Workload Placement System Using Client Policy Analysis
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Solution Overview
Problem
Conventional workload placement services in cloud computing do not consider client-specific rules or technical characteristics of workloads, leading to inefficient infrastructure sizing and potential business disruptions.
Innovation Solution
An apparatus and method that determine the appropriate infrastructure and hosting provider for a client workload based on its technical characteristics and client policies, including location, data type, transaction volume, and criticality, while considering contractual agreements and costs, to ensure compliance with client policies and optimize resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional workload placement services select any available cloud service provider based on basic availability and price, then the selection process is simple and quick, but the infrastructure sizing becomes inefficient and may cause business disruptions
Solution Approach 1:
The patent transforms the workload placement process from a simple provider selection based on basic parameters (availability, price) to a comprehensive analysis that changes multiple parameters including technical characteristics (compute, storage, networking), client policies (compliance, security), and infrastructure requirements. This multi-parameter evaluation ensures both efficiency and reliability by matching workloads to providers that satisfy all constraints.
Solution Approach 2:
The system performs preliminary analysis of client policies, technical characteristics, and provider capabilities before making placement decisions. By pre-evaluating compliance requirements, security constraints, and infrastructure needs, the system avoids business disruptions by ensuring all requirements are met before workload deployment.
2Device complexity
If conventional workload placement services do not consider client-specific rules and technical characteristics, then the placement process is faster and less complex, but the infrastructure costs increase due to unnecessary provisioning
Solution Approach 1:
The patent introduces multiple evaluation parameters including technical characteristics (compute, storage, networking requirements), client policies (compliance, security), and provider capabilities. This comprehensive parameter set enables precise matching of workload requirements to provider resources, preventing over-provisioning and reducing infrastructure costs while maintaining necessary complexity for accurate decision-making.
3Ease of operation
If conventional workload placement services select hosting providers without considering technical characteristics and client policies, then the provider selection is simpler, but energy efficiency decreases due to suboptimal resource usage
Solution Approach 1:
The patent incorporates energy efficiency as a evaluation parameter alongside technical characteristics and client policies. By analyzing compute, storage, and networking requirements against provider capabilities, the system identifies placements that optimize resource utilization and energy consumption, transforming the simple selection process into an optimized decision-making framework.
Data Source
AI summary
According to examples, an apparatus includes a processor and a memory on which is stored machine readable instructions. The instructions may cause the processor to acquire technical characteristics of a client workload, access client policies, determine an infrastructure to implement the client workload based upon the acquired technical characteristics of the client workload, determine, based upon the determined server sizing and the accessed client policies, a recommended hosting provider that is to host the client workload, and output the determined server sizing and the recommended hosting provider.