Dynamic Provisioning Engine for On-Demand Training Labs
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Solution Overview
Problem
The existing methods for staging hands-on training labs are expensive and logistically complex, with significant costs for systems, software, and maintenance, and lack common tools for content creation and distribution, making it difficult to coordinate and scale training efforts for software releases.
Innovation Solution
A method for dynamically provisioning computing resources on-demand, using an instantiation engine to select and provision service provider computing devices based on user requests, allowing for scalable and efficient access to computing resources for training courses at scheduled times, reducing the need for physical infrastructure and enabling remote access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If physical infrastructure and systems are acquired for hands-on training labs, then training quality and effectiveness are improved, but acquisition costs and maintenance expenses increase significantly
Solution Approach 1:
The patent creates virtual copies of physical training lab environments through virtual machines and cloud computing instances. These virtual replicas provide hands-on training functionality without requiring actual physical hardware acquisition, thereby maintaining training quality while eliminating significant acquisition costs for systems and software infrastructure
Solution Approach 2:
The patent replaces physical mechanical training lab infrastructure with virtualized computing resources. Instead of acquiring physical servers, workstations, and laboratory equipment, the system uses virtual machine instances deployed on cloud platforms, substituting physical hardware with software-based virtual environments that provide identical training capabilities
2Ease of operation
If physical training labs are staged and configured, then hands-on training capability is improved, but logistics complexity and time consumption increase
Solution Approach 1:
The patent implements dynamic provisioning of training lab environments through automated virtual machine deployment. Training labs can be rapidly instantiated, scaled, and terminated based on demand without manual physical setup, enabling on-demand access while eliminating complex logistics related to physical equipment deployment and management
Solution Approach 2:
The patent enables users to self-serve by automatically provisioning virtual training environments through simple software interfaces. The system automatically handles infrastructure setup, configuration, and resource allocation without requiring users to engage with complex physical logistics, thereby improving accessibility while reducing perceived system complexity
3Manufacturing precision
If content creation and distribution are coordinated manually, then training content quality is maintained, but coordination difficulty and time consumption increase
Solution Approach 1:
The patent creates a universal virtualized training platform that serves multiple functions: content delivery, environment provisioning, user management, and resource allocation. This multi-functional system consolidates previously separate manual coordination tasks into a single integrated platform, improving content distribution efficiency while maintaining quality through standardized virtualized templates
Solution Approach 2:
The patent transforms the delivery parameters of training content from physical media and manual distribution to digital virtual machine instances. By changing the fundamental parameter of content delivery from physical to virtual, the system achieves automated scaling and distribution while maintaining content quality through standardized virtual environments that can be replicated indefinitely
Data Source
AI summary
A method for providing access to dynamically provisioned resources and on-demand courses includes receiving, by an instantiation engine executing on a first computing device, from a second computing device associated with a user, an indication that the user has purchased access to the course at a scheduled time. A type of computing resource is identified for use during the course at the scheduled time. A service provider computing device is selected from a plurality of service provider computing devices, based upon an ability to provide access to the identified type of computing resource at the scheduled time. Before the scheduled time, the instantiation engine instructs the selected service provider computing device to provision a computing resource of the identified type. The method includes transmitting, to the second computing device, an instruction to establish a connection to the provisioned computing resource at the scheduled time.