Virtual Machine Pre-provisioning via Request Pattern Weighting
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Solution Overview
Problem
Current cloud service providers face inefficiencies in server provisioning times, which can take minutes, hindering user satisfaction, especially when dealing with frequent requests for virtual servers, as they rely on elaborate workflows that do not effectively utilize prediction techniques to pre-configure servers based on user demand.
Innovation Solution
Implementing a method for rapid provisioning of virtual machines by deriving weight functions from historical data to prioritize and pre-provision virtual machine instances based on user request patterns, caching frequently requested images, and optimizing cache composition to reduce the time spent on image fetching and expansion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional cloud server provisioning workflow is used, then service delivery is achieved, but provisioning time is too long (minutes)
Solution Approach 1:
The system performs preliminary actions by analyzing historical request patterns and pre-provisioning virtual machine instances before users actually request them. The cloud provider uses machine learning models to predict future requests and prepares server instances in advance, transforming the reactive provisioning workflow into a proactive one that delivers servers immediately when requested.
Solution Approach 2:
The system dynamically adjusts provisioning strategies based on real-time and historical data. It continuously learns from user request patterns and adapts its pre-provisioning decisions, optimizing which virtual machine instances to create and when to delete them, thereby dynamically balancing provisioning speed with resource efficiency.
2Speed
If pre-provisioning based on prediction techniques is implemented, then provisioning speed is improved, but system complexity increases
Solution Approach 1:
The system introduces intermediary components including machine learning prediction models and a pre-provisioning management layer that sits between user requests and the actual virtualization infrastructure. These intermediaries handle the complexity of pattern analysis and decision-making, allowing the core provisioning system to remain relatively simple while achieving intelligent pre-provisioning capabilities.
Data Source
AI summary
An apparatus and an article of manufacture for pre-provisioning a virtual machine instance include deriving a weight function for at least one virtual machine request based on historical data of the at least one virtual machine request to create a weighted virtual machine request for each request, capturing at least one inter-arrival pattern of requests, and applying the at least one pattern to the at least one weighted request to create a prioritized ordering of the at least one weighted request, and pre-provisioning at least one instance of a virtual machine image based on the prioritized ordering of the at least one weighted request.