Normalized Performance Index for Virtualized Workload Resource Allocation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In virtualized computing environments, existing solutions poorly address the challenge of balancing price and performance, leading to capacity bottlenecks, performance degradation, and inefficient resource allocation, which can result in downtime and increased costs.
Innovation Solution
A system and method for normalized performance indexing that includes a performance manager to generate a Price Performance Delta Index (PPDI) to optimize resource allocation across workloads, ensuring balanced performance and cost by reallocating resources based on the index.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If physical servers are consolidated into virtual servers to reduce hardware costs, then cost efficiency is improved, but resource capacity bottlenecks and performance degradation occur
Solution Approach 1:
The system dynamically monitors resource utilization metrics (CPU, memory, storage, network) and automatically adjusts resource allocation based on changing workload demands. The performance index calculation and resource reallocation occur continuously, allowing the virtualized environment to adapt to varying loads and prevent capacity bottlenecks while maintaining cost efficiency through consolidation.
Solution Approach 2:
The system implements a feedback mechanism where resource utilization data is collected, analyzed to generate performance indexes, and used to trigger resource reallocation when thresholds are exceeded. This closed-loop control ensures that performance degradation is detected and corrected by reallocating resources before critical bottlenecks occur, maintaining reliability while preserving consolidation benefits.
2Productivity
If shared resources are over-utilized to maximize consolidation benefits, then cost efficiency is improved, but performance degradation and downtime occur
Solution Approach 1:
The system calculates performance indexes and identifies potential capacity bottlenecks before they cause performance degradation or downtime. By proactively monitoring resource utilization trends and predicting when thresholds will be exceeded, the system can pre-allocate additional resources or redistribute workloads to prevent service disruption, ensuring both high utilization and availability.
Solution Approach 2:
Continuous monitoring of resource utilization provides feedback that triggers automatic resource reallocation when performance indexes indicate approaching capacity limits. This ensures that shared resources are fully utilized without exceeding thresholds that would cause degradation, maintaining the balance between productivity and reliability.
3Measurement precision
If manual resource allocation is used to manage workloads, then control precision is improved, but operational complexity and time consumption increase
Solution Approach 1:
The system automatically performs resource allocation and reallocation based on calculated performance indexes without requiring manual intervention. The performance manager continuously monitors resource utilization, identifies bottlenecks, and executes resource redistribution autonomously, providing precise control while eliminating the time consumption and operational complexity associated with manual management.
Solution Approach 2:
The system transforms complex multi-dimensional resource utilization data into simplified performance index parameters that automatically guide resource allocation decisions. By changing the representation of resource states into actionable index values, the system enables automated precise control without requiring manual analysis or intervention, reducing management time while maintaining allocation accuracy.
Data Source
AI summary
Systems and methods relate to indexing of performance and cost of workloads in a computing environment. The computing environment may include a virtualized computing environment. According to some embodiments, a performance index relating to a plurality of workloads executing in the computing environment may be generated, where the performance index is based at least in part on performance and cost of use of one or more resources in the computing environment by the plurality of workloads. The index may be normalized. If the performance or cost of a particular workload departs from an expected performance or cost determined from the average performance and/or cost in the computing environment, resources may be reallocated to the workloads such that the performance or cost of the workload is closer to its expected performance or cost based on the performance index.