Hybrid Cloud Placement Optimizing Elasticity and Security
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Solution Overview
Problem
Businesses face challenges in achieving elasticity and cost-effectiveness in cloud computing by balancing the need for control and security in on-premise infrastructure with the agility and cost of public cloud services, as existing solutions primarily focus on individual VM placement rather than the entire application structure.
Innovation Solution
A hybrid cloud placement method that determines whether an application should be placed on a private or public cloud based on its attributes, considering factors like security, cost, and communication overhead, using a placement system that splits the application across both environments to optimize resource utilization and minimize public cloud costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If workloads are deployed to public cloud service, then elasticity and agility are improved, but control and security are worsened
Solution Approach 1:
The patent segments the application into multiple components and selectively places them in different cloud environments. Critical components requiring security and control remain in the private cloud, while non-critical components that benefit from elasticity are deployed to the public cloud. This segmentation allows the system to simultaneously achieve elasticity from public cloud resources while maintaining security through private cloud isolation for sensitive workloads.
2Reliability
If workloads are hosted on on-premise infrastructure, then control and security are improved, but elasticity and cost-effectiveness are worsened
Solution Approach 1:
The patent merges private cloud and public cloud infrastructure into a hybrid cloud environment. The private cloud provides controlled, secure hosting for critical workloads, while the public cloud adds elastic capacity. The system dynamically orchestrates workload placement across both environments, allowing organizations to maintain control over sensitive operations while leveraging public cloud elasticity during peak demand periods, thus combining the advantages of both infrastructure types.
3Productivity
If individual VM placement is optimized, then resource utilization is improved, but application structure constraints are ignored
Solution Approach 1:
The patent implements a dynamic placement approach that adapts to application structure constraints. Rather than treating all VMs independently, the system dynamically identifies components with strict placement requirements and respects those constraints during optimization. The placement algorithm dynamically adjusts resource allocation based on application topology, ensuring that components with dependencies are placed appropriately while still maximizing overall resource utilization across the hybrid cloud infrastructure.
Data Source
AI summary
Placing an application on a private portion and a public portion of a hybrid computing environment for processing. An application may be received for placement and processing. A primary processing objective and a split preference of the application may be determined. The split preference indicates whether the application can be processed using one or both of the private portion and the public portion of the hybrid computing environment. The application may be placed on one or both of the private portion and the public portion of the hybrid computing environment for processing, based on the primary processing objective and based on the split preference.