Hybrid Cloud Resource Management via User Status Triggers
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Solution Overview
Problem
In hybrid cloud environments, resources such as compute and storage instances continue to consume valuable resources and incur significant costs when not actively utilized, making it difficult to efficiently reallocate or reclaim them, leading to increased operational business costs.
Innovation Solution
A system that includes a processor and memory to receive user status triggers from mobile, biometric, or geo-fencing applications, analyze usage data, and provide recommendations for resource deployment or termination to optimize resource usage, automatically identifying and reallocating resources based on usage patterns and policies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If resources continue to run in hybrid cloud environment to ensure availability, then service reliability is improved, but operational costs increase due to unused resources consuming compute time, network bandwidth and cloud resources
Solution Approach 1:
The system dynamically adjusts resource states based on real-time usage detection. Resources are automatically transitioned between active, suspended, and terminated states according to detected usage patterns, allowing the system to maintain reliability when needed while reducing operational costs during idle periods
Solution Approach 2:
The system implements continuous monitoring of resource usage and provides feedback triggers that initiate state changes. When usage is detected below thresholds, the system feedbacks to suspend or terminate resources; when usage exceeds thresholds, resources are activated, creating a closed-loop control system that balances reliability and cost
2Productivity
If manual identification and re-allocation of unused resources is performed, then resource efficiency is improved, but time consumption increases making it difficult to reclaim resources promptly
Solution Approach 1:
The system enables resources to self-manage their state based on detected usage conditions. Resources automatically transition to suspended or terminated states when usage drops below thresholds, and reactivate when usage increases, eliminating the need for manual intervention while maintaining high resource efficiency
Solution Approach 2:
The system continuously monitors resource usage and prepares for state changes in advance. When usage patterns indicate impending idle periods, the system proactively suspends or terminates resources before complete idle occurrence, reducing the time required for resource reclamation
Data Source
AI summary
Resource management in a cloud environment is disclosed. One example is a system including at least one processor and a memory storing instructions executable by the at least one processor to receive an action trigger indicative of a status of a user from a source application, wherein the source application includes a mobile application, a biometric application or a geo-fencing application, retrieve an activity status for a resource of a plurality of resources in a hybrid cloud environment, and provide, based on the action trigger and the activity status, a recommendation for deployment or non-deployment of the resource to achieve resource efficiency.