Dynamic Resource Allocation for Data Center Utilization
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Solution Overview
Problem
Data centers face inefficiencies in resource management due to varying resource utilization patterns across different services, leading to overprovisioning and unnecessary costs, as existing systems often base capacity on peak utilization peaks that do not coincide, resulting in underutilization and inefficient billing practices.
Innovation Solution
A resource monitoring system with a service request module and a resource module that utilizes an API to monitor and manage resources, implement a pricing/billing module to shape resource utilization, and apply cross-dimensional resource-shaping techniques to decouple and optimize resource allocation, allowing for better matching of resource demand and supply across services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data centers base capacity on peak utilization peaks, then service reliability is improved, but resource utilization efficiency deteriorates due to overprovisioning
Solution Approach 1:
The patent implements dynamic resource allocation by continuously monitoring actual resource consumption patterns and adjusting capacity assignments in real-time. The system transitions from static peak-based provisioning to dynamic demand-responsive allocation, where resources are allocated based on actual usage patterns rather than predetermined peak capacities, thereby improving utilization efficiency while maintaining service reliability through flexible adjustment mechanisms.
Solution Approach 2:
The system changes the parameter basis for capacity determination from peak utilization metrics to actual average consumption patterns. By analyzing real-world usage data and shifting from peak-oriented to average-based capacity planning, the system eliminates overprovisioning while ensuring sufficient resources are available during normal operation, thus resolving the contradiction between reliability and efficiency.
2Reliability
If dedicated servers are assigned to each service, then service isolation is improved, but resource allocation efficiency deteriorates due to inability to share resources
Solution Approach 1:
The patent implements a universal resource pool that can be dynamically assigned to multiple different services based on actual demand. Instead of dedicated servers for each service, the system creates a shared resource infrastructure where any service can access any resource from the pool. This multi-functional approach maintains service isolation through logical separation while enabling efficient resource sharing across services, resolving the contradiction between isolation and allocation efficiency.
Solution Approach 2:
The system introduces a resource allocation intermediary layer that mediates between services and physical resources. This intermediary manages the mapping between service requests and available resources, enabling services to access the resource pool without direct physical connections. The intermediary ensures proper resource distribution while maintaining service boundaries, thus achieving both isolation and efficiency simultaneously.
3Reliability
If billing is based on peak utilization, then service level agreement compliance is improved, but cost efficiency deteriorates due to paying for unused capacity
Solution Approach 1:
The system implements feedback-based billing by continuously monitoring actual resource consumption and using this information to adjust billing calculations. Instead of billing based on predetermined peak capacities, the system receives feedback on actual usage patterns and charges accordingly. This feedback mechanism ensures SLA compliance by guaranteeing sufficient resources while improving cost efficiency by charging only for actually consumed capacity, eliminating waste from paying for unused peak capacity reserves.
Data Source
AI summary
An exemplary component for managing requests for resources in a data center includes a service request module for receiving requests for resources from a plurality of services and a resource module to monitor resources in a data center and to match received requests to resources. Such a component optionally includes an application programming interface (API) that provides for sending information in response to an API call made by a service. Other methods, devices and systems are also disclosed.