AR Node Diagnostics for Faster Data Center Fault Repair
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Solution Overview
Problem
Maintaining and diagnosing large-scale data center systems, such as Hyper Converged Infrastructure (HCI) clusters, is challenging due to geographic dispersion and the complexity of numerous elements, requiring sophisticated diagnostic tools that simplify fault detection and enable quick resolution by customer service technicians.
Innovation Solution
An augmented reality (AR) diagnostic tool on a portable device that uses AR infrastructure to locate, diagnose, and provide recommendations for repairing failed HCI cluster nodes by sending diagnostic information to a cloud-based analytics service and employing beacon technology for proximity analysis and image detection features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional diagnostic methods are used for large-scale data center systems, then technicians can perform basic troubleshooting, but the geographic dispersion and quantity of elements make maintenance challenging and time-consuming
Solution Approach 1:
The patent replaces manual mechanical inspection and conventional diagnostic procedures with an augmented reality system that uses optical visualization and digital overlay technology. The AR device superimposes diagnostic information, node identifiers, and system status directly in the technician's field of view, eliminating the need to manually navigate complex system documentation and physically locate components in dispersed data center environments.
Solution Approach 2:
The AR diagnostic tool acts as an intermediary between the complex data center system and the technician. It processes raw system data, node configurations, and diagnostic information through the AR platform, presenting simplified visual representations and guided troubleshooting steps that bridge the gap between system complexity and human comprehension.
2Loss of time
If technicians manually locate and diagnose failed nodes in dispersed data centers, then basic troubleshooting can be performed, but the time required to locate and assess root causes increases significantly
Solution Approach 1:
The AR diagnostic system uses color-coded visual indicators to represent different system states, node statuses, and fault conditions. Failed nodes, warning conditions, and system health metrics are displayed with distinct color codes directly overlaid on physical components, enabling technicians to rapidly identify and prioritize issues without manual inspection or interpretation of technical documentation.
Solution Approach 2:
The patent adds a digital information dimension to the physical data center environment by superimposing virtual diagnostic data, node identifiers, and system status information directly onto the physical infrastructure through AR visualization. This multi-dimensional presentation allows technicians to access comprehensive diagnostic information while maintaining spatial awareness of physical component locations.
3Reliability
If sophisticated diagnostic tools are implemented to handle geographic dispersion and system complexity, then diagnostic capability improves, but the ease of operation decreases and requires specialized knowledge
Solution Approach 1:
The AR diagnostic system provides self-guided troubleshooting capabilities that enable technicians to perform complex diagnostic tasks independently. The system automatically detects node failures, retrieves relevant system information, and presents step-by-step diagnostic guidance directly in the technician's field of view, eliminating the need for external expert intervention or specialized training on complex diagnostic procedures.
Solution Approach 2:
The AR diagnostic platform serves multiple diagnostic functions through a single unified interface. It can identify node locations, display system status, guide troubleshooting procedures, and provide repair instructions across diverse data center configurations and hardware platforms, making the tool universally applicable without requiring specialized knowledge for different system types.
Data Source
AI summary
An augmented reality (AR) diagnostic tool embodied as a software application on a portable device employs AR infrastructure to enable a user to locate a failed/malfunctioning node of a cluster and, with minimal interaction, diagnose causes and provide recommendations to repair the node. The portable device may be a computer embodied as visualization technology and configured to execute the software application. Once installed, the AR diagnostic (ARD) tool is ready for use by the user, e.g., a customer service technician, to locate and repair one or more failed cluster nodes. In response to a failure/malfunction, the cluster node sends diagnostic and configuration information (i.e., failure/malfunction information) of the failed node to an analytics service. The failure information informs the technician of the cluster failure. The technician may then activate the ARD tool and AR infrastructure to locate and repair the failed node.