Automatic Resource Provisioning via Work-Breakdown Structures
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Solution Overview
Problem
Cloud computing systems face complexity and overhead in managing and tracking resources allocated to software offerings due to the lack of a comprehensive view of dependencies between software components and hardware resources, leading to difficulties in tracking events and failures.
Innovation Solution
A system that creates a multidimensional model of a software offering based on its service definition and resource availability, using a work-breakdown structure to automatically provision resources without manual configuration, including service containers for computing, storage, and network resources, and enabling monitoring during deployment and execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual configuration of resources is used, then ease of operation is improved, but device complexity and management overhead increase
Solution Approach 1:
The system performs self-service by automatically provisioning resources based on service definitions and work-breakdown structures without requiring manual configuration. The resource provisioning system autonomously creates service containers, allocates resources, and configures dependencies based on predefined policies and service templates.
Solution Approach 2:
The system applies preliminary action by pre-defining service definitions, work-breakdown structures, and resource templates before actual provisioning occurs. This allows the complex resource allocation decisions to be made in advance, enabling automated execution during deployment without manual intervention.
2Device complexity
If automatic resource provisioning is implemented, then device complexity is reduced, but measurement precision and tracking capability worsen
Solution Approach 1:
The system implements feedback mechanisms through multidimensional modeling that continuously tracks service components, resources, and their dependencies. The model provides feedback about the provisioning state, enabling the system to monitor and verify that automatic provisioning meets the required service level agreements and policy requirements.
Solution Approach 2:
The system applies dimensionality change by introducing a multidimensional model that adds layers of abstraction and tracking dimensions. This model organizes information about services, resources, and dependencies across multiple dimensions (service level, resource level, dependency level), enabling comprehensive tracking without increasing operational complexity.
3Measurement precision
If comprehensive resource tracking is implemented, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system applies segmentation by dividing the comprehensive tracking task into separate dimensional layers. The multidimensional model segments tracking into service component tracking, resource tracking, and dependency tracking, making the complex monitoring function manageable and organized through structured abstraction.
Data Source
AI summary
The disclosed embodiments provide a system that facilitates the deployment and execution of a software offering. During operation, the system obtains a service definition of the software offering. Next, the system creates a work-breakdown structure based on a set of policies from the service definition. Finally, the system uses the work-breakdown structure to automatically provision a set of resources for use by the software offering without requiring manual configuration of the resources by a user.