Graph Transformations for Data Center SLO Violation Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Data center management systems face inefficiencies in managing service-level objectives (SLOs) due to pre-allocation of resources and per-resource controllers, leading to increased costs and potential SLO violations.
Innovation Solution
The use of graph transformations to create mutated graphs that evaluate and correct SLO violations by optimizing resource allocation across multiple systems and vendors within a data center, thereby ensuring compliance with SLOs while minimizing resource expenditure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pre-allocation of resources is used to handle peak application needs, then service-level objectives are maintained, but resource costs increase and resources may not be available for new needs
Solution Approach 1:
The patent implements dynamic resource allocation by continuously monitoring service-level objective compliance and automatically adjusting resource assignments in response to changing workload conditions. The system transitions from static pre-allocation to dynamic real-time adjustment, allowing resources to be allocated based on actual current needs rather than peak predictions, thereby reducing wasted resources while maintaining SLO compliance.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor SLO compliance metrics and use this information to automatically adjust resource allocation decisions. When SLO violations are detected or resource utilization patterns change, the feedback loop triggers re-evaluation and reallocation of resources, creating a closed-loop control system that optimizes resource expenditure while maintaining service level commitments.
2Reliability
If per-resource controllers are used to maintain service-level objectives, then SLO compliance is improved, but more resources are expended and additional SLO violations occur
Solution Approach 1:
The patent merges the functionality of multiple independent per-resource controllers into a unified resource management system. Instead of having separate controllers for each resource that operate independently and potentially conflict with each other, the system consolidates control logic to coordinate resource allocation across the entire data center, reducing overall controller resource expenditure while maintaining SLO compliance through centralized coordination.
Solution Approach 2:
The resource management system is designed with universal control logic that can manage multiple resource types (storage, compute, network, memory) through a single integrated framework. This multi-functional approach eliminates the need for separate specialized controllers for each resource type, reducing the total number of controllers required while maintaining comprehensive SLO monitoring and enforcement capabilities.
3Productivity
If pre-allocation of entire storage systems is used, then peak needs are satisfied, but resources are not available for new needs and costs increase
Solution Approach 1:
The patent segments storage systems and resources into finer-grained allocatable units rather than treating entire storage systems as indivisible pre-allocated blocks. This segmentation allows the system to allocate smaller portions of storage capacity to different applications based on actual needs, enabling more flexible adaptation to new requirements while maintaining the ability to satisfy peak demands through aggregated resource allocation.
Solution Approach 2:
The system implements dynamic resource allocation that continuously adapts to changing workload patterns and new service requirements. Rather than being locked into static pre-allocation agreements, the system can dynamically adjust resource assignments in real-time, allowing resources to be reassigned from declining workloads to emerging needs, thereby maintaining both peak satisfaction capability and adaptability to new requirements.
Data Source
AI summary
Graph transformations are used by a data management system to correct violations of service-level objectives (SLOs) in a data center. In one aspect, a process is provided to manage a data center by receiving an indication of a violation of a service-level objective associated with the data center from a server in the data center. A graph representation and a transformations data container are retrieved by the data management system from data storage accessible to the data management system. The transformations data container includes one or more transformations. The transformation is processed to create a mutated graph from a data center representation from the graph representation. An option for managing the data center is determined as a result of evaluating the mutated graphs.