Automated Bootstrap for Hardware Inventory Integration
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Solution Overview
Problem
Manual processes for expanding data center capacity are time-consuming, inconsistent, and prone to service interruptions, lacking efficiency and scalability in integrating new hardware into cloud-computing fabrics.
Innovation Solution
An automated bootstrap process that verifies and integrates non-configured hardware as a fabric-computing cluster within a cloud-computing fabric, utilizing self-contained workflows for discovery, validation, and deployment, ensuring consistent and effective expansion of data center capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual processes are used for integrating new hardware into the fabric, then flexibility in handling diverse hardware configurations is maintained, but the process becomes time-consuming, inconsistent, and prone to service interruptions
Solution Approach 1:
The system performs self-discovery and self-configuration of hardware components. The fabric controller automatically detects new hardware, retrieves configuration data from the hardware inventory, and configures components without human intervention, enabling the system to service itself during expansion operations
Solution Approach 2:
Configuration data is pre-stored in the hardware inventory before physical hardware deployment. The system retrieves this predetermined configuration information during the integration process, allowing rapid deployment without time-consuming manual configuration steps
2Reliability
If manual configuration steps are performed for each hardware component, then customization for specific hardware requirements is possible, but consistency and reliability of the integration process deteriorate
Solution Approach 1:
The fabric controller implements a universal integration process that handles diverse hardware types (network devices, storage devices, compute devices) through a single automated workflow. The system retrieves appropriate configuration data from the hardware inventory based on device type, providing consistent treatment across different hardware categories without requiring separate manual procedures
Solution Approach 2:
The hardware inventory serves as an intermediary database that stores predetermined configuration data for various hardware components. The fabric controller queries this intermediary to obtain configuration information, eliminating the need for manual configuration steps while ensuring consistency through centralized data management
3Productivity
If existing hardware is reconfigured to operate with existing nodes, then data center capacity is expanded, but service interruptions may occur during the reconfiguration process
Solution Approach 1:
Configuration data is prepared and stored in the hardware inventory before hardware deployment or reconfiguration begins. This preliminary preparation allows the automated process to quickly retrieve and apply configurations without interrupting ongoing services, as all configuration decisions are predetermined and executed atomically
Solution Approach 2:
The automated discovery and configuration process rapidly progresses through hardware integration steps without pausing for manual intervention. The system quickly discovers hardware, retrieves configuration data, and completes integration in a streamlined sequence that minimizes the window of potential service disruption
4Productivity
If automated bootstrap process is implemented for hardware integration, then integration efficiency and consistency are improved, but system complexity increases
Solution Approach 1:
The system uses template-based configuration data stored in the hardware inventory that represents ideal hardware configurations. Instead of creating configurations from scratch or through complex manual procedures, the automated process retrieves and applies pre-defined configuration templates, simplifying the integration workflow while maintaining high efficiency
Data Source
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AI summary
Methods, systems, and computer-readable media for automatically configuring an inventory of hardware to interact seamlessly with a computing fabric of a data center are provided. Initially, a communicative coupling between a user device and computing units of the hardware inventory is established. The communicated coupling allows an engine running on the user device to provision the computing units with software that allows the hardware inventory to function as a fabric-computing cluster (FCC) of the data center. Provisioning involves deploying a computing fabric to the computing units, and deploying core infrastructure services to run on top of the computing fabric. The computing fabric enables the computing units to interact as a unified logical system, while the core infrastructure services represent operating-system-level components that provide underlying support of applications running on the FCC. Upon carrying out the provisioning, the components internal to the computing units of the hardware inventory are validated.