Dynamic Service Level Agreement for Cloud Resource Allocation
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Solution Overview
Problem
Cloud computing systems face challenges in dynamically selecting an optimum service from secondary clouds while adhering to service level agreements, especially when actual usage levels deviate from planned levels, leading to inefficient resource allocation and additional costs.
Innovation Solution
A cloud computing system dynamically updates service level agreements based on actual usage levels, selecting services that satisfy the new agreements from both primary and secondary clouds, ensuring compliance with user preferences and constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed service level agreement is maintained, then service compliance is ensured, but resource allocation efficiency deteriorates when actual usage deviates from planned levels
Solution Approach 1:
The service level agreement is transformed from a fixed contract to a dynamic parameter that adjusts based on actual service usage levels. The system continuously monitors actual usage and recalibrates the service level agreement to match real-world conditions, enabling both compliance maintenance and resource optimization.
Solution Approach 2:
The system implements a feedback mechanism where actual service usage levels are continuously measured and fed back into the service level agreement determination process. This closed-loop control allows the system to automatically adjust service levels in response to usage patterns, resolving the contradiction between fixed compliance and flexible efficiency.
2Reliability
If service levels are increased to meet user requirements, then service quality improves, but costs increase
Solution Approach 1:
The system dynamically changes the service level parameters based on actual usage data and user requirements. By adjusting service level parameters in real-time rather than maintaining fixed high levels, the system delivers necessary service quality while avoiding unnecessary resource consumption and associated costs.
Solution Approach 2:
The system applies partial action by providing exactly the service level needed based on actual usage, rather than consistently providing excessive service capacity. This prevents waste of resources while ensuring user requirements are met during periods of high demand.
3Adaptability or versatility
If secondary clouds are used to provide services, then service availability increases, but service selection complexity increases
Solution Approach 1:
The system implements self-service by automatically selecting appropriate secondary cloud providers based on current service level agreements and usage patterns. This automated service selection process reduces complexity by eliminating manual intervention while maintaining high service availability through multiple cloud providers.
Solution Approach 2:
The system uses parameter changes in service level agreements to simplify service selection across multiple clouds. By dynamically adjusting service level parameters, the system automatically determines optimal cloud provider selection without requiring complex manual configuration or evaluation of multiple providers.
Data Source
AI summary
A method for dynamically updating a service level agreement, performed by a cloud computing server, includes storing a preference for service selection, acquiring an actual usage level of a first service provided to a user during a predetermined time period in accordance with a first service level agreement, determining a second service level agreement different from the first service level agreement based on the actual usage level acquired during the predetermined time period, and selecting a second service that satisfies the second service level agreement.