommendations that consider both isolated issues and systemic optimization opportunities.

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The analysis system serves multiple functions simultaneously: it detects individual resource anomalies, identifies systemic utilization patterns, prioritizes optimization opportunities, and provides actionable recommendations. This multi-functional approach eliminates the need for separate analysis tools and prevents information loss across different analysis dimensions.

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Loss of energy

If existing solutions focus on identifying spend leakages, then cost anomalies are detected, but prioritization and budget planning guidance are insufficient

Engineering Contradiction:

Improvespend leakage identificationVSAvoidprioritization guidance

Core Design Contradiction:

Loss of energyVSEase of operation

Solution Approach 1:

The system changes the parameter of analysis from static cost identification to dynamic utilization pattern classification. By applying sliding window calculations and comparing against predefined thresholds, the system transforms leakage detection into a prioritized recommendation system that guides budget planning and optimization actions based on current utilization trends rather than historical anomalies alone.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20260065191A1Method and system to optimize cloud cost by analyzing pricing models

Publication Date: 2026.03.05 TATA CONSULTANCY SERVICES LTD

AI summary

Existing tools provide statistical analysis but often lack comprehensive insights into where costs are accruing and how they can be optimized. The present method obtains optimal band by sorting set of datapoints in ascending order. Sliding window approach is applied on sorted set of datapoints for selected window size, wherein lower band and upper band is created. Minimum width is created by finding difference between lower band and upper band. New lower band and new upper band are obtained, and width is computed by finding difference between new lower band and new upper band. Width and minimum width are compared, and width is saved as optimal band. Total outlier factor is calculated to determine set of datapoints outside optimal band and to assess proximity of set of datapoints to optimal band. One or more recommendations for optimizing cloud cost are generated based on obtained optimal band and total outlier factor.