Dynamic SLA Provisioning via Utility Functions
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Solution Overview
Problem
Current cloud computing environments lack dynamic and adaptive Service Level Agreement (SLA) provisioning, which fails to efficiently match customer service requirements with provider capabilities, leading to suboptimal service delivery and inflexible response to changing business needs.
Innovation Solution
A method and system for dynamic SLA provisioning that identifies customer service level criteria, determines computing environment characteristics, evaluates utility functions defining service level variables, and automatically generates an optimal SLA based on these factors, enabling real-time adjustments to meet evolving business demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static SLA provisioning is used, then SLA terms are simple to define, but the system cannot adapt to changing business needs and service requirements
Solution Approach 1:
The patent implements dynamic SLA provisioning by enabling automatic adjustment of SLA terms based on real-time service performance metrics and changing business requirements. The system continuously monitors service level compliance and dynamically modifies SLA parameters without manual intervention, transforming static agreements into adaptive contracts that evolve with business needs.
Solution Approach 2:
The system automatically modifies SLA parameters such as service level targets, penalty clauses, and performance thresholds based on monitored service quality metrics. By changing these parameters dynamically according to actual service performance and business conditions, the system maintains optimal SLA terms while reducing manual complexity.
2Productivity
If manual SLA negotiation is used, then SLA terms can be customized for each customer, but the process is time-consuming and inefficient
Solution Approach 1:
The system enables self-service SLA provisioning by automatically generating and adjusting SLA terms based on pre-defined templates, service performance data, and business rules. The automated system performs negotiation tasks independently, eliminating the need for manual back-and-forth between providers and customers, thereby significantly reducing time consumption.
Solution Approach 2:
The system pre-configures SLA templates and performance thresholds before service deployment. By preparing these frameworks in advance, the system can rapidly generate customized SLA agreements without time-consuming negotiations during the onboarding process, achieving both customization and efficiency.
3Manufacturing precision
If SLA terms are highly customized for each customer, then service levels can be precisely matched to individual needs, but the complexity of managing diverse SLA provisions increases
Solution Approach 1:
The system applies local quality customization by allowing different SLA parameters and performance thresholds for different customers or service types while maintaining a unified management framework. Each customer receives tailored SLA terms appropriate to their specific needs, but the overall system architecture remains standardized and manageable through centralized automation.
Solution Approach 2:
The system introduces an intermediary layer of automated rule engines and performance monitoring tools that mediate between customized customer requirements and standardized service delivery. This intermediary layer translates diverse customer needs into manageable SLA provisions through automated interpretation and enforcement, reducing management complexity.
4Adaptability or versatility
If real-time SLA adjustment is implemented, then the system responds to changing conditions dynamically, but the system complexity and computational requirements increase
Solution Approach 1:
The system implements real-time SLA adjustment through continuous feedback loops that monitor service performance metrics and automatically trigger SLA term modifications when predefined conditions are met. The feedback mechanism operates autonomously based on objective data, enabling dynamic adaptation without requiring complex decision-making algorithms or excessive computational resources.
Data Source
AI summary
According to one aspect of the present disclosure a method and technique for dynamic system level agreement provisioning is disclosed. The method includes: identifying, by a data processing system of a computing environment service provider, service level criteria for a customer of computing services; determining characteristics of the computing environment; identifying a time period for providing the computing services; evaluating one or more utility functions defining service level variables; and automatically determining, by the data processing system, a service level agreement (SLA) provision for the customer based on the one or more utility functions.