Private Cloud AI Orchestration for Simplified Tool Updates
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Managing and updating AI tools in on-premises private clouds is complicated due to the variety of hardware and software sources, making it difficult to keep systems up-to-date and efficiently deploy new configurations.
Innovation Solution
A simplified setup process for AI functionality in private clouds, where racks are delivered pre-configured with AI tools, and updates are managed through a remote cloud management system using a single-click interface, streamlining network and user access, and ensuring compatibility with existing systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If AI tools are deployed in on-premises private clouds with multiple hardware and software sources, then system functionality and versatility are improved, but device complexity and difficulty of management increase
Solution Approach 1:
The patent introduces a control plane as an intermediary layer between the diverse hardware/software sources and the AI tools. This control plane provides unified management, configuration, and orchestration capabilities, allowing multiple sources to be coordinated through a single interface rather than requiring direct management of each component separately.
Solution Approach 2:
The system is segmented into distinct functional layers: a control plane for management and orchestration, and worker nodes for executing AI workloads. This segmentation allows the complex management tasks to be isolated in the control plane while the worker nodes focus on computation, reducing overall management complexity.
2Adaptability or versatility
If AI tools are manually configured and updated across multiple sources, then customization and adaptability are improved, but loss of time and productivity decrease
Solution Approach 1:
The control plane performs preliminary configuration and validation of AI tools before deployment to worker nodes. By pre-configuring and validating tools centrally, the system eliminates time-consuming manual configuration steps at each deployment location while maintaining customization capabilities through the centralized interface.
Solution Approach 2:
The control plane serves multiple functions including configuration management, software updates, monitoring, and orchestration across all AI tools and worker nodes. This universal management interface handles diverse tasks through a single system, improving productivity by eliminating the need for separate management processes for each function.
3Reliability
If comprehensive monitoring and management of AI tools is implemented, then reliability and system health are improved, but device complexity and operational overhead increase
Solution Approach 1:
The control plane implements self-service monitoring capabilities that automatically detect, diagnose, and resolve issues with AI tools and worker nodes. The system autonomously tracks system health metrics, identifies problems, and performs corrective actions without requiring manual intervention, thereby improving reliability while reducing operational overhead.
Data Source
AI summary
Efficient implementation of setup of racks with artificial intelligence (AI) tools in private or on-premises clouds and updating the AI tools are provided herein. Specifically, a remote cloud management system includes a private cloud AI platform orchestrator that is remote from a private cloud system. The remote cloud management system is configured to interface with the private cloud system using a connector and to orchestrate artificial intelligence (“AI”) operations on the private cloud system using the private cloud AI platform orchestrator. The remote cloud management system is also configured to manage AI software installed in the private cloud system.