Cloud Load Balancer for Virtual Machine Integration
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Solution Overview
Problem
In cloud integration, the random allocation of locks to virtual machines often leads to inefficient resource utilization, resulting in slower processing and potential crashes due to limited memory and CPU availability, as complex integration steps are executed on virtual machines with insufficient resources.
Innovation Solution
A load balancer module is introduced to distribute integration steps across multiple virtual machines based on available resources, allowing users to select virtual machines with the most suitable memory or CPU capacity, ensuring that integration steps are executed on the virtual machine with the least resource constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If random allocation of locks to virtual machines is used, then simplicity of lock distribution is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The load balancer continuously monitors resource utilization metrics (CPU usage, memory availability, disk I/O) of each virtual machine and uses this feedback to dynamically adjust lock allocation decisions, selecting the virtual machine with the least current load to receive the lock and execute integration steps
Solution Approach 2:
The system changes the allocation parameter from random selection to selection based on resource utilization parameters, where the load balancer evaluates multiple parameters (CPU, memory, disk) and selects the virtual machine that optimizes overall system performance
2Ease of operation
If integration steps are executed on any available virtual machine, then ease of task distribution is improved, but system reliability deteriorates
Solution Approach 1:
The load balancer monitors resource thresholds and feedback from virtual machines to determine when to allocate locks, ensuring that integration steps are only executed on virtual machines with sufficient resources to complete tasks without crashing
Solution Approach 2:
The system performs preliminary resource verification before allocating locks to virtual machines, checking that sufficient CPU, memory, and disk resources are available to handle the incoming integration steps, thereby preventing resource exhaustion and crashes
3Speed
If multiple virtual machines receive data simultaneously, then data distribution speed is improved, but processing speed deteriorates
Solution Approach 1:
The system extracts the lock acquisition mechanism from the data distribution process, allowing multiple virtual machines to receive data simultaneously while only one virtual machine (the one with the lock) executes the integration steps, thus maintaining both fast data distribution and efficient processing
Data Source
AI summary
A method and system including two or more virtual machines; a load balancer module; a load balancer processor in communication with the load balancer module and operative to execute processor-executable process steps to cause the system to: initiate an application integration component; create a set of one or more integration steps to transfer data between a cloud-based application and a second application; receive selection of an element of a virtual machine; broadcast a current state of each virtual machine to the other virtual machines; determine which of the two or more virtual machines has a pre-set amount of the selected element; retrieve a mutual exclusion component, wherein the mutual exclusion component is retrieved by the virtual machine determined to have the pre-set amount of the selected element; and execute the integration steps at the virtual machine that retrieved the mutual exclusion component. Numerous other aspects are provided.