AI Data Center Device Configuration Automation

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Solution Overview

Problem

Conventional data center management approaches are time-consuming and prone to errors due to the manual control of communication speeds and settings across devices, making it difficult to accurately monitor and respond to device changes in a timely manner.

Innovation Solution

The implementation of automated configuration determinations using artificial intelligence (AI) that processes input information and telemetry data to determine optimal device configurations and perform automated actions, leveraging deep reinforcement learning and neural networks to optimize data center performance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual techniques are used to control communication speeds and settings across devices, then configuration changes can be made with human judgment, but the process becomes time-consuming and labor-intensive

Engineering Contradiction:

Improveaccuracy of configuration decisionsVSAvoidtime required for configuration management

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system enables automated self-service through AI agents that independently analyze device telemetry data, determine optimal configurations, and implement changes without human intervention. The configuration management system automatically monitors device states, processes performance metrics, and executes configuration adjustments based on learned patterns from historical data.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual mechanical processes of configuration management are replaced with an automated AI-based system. The patent substitutes human operators with machine learning models that process device data, predict optimal settings, and execute configuration changes programmatically, eliminating the need for manual intervention while improving speed and consistency.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If manual techniques are used to monitor and respond to device changes, then human operators can make judgment-based decisions, but errors are commonly introduced

Engineering Contradiction:

Improvespeed of response to device changesVSAvoidaccuracy of configuration decisions

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system implements continuous feedback loops where AI agents monitor device telemetry data, compare actual performance against expected outcomes, and automatically adjust configurations in response to observed changes. The system learns from historical configuration outcomes and continuously refines its decision-making based on feedback from device performance metrics.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The configuration management system performs self-correction and self-optimization by automatically detecting device changes, analyzing their impact on performance, and implementing appropriate configuration adjustments without human intervention, thereby eliminating human error while maintaining rapid response times.

Inventive Principle:

Principle #25Self-service

3Productivity

If automated actions are performed based on AI-determined configurations, then timeliness and accuracy are improved, but system complexity increases

Engineering Contradiction:

Improveefficiency of configuration managementVSAvoidcomplexity of configuration system

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent introduces AI agents as intermediary components between device telemetry data and configuration decisions. These agents serve as intelligent mediators that process raw device data, apply learned knowledge from historical configurations, and generate optimized configuration recommendations, thereby managing system complexity through modular intelligent intermediaries.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The AI-based configuration management system is designed as a universal platform that can handle multiple device types, various configuration parameters, and diverse operational scenarios through a single integrated system. The patent implements multi-functional AI agents that can adapt to different device contexts and perform multiple configuration tasks, reducing overall system complexity through consolidation.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS11775819B2Automated configuration determinations for data center devices using artificial intelligence techniques

Publication Date: 2023.10.03 DELL PROD LP

AI summary

Methods, apparatus, and processor-readable storage media for automated configuration determinations for data center devices using artificial intelligence are provided herein. An example computer-implemented method includes obtaining input information pertaining to one or more device-related changes to a data center; obtaining telemetry data attributed to one or more devices in the data center; determining one or more device configurations for implementation in at least one device in the data center in connection with the one or more device-related changes by processing the input information and the obtained telemetry data using one or more artificial intelligence techniques; and performing at least one automated action based at least in part on the one or more determined device configurations.