Virtual Resource Selection Using Hybrid Cloud Management Engine
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Solution Overview
Problem
In cloud environments, tenants incur additional costs and resource usage due to the creation of new virtual resources without considering existing resources with available capacity, leading to inefficient resource allocation.
Innovation Solution
A hybrid cloud management engine with a tag manager and resource utilization collector identifies and utilizes existing virtual resources with available capacity to satisfy tenant requests, avoiding the creation of new resources by matching request properties with existing instances and selecting based on utilization thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If new virtual resources are created to satisfy tenant requests, then tenant needs are met, but additional costs and resource usage occur
Solution Approach 1:
The system performs preliminary actions by proactively identifying and preparing existing virtual resources that can satisfy future tenant requests. The resource identification module continuously monitors and tags existing resources, so when a tenant requests a resource, the system already has a list of suitable candidates ready for immediate allocation, avoiding the need to create new resources from scratch.
Solution Approach 2:
Existing virtual resources are made multi-functional by enabling them to serve multiple tenant requests simultaneously. The system tags resources with multiple attributes (performance level, availability, location) allowing a single resource to be allocated to different tenants based on their specific needs, maximizing resource utilization and reducing the need for dedicated resource creation.
2Productivity
If existing virtual resources with available capacity are reused, then resource allocation efficiency improves, but system complexity increases
Solution Approach 1:
The resource management system is segmented into distinct functional modules: a resource identification module that discovers existing resources, a tagging module that assigns attributes, an allocation module that matches requests to resources, and a utilization monitoring module that tracks usage. This segmentation allows each module to perform its specific function independently, making the overall complex system more manageable and maintainable.
Solution Approach 2:
The system introduces intermediary components including a tagging module that acts as a mediator between resource identification and allocation. This tagging module processes resource attributes and creates a standardized representation that the allocation module can use for matching, simplifying the interaction between complex components and reducing overall system complexity.
3Ease of manufacture
If virtual resources are created without considering existing capacity, then resource creation is simplified, but costs and power usage increase
Solution Approach 1:
The system implements feedback mechanisms where the utilization monitoring module continuously tracks the status of existing virtual resources and feeds this information back to the allocation module. This feedback loop ensures that when a tenant requests a resource, the system knows which existing resources have available capacity and can allocate them accordingly, preventing the creation of new resources and reducing energy consumption.
Solution Approach 2:
The system performs preliminary identification and tagging of existing virtual resources and their capacity status before tenant requests are processed. This preliminary action ensures that the allocation module has immediate access to information about available resources, enabling rapid decision-making without the need to create new resources and consume additional energy.
Data Source
AI summary
In some examples, a system associates, with a plurality of virtual resources deployed in a cloud environment, properties representative of characteristics of the virtual resources, the properties comprising a performance level of a virtual resource. The system receives a request to create a virtual resource in the cloud environment, and, in response to determining that properties of the virtual resource to be created for the request satisfy a criterion with respect to properties of a given virtual resource of the plurality of virtual resources, selects the given virtual resource as a candidate virtual resource for the request.


