Cloud Resource Provisioning Automation
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Solution Overview
Problem
Traditional provisioning of private cloud resources is manual and time-consuming, especially for backing services like databases and message queues, which hampers efficient access and management of resources.
Innovation Solution
A computer-implemented method and system for on-premise provisioning of private cloud resources, which includes determining demand for hardware and software resources, initiating a workflow for resource retrieval, assessing availability, and providing instructions for provisioning service instances based on demand.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual provisioning is used for private cloud resources, then resource allocation can be carefully planned and optimized, but the provisioning process becomes time-consuming and labor-intensive
Solution Approach 1:
The system performs preliminary actions by automatically determining resource demand, checking availability, and preparing provisioning workflows before actual service deployment is needed. This advance preparation maintains optimization quality while reducing actual provisioning time when services are requested.
Solution Approach 2:
The provisioning system performs self-service by automatically determining its own resource demand, checking availability, and executing provisioning workflows without requiring manual intervention. This automation maintains careful resource allocation while eliminating the time-consuming manual setup process.
2Adaptability or versatility
If manual setup is used for backing services, then necessary adjustments can be made for small-scale private cloud deployment, but deployment and configuration require additional manual tasks
Solution Approach 1:
The system automates the deployment process by self-determining resource requirements, checking availability, and configuring services automatically. This maintains the adaptability needed for small-scale private cloud deployments while eliminating the manual configuration tasks that increase deployment complexity.
Solution Approach 2:
The system uses parameter changes to adapt provisioning workflows based on specific private cloud requirements. By dynamically adjusting resource allocation parameters and configuration settings, the system maintains deployment flexibility while automating the process to reduce complexity.
3Quantity of substance
If more hardware is added to provide storage capacity, then data storage needs can be met, but resource capacity remains limited in private cloud environments
Solution Approach 1:
The provisioning system provides multi-functionality by automatically managing hardware resources for multiple purposes including storage capacity expansion, compute resource allocation, and service deployment. This universal approach meets various storage needs while centralizing hardware management to reduce complexity.
Solution Approach 2:
The system performs self-service by automatically determining hardware resource requirements, checking availability, and provisioning services without manual intervention. This automation allows storage capacity to be expanded through additional hardware while the system自行 manages the complexity of hardware integration and configuration.
Data Source
AI summary
Methods, systems, and computer-readable storage media for determining a demand for private cloud resources including hardware resources and software resources, initiating a workflow for retrieving the private cloud resources, determining an availability of the private cloud resources, providing an instruction to provision service instances according to the demand for the private cloud resources, and providing an access to the service instances using the private cloud resources.