Cloud Budget Allocation Using Hierarchical Parameter Scoring
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Solution Overview
Problem
Cloud budget allocation is challenging due to unpredictable resource demand, complex pricing structures, varying project requirements, and lack of expertise, leading to suboptimal resource utilization and cost management.
Innovation Solution
A multi-dimensional, multi-layered approach for cloud budget allocation involving parameter scoring, interdependency analysis, and expert input to derive optimized budget values through a system that considers scalability, availability, compliance, performance, and historical cost data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cloud budget allocation is based on simple estimation, then the budget creation process is fast and simple, but the accuracy of budget allocation is poor and actual spending exceeds budget
Solution Approach 1:
The budget allocation process is segmented into multiple hierarchical levels: application level, project level, and environment level. Each level has its own parameters and weightages, allowing complex budget allocation to be broken down into manageable segments that can be calculated and optimized independently while maintaining overall accuracy.
Solution Approach 2:
The patent introduces a multi-dimensional approach by considering multiple parameters (infrastructure, performance, storage, etc.) across multiple levels (application, project, environment). This transforms the simple 1D estimation into a multi-dimensional calculation that captures the complexity of cloud resource allocation while providing accurate budget predictions.
2Adaptability or versatility
If cloud budget allocation considers multiple projects and environments, then the allocation becomes more comprehensive, but the complexity of tracking and managing resources increases
Solution Approach 1:
The system segments the cloud ecosystem into distinct hierarchical levels (applications, projects, environments) with clear boundaries. Each segment has its own parameter set and budget calculation logic, making it easier to track and manage resources at each level while maintaining comprehensive coverage across the entire system.
Solution Approach 2:
By introducing hierarchical dimensions (application > project > environment), the system organizes complex multi-project and multi-environment allocations into structured layers. This dimensional organization allows comprehensive resource tracking while simplifying management through hierarchical aggregation and decomposition.
3Measurement precision
If cloud budget allocation uses detailed parameter analysis, then the budget accuracy improves, but the time and resources required for budget creation increase
Solution Approach 1:
The detailed parameter analysis is segmented across hierarchical levels, with each level contributing a portion of the total calculation. This allows comprehensive analysis to be performed in parallel at different levels rather than sequentially, reducing overall budget creation time while maintaining high accuracy through multi-level parameter consideration.
Solution Approach 2:
The patent transforms the time-consuming single-level detailed analysis into a multi-level dimensional approach where parameters are analyzed at application, project, and environment levels simultaneously. This dimensional distribution of analysis reduces the time burden at each individual level while achieving superior overall accuracy through the aggregation of multi-dimensional data.
Data Source
AI summary
The disclosure relates to a method and system for optimizing budget allocation for an application. The method includes, for a project of one or more projects associated with the application, and for an environment of one or more environments, receiving a parameter score level corresponding to a parameter, based on relevance of the parameter to the environment, wherein the parameter score level corresponds to a range of parameter score values. Further, for the project and for the environment, a mean environment budget value is derived based on the range of parameter score values corresponding to the set of parameters, and determining a project budget value based on summation of the mean environment budget value and an associated environment weightage corresponding to the one or more environments. The method further includes determining an application budget value based on summation of the project budget values.