Host Controller Virtual Machine Load Balancing
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Solution Overview
Problem
Existing virtual machine management systems face challenges in load balancing across hosts in a cluster, leading to performance degradation due to manual selection processes that are time-consuming and inefficient.
Innovation Solution
A host controller with a virtual machine manager that selects hosts based on CPU consumption and expected load, using a host selection rating calculated from current and expected CPU load, and confirms memory availability to automate the distribution of virtual machines, thereby balancing load without manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual host selection is used for virtual machine deployment, then system administrator control is maintained, but the process becomes time-consuming and inefficient
Solution Approach 1:
The system performs self-service by automatically selecting appropriate hosts for virtual machine deployment without requiring manual administrator intervention. The host selection module autonomously evaluates host metrics, calculates ratings, and makes deployment decisions based on current system state and load balancing requirements.
Solution Approach 2:
The system performs preliminary actions by pre-calculating host ratings and maintaining updated metrics about each host's capacity and load status. This preparation work is done in advance so that when virtual machine deployment is needed, the system can quickly make informed decisions without time-consuming analysis at deployment moment.
2Productivity
If virtual machines are distributed across hosts, then load balancing is achieved, but manual intervention increases system complexity
Solution Approach 1:
The system implements feedback by continuously monitoring host metrics such as CPU usage, memory availability, and current load status. This feedback information is used by the host selection module to dynamically adjust host ratings and make informed deployment decisions that maintain optimal load balancing across the cluster.
Solution Approach 2:
The system applies parameter changes by dynamically adjusting host ratings based on changing system conditions. As host metrics change over time, the ratings are recalculated to reflect current capacity and load status, allowing the system to adapt to varying conditions without manual reconfiguration.
3Productivity
If automated host selection is implemented, then deployment speed improves, but selection accuracy may be compromised
Solution Approach 1:
The system performs preliminary calculations to pre-determine host ratings based on current metrics and deployment requirements. This advance preparation ensures that when deployment decisions are made, they are based on pre-analyzed data, maintaining both speed and accuracy without requiring time-consuming analysis at the moment of deployment.
Data Source
AI summary
A host controller selects a host from a host cluster to run a virtual machine. In one embodiment, a host controller receives a request to run a virtual machine. The virtual machine may be a newly added virtual machine, or an existing virtual machine that needs to migrate from a currently active host to another host. The host controller selects a host from the host cluster based on current central processing unit (CPU) consumption and expected load to be incurred by the virtual machine. The expected load may be estimated from the number of cores to be used by the virtual machine. The host controller then assigns the virtual machine to run on the host.