Intelligent Load Balancer Selection in Multi-Load Balancer Environments
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Solution Overview
Problem
In multi-load balancer environments, the manual and ad-hoc selection of load balancers for load balancing duties leads to inefficient resource usage and sub-optimal performance, as administrators often choose load balancers based on perception rather than actual resource availability and performance metrics.
Innovation Solution
A computer system generates a user interface to select a load balancer based on predefined criteria such as resource usage, load balancing performance, and location, collecting statistics from available load balancers to automatically choose the most suitable one that optimally satisfies the specified criteria, leveraging Software Defined Networking (SDN) infrastructure for communication and management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual and ad-hoc selection of load balancer is used, then ease of operation is improved, but resource usage efficiency deteriorates
Solution Approach 1:
The system enables load balancers to automatically evaluate themselves against multiple criteria (resource usage, performance metrics, location) and select the most suitable candidate without human intervention. The automated selection process allows the system to serve itself by making intelligent decisions based on real-time statistics and predefined policies.
2Productivity
If automated selection based on multiple criteria is implemented, then resource usage efficiency is improved, but device complexity increases
Solution Approach 1:
The complex selection process is divided into separate, manageable components: criteria definition (resource usage, performance, location), statistics collection from individual load balancers, automated evaluation against multiple criteria, and final selection. This segmentation allows each component to be independently configured and managed, reducing overall system complexity.
Solution Approach 2:
An intermediary automated selection mechanism is introduced between the user and the load balancer pool. This intermediary collects statistics from multiple load balancers, evaluates them against predefined criteria, and automatically selects the best candidate, thereby managing the complexity of multi-criteria evaluation without requiring direct user involvement in the complex decision-making process.
3Ease of operation
If manual selection by network administrator is used, then ease of operation is improved, but service performance deteriorates
Solution Approach 1:
The system implements feedback loops where statistics from load balancers (resource usage, performance metrics) are continuously collected and used to inform the selection process. This feedback mechanism ensures that the selected load balancer is based on actual performance data rather than administrator perception, thereby improving service performance while maintaining ease of operation through automation.
Data Source
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AI summary
Techniques for performing intelligent load balancer selection in a multi-load balancer environment are provided. In one embodiment, a computer system can generate a user interface for deploying a virtual IP address (VIP) on a load balancer in a network environment, where the network environment includes a plurality of load balancers, and where the user interface presents a plurality of criteria for selecting one of the plurality of load balancers. The computer system can further receive, from a user, a selection of one or more of the plurality of criteria, and can collect, from each load balancer in the plurality of load balancers, statistics that are relevant to the one or more criteria. The computer system can then select a load balancer from among the plurality of load balancers based on the one or more criteria and the collected statistics.