Distributed Policy Control for Virtualization Resource Contention

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Solution Overview

Problem

Existing virtualization infrastructure management systems lack effective real-time monitoring and dynamic optimization capabilities, leading to inefficiencies and resource contention issues in cloud data centers.

Innovation Solution

A policy controller and policy agents are deployed to monitor and manage resource usage across virtualization infrastructure elements, applying rulesets and profiles to optimize resource distribution and performance, with features like real-time analytics and machine learning to adjust policies dynamically.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If virtualization infrastructure is deployed to improve resource efficiency and control, then efficiency and management advantages are improved, but real-time monitoring and dynamic optimization capabilities are insufficient leading to resource contention issues

Engineering Contradiction:

Improveresource efficiencyVSAvoidmonitoring capability

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system segments the monitoring function by deploying distributed policy agents on individual compute nodes, infrastructure elements, and network devices throughout the virtualization infrastructure. Each agent independently monitors local resource usage and metrics, then reports to a centralized policy controller. This segmentation enables comprehensive real-time monitoring across the entire infrastructure while maintaining the productivity benefits of virtualization.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The policy controller acts as an intermediary between the virtualized compute resources and the management system. It receives metrics from policy agents, evaluates them against defined policies and rulesets, and automatically executes remediation actions when resource contention or performance issues are detected. This intermediary layer provides the missing real-time monitoring and dynamic optimization capabilities without disrupting the virtualization architecture.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If multiple virtual machines and containers share physical computing resources, then resource utilization efficiency is improved, but resource contention and performance management issues worsen

Engineering Contradiction:

Improveresource utilization efficiencyVSAvoidresource contention

Core Design Contradiction:

ProductivityVSObject-affected harmful factors

Solution Approach 1:

The system implements continuous feedback loops where policy agents monitor resource usage metrics from virtual machines and containers, report to the policy controller, which then evaluates policies and executes remediation actions. This closed-loop feedback mechanism detects resource contention conditions in real-time and automatically adjusts resource allocation or triggers remediation, maintaining high utilization efficiency while preventing performance degradation from contention.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The policy controller dynamically changes operational parameters such as resource allocation limits, scheduling priorities, and policy rulesets based on real-time metrics evaluation. When resource contention is detected, the system adjusts parameters like CPU quotas, memory limits, or network bandwidth allocations for affected virtual machines and containers, thereby maintaining efficient resource utilization while eliminating harmful contention effects.

Inventive Principle:

Principle #35Parameter changes

3Loss of information

If comprehensive monitoring of infrastructure elements is implemented, then visibility and performance management are improved, but system complexity increases

Engineering Contradiction:

Improveperformance visibilityVSAvoidsystem complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The policy agent is designed as a universal multi-functional component that can be deployed on any compute node, infrastructure element, or network device in the virtualization infrastructure. It performs multiple functions including local metric collection, policy evaluation, and remediation execution. This universality enables comprehensive monitoring across diverse infrastructure elements without requiring different monitoring solutions for each component, thereby improving performance visibility while controlling system complexity through standardization.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS12489696B2Policy controller for distributed virtualization infrastructure element monitoring

Publication Date: 2025.12.02 HEWLETT PACKARD ENTERPRISE DEV LP

AI summary

This disclosure describes techniques for monitoring, scheduling, and performance management for virtualization infrastructures within networks. In one example, a computing system includes a plurality of different cloud-based compute clusters (e.g., different cloud projects), each comprising a set of compute nodes. Policy agents execute on the compute nodes to monitor performance and usage metrics relating to resources of the compute nodes. Policy controllers within each cluster deploy policies to the policy agents and evaluate performance and usage metrics from the policy agents by application of one or more rulesets for infrastructure elements of the compute cluster. Each of the policy controllers outputs data to a multi-cluster dashboard software system indicative of a current health status for the infrastructure elements based on the evaluation of the performance and usage metrics for the cluster. The multi-cluster dashboard software system data outputs, as single user interface screen, the current health status for each of the cloud-based compute clusters.