Hybrid Cloud Resource Allocation for Cost Predictability
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Solution Overview
Problem
Hybrid cloud systems face challenges in resource management, particularly in predicting costs and efficiently utilizing on-prem and public cloud resources, leading to potential over-purchasing of system resources and unpredictable expenses.
Innovation Solution
A project management tool that allocates resources from both on-prem and public cloud platforms based on project requests, prioritizing the use of existing on-prem resources and leveraging public cloud resources when on-prem resources are insufficient, while optimizing resource utilization and cost management through scheduling and resource assignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If public cloud resources are used to provide flexibility and additional capacity, then resource availability and scalability are improved, but cost predictability deteriorates due to pay-as-you-go pricing
Solution Approach 1:
The system dynamically selects between on-prem and public cloud resources based on real-time resource availability and project requirements. The resource allocation is not static but adapts to changing conditions, allowing the system to maintain cost predictability by preferring on-prem resources while scaling to public cloud only when necessary.
Solution Approach 2:
The hybrid cloud system creates a universal resource pool that encompasses both on-prem and public cloud resources. This multi-functional resource pool can serve different project needs differently - using on-prem resources for stable, predictable workloads and public cloud resources for scalable, variable workloads, thereby achieving both cost predictability and resource scalability.
2Loss of energy
If on-prem resources are pre-purchased to reduce long-term costs, then cost efficiency is improved, but resource utilization efficiency deteriorates due to potential over-purchasing
Solution Approach 1:
The system continuously monitors resource utilization across on-prem and public cloud platforms and uses this feedback to optimize allocation. By tracking actual usage patterns, the system can identify underutilized on-prem resources and reallocate them or adjust future purchasing decisions, thereby improving both cost efficiency and resource utilization efficiency simultaneously.
Solution Approach 2:
The patent merges on-prem and public cloud resources into a unified hybrid cloud environment. This combination allows the system to leverage the cost efficiency of on-prem resources while compensating for their limited scalability by integrating public cloud resources, thereby achieving both cost efficiency and high resource utilization efficiency through optimized resource pooling.
3Reliability
If multiple systems are managed separately to maintain control, then system reliability is improved, but operational complexity increases making central management necessary
Solution Approach 1:
The patent merges the management of on-prem and public cloud systems into a unified hybrid cloud management platform. This consolidation maintains the reliability and control benefits of separate system management while reducing operational complexity by providing centralized control, single-pane monitoring, and automated resource allocation across both environments.
Solution Approach 2:
The system introduces a centralized management platform as an intermediary between on-prem and public cloud systems. This mediator handles resource allocation, monitoring, and coordination, thereby maintaining the reliability of individual systems while simplifying overall management complexity through automated mediation and coordination protocols.
Data Source
AI summary
Example implementations described herein involve providing an interface configured to receive input to generate a project request for a project; determining an allocation of resources for the project for execution; determining a schedule for the project based on the project request based on the allocation of resources; for the first service platform being available to allocate the resources to execute the project according to the schedule, allocating the resources for executing the project on the first service platform according to the schedule; for the first service platform being unavailable to execute the project according to the schedule, determining whether a second service platform is available to allocate the resources to execute the project according to the schedule, and for the second service platform being available to execute the project according to the schedule, allocating the resources for executing the project on the second service platform according to the schedule.