Fault Tolerance API for Cloud Resource Placement
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Solution Overview
Problem
In cloud computing environments, customers lack visibility and control over resource placement, making it difficult to determine fault tolerance, which is crucial for ensuring service reliability and risk management.
Innovation Solution
A mechanism, including an API, is provided that allows customers to request and receive information about fault tolerance and risk scores for their deployments, enabling them to assess and adjust resource placement across different zones and fault boundaries, with the system automatically making changes to meet specified risk criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If resources are provided in cloud locations over which the customer does not have visibility or direct control, then the customer can access services through cloud computing, but the customer cannot determine the fault tolerance of the resources
Solution Approach 1:
The system implements feedback by providing customers with fault tolerance information through APIs. The resource provider environment determines fault tolerance data and returns it to the customer, enabling informed decision-making about resource placement and risk management.
Solution Approach 2:
An API serves as an intermediary between the customer and the resource provider environment. The customer submits requests through the API, and the system returns fault tolerance information, bridging the information gap without requiring direct control of physical resources.
2Ease of manufacture
If the customer has minimal ability to control how and where resources are provided, then the resource provider can manage cloud infrastructure, but the customer cannot adjust resource placement to meet fault tolerance requirements
Solution Approach 1:
The system segments control by separating infrastructure management (handled by the resource provider) from fault tolerance decision-making (enabled for the customer through APIs). Customers can request specific fault tolerance levels and resource distribution patterns without managing the underlying infrastructure.
Solution Approach 2:
The system enables dynamic resource placement adjustments by allowing customers to submit requests through APIs to redistribute resources according to specified fault tolerance criteria. The system can automatically make changes to meet risk criteria while maintaining infrastructure management efficiency.
3Reliability
If the system provides detailed fault tolerance information and enables customer control over resource placement, then the customer can improve fault tolerance, but the system complexity increases
Solution Approach 1:
The API serves multiple functions: it accepts customer requests for fault tolerance information, processes resource redistribution requests, and returns updated fault tolerance data. This multi-functional approach reduces overall system complexity by consolidating operations through a single interface.
Solution Approach 2:
The system enables self-service by allowing customers to independently assess and adjust their own resource placements based on fault tolerance criteria. The automated processing of requests and redistribution of resources reduces the need for complex manual management interfaces.
Data Source
AI summary
A customer having a deployment of resources in a resource provider environment can utilize a mechanism such as an application programming interface (API) to obtain fault, risk, and/or distribution information for the deployment. A risk score can be generated, by the customer or a component of the resource provider environment, that gives the customer a measure of the risk of the current deployment, whereby the customer can request one or more changes to the customer deployment. In some embodiments the customer can provide one or more risk criteria, such as a maximum risk score or minimum fault tolerance, that the resource provider environment can attempt to satisfy over the duration of the customer deployment, automatically making adjustments to the deployment as appropriate. The risk score can include information about the customer workload as well as the physical deployment in order to provide more accurate data.