Cloud Template Approval via Chargeback Mapping
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Solution Overview
Problem
In private cloud systems, administrators often manually create cloud templates without considering chargeback package details, leading to potential misallocation of resources and inefficiencies, as they lack knowledge of departmental chargeback packages, resulting in inappropriate resource allocation to departments.
Innovation Solution
An automated method for cloud template approval that maps user requests to chargeback packages, determining if the requested resources are within the user's allocated limits, and automatically approving or denying the template based on these criteria, using modules like Server-Chargeback Mapper and Template Qualifier to ensure accurate resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If administrators manually create cloud templates without considering chargeback package details, then the process is simple and quick, but resource allocation accuracy deteriorates leading to misallocation
Solution Approach 1:
The system automatically maps user requests to chargeback packages and determines allocation accuracy without administrator intervention. The automated resource allocation system evaluates requests against chargeback package details, eliminating the need for administrators to manually consider chargeback details while maintaining high allocation accuracy.
Solution Approach 2:
The manual administrative process is replaced with an automated computational system that uses algorithms to map requests to chargeback packages and determine allocation accuracy. This substitution of mechanical human decision-making with an automated system resolves the contradiction by providing both speed and precision.
2Manufacturing precision
If administrators manually create templates with knowledge of chargeback packages, then resource allocation accuracy improves, but the process complexity and time consumption increase
Solution Approach 1:
The system performs automatic mapping of user requests to chargeback packages and automatic determination of allocation accuracy without requiring administrator knowledge or manual processes. This self-service approach maintains high allocation accuracy while eliminating process complexity for administrators.
Solution Approach 2:
An automated intermediary system is introduced between the user request and template creation processes. This intermediary automatically handles the complex mapping and evaluation tasks, providing accurate resource allocation decisions without exposing administrators to process complexity.
3Manufacturing precision
If administrators manually create templates with knowledge of chargeback packages, then resource allocation accuracy improves, but the time required for template creation increases
Solution Approach 1:
The manual administrative process is replaced with automated computational processing that instantly evaluates requests against chargeback packages. This substitution maintains high allocation accuracy while dramatically reducing template creation time from manual processes to automated instant decision-making.
Solution Approach 2:
The system automatically performs the time-consuming tasks of mapping requests to chargeback packages and determining allocation accuracy without administrator involvement. This self-service automation maintains precision while eliminating time loss associated with manual processes.
Data Source
AI summary
Systems, methods, and computer-readable and executable instructions are provided for automatic cloud template approval. Automatic cloud template approval can include mapping a request to a chargeback package of a user, the request being for cloud service including a plurality of cloud service components. The automatic cloud template approval can include determining if the request is within the chargeback package of the user based on each of the plurality of cloud service components and, in response to the request being within the chargeback package of the user, automatically approving a cloud template to allocate the cloud service requested by the user. After approval resources will be allocated based on the availability, else resource analysis will be done and allocation will be done appropriately.


