Autonomous Multi-Cloud Solution Design via Crowdsourced Partitioning
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Solution Overview
Problem
The increasing complexity and cost of managing cloud services and IT services due to the influx of providers and ever-changing capabilities make it challenging for customers to maintain skilled teams or outsource effectively, necessitating an autonomous multi-cloud solution design and fulfillment platform.
Innovation Solution
A crowdsourcing approach that uses a cloud solution program to parse customer requests into partitions, advertise them to participating solutioning teams, and leverage trusted networks for secure, automated, and transparent collaboration, employing domain modeling language and electronic contracts to create and verify solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional cloud service management is used with multiple providers, then service capabilities and options increase, but management complexity and costs increase
Solution Approach 1:
The patent introduces an autonomous multi-cloud solution design and fulfillment platform as an intermediary layer between customers and multiple cloud service providers. This platform automatically manages service orchestration, provisioning, and configuration across different providers, thereby maintaining service versatility while reducing management complexity for customers.
Solution Approach 2:
The patent segments the complex multi-cloud management process into distinct functional modules including service design, provisioning, configuration, and optimization. Each module handles specific aspects of cloud service management independently, making the overall system more manageable and easier to operate despite dealing with multiple providers.
2Reliability
If skilled teams are maintained to manage cloud services, then service quality improves, but operational costs increase
Solution Approach 1:
The patent implements self-service capabilities through automated algorithms and AI-driven orchestration that can independently design, provision, and manage cloud services without requiring skilled human teams. The system automatically optimizes resource allocation and service configuration, maintaining high service quality while eliminating the need for expensive specialized personnel.
Solution Approach 2:
The patent replaces manual mechanical processes of skilled team members with automated computational systems. Algorithms perform service design, resource allocation, and configuration tasks that previously required human expertise, thereby maintaining service quality while reducing operational costs associated with skilled labor.
3Productivity
If outsourcing is used to manage cloud services, then internal resource allocation improves, but control and transparency decrease
Solution Approach 1:
The patent incorporates comprehensive feedback mechanisms that provide real-time visibility into cloud service management operations. The platform continuously monitors service performance, resource allocation, and configuration changes, providing transparent information flow between the automated system and customers. This maintains control and visibility while enabling effective outsourcing of management functions.
Data Source
AI summary
A method, computer system, and a computer program product for multi-cloud solution design and fulfillment via crowdsourcing is provided. Embodiments of the present invention may include receiving a request, wherein the request includes computing requirements. Embodiments of the present invention may include parsing the received request into partitions. Embodiments of the present invention may include advertising the partitions to a plurality of participating members on a trusted network environment. Embodiments of the present invention may include receiving conceptual solutions to the partitions. Embodiments of the present invention may include evaluating the received conceptual solutions.