Automated Computing Infrastructure Deployment With State Reconciliation
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Solution Overview
Problem
Existing data centre deployment methods involve manual configuration, leading to errors, inconsistencies, and extended downtime, and existing solutions like Cisco APIC, OpenStack Ironic, and Microsoft Azure Stack require multiple controllers or pre-existing infrastructure, lacking support for BareMetal servers and network infrastructure integration.
Innovation Solution
A computer-implemented method and system for automated deployment of computing infrastructure using a CMDB module, deployment module, communication module, configuration module, NOG module, and DNS module, which manage and automate the deployment and configuration of un-provisioned servers and switches, ensuring real-time data reconciliation and safety updates to maintain consistency and reduce errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual configuration methods are used for deploying data centres, then flexibility and adaptability are maintained, but errors, inconsistencies, and extended downtime occur
Solution Approach 1:
The system enables automated self-provisioning where the computing infrastructure automatically discovers and configures itself without manual intervention. The automated deployment module detects un-provisioned servers and switches, retrieves their true states, and configures them based on registered data, allowing the system to serve itself during deployment.
Solution Approach 2:
The system performs preliminary actions by pre-registering infrastructure data in the CMDB before physical deployment. The registered data (desired state) is prepared in advance, allowing the automated deployment module to quickly configure devices by comparing their true states against the pre-prepared registered data, eliminating the need for manual configuration during deployment.
2Reliability
If existing solutions like Cisco APIC are used, then network infrastructure management is improved, but deployment requires three controllers making it unsuitable for initial deployments with limited resources
Solution Approach 1:
The invention extracts the essential infrastructure management functionality from complex multi-controller systems. The automated deployment module isolates and implements only the critical functions needed for initial deployment (discovery, state comparison, configuration), eliminating the need for multiple controllers while maintaining management capability.
Solution Approach 2:
The automated deployment module is designed to perform multiple functions within a single component: it discovers un-provisioned devices, retrieves their true states, compares them with registered data, and applies configurations. This multi-functional approach replaces the need for separate controllers while maintaining comprehensive infrastructure management.
3Adaptability or versatility
If OpenStack Ironic is used for managing BareMetal servers, then server lifecycle management is provided, but it requires a pre-existing infrastructure making it less suitable for initial deployments
Solution Approach 1:
The system performs preliminary action by pre-registering infrastructure data in the CMDB before physical devices are deployed. This allows the automated deployment module to immediately configure BareMetal servers upon discovery without requiring pre-existing infrastructure management systems, as the configuration data is already prepared in advance.
Solution Approach 2:
The automated deployment module enables BareMetal servers to self-provision by automatically detecting them, comparing their true states with pre-registered data, and applying configurations without requiring external infrastructure management systems. The system serves itself during the initial deployment phase.
4Reliability
If real-time frequency updates are used in the communication module, then data consistency is improved, but system resource consumption increases
Solution Approach 1:
The communication module performs safety operations at periodic intervals (safety frequency) rather than continuously. It compares true states with registered data at these periodic intervals and updates only when differences are detected, maintaining data consistency while reducing resource consumption compared to continuous real-time monitoring.
Solution Approach 2:
The system implements feedback by comparing the true state of infrastructure components with their registered states and only updating the registered data when differences are detected. This feedback mechanism ensures data consistency by correcting discrepancies while minimizing unnecessary updates and resource consumption.
Data Source
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AI summary
The technology relates to a computer-implemented method for managing a computing infrastructure having several components, each component being in a state, called true state, the method comprising: - a communication module receives data at a given frequency, called real-time frequency, and updates registered data of a database, depending on the received data, - the module executes a safety operation at a given frequency, called safety frequency, the safety operation comprising: • comparing each true state of each component to each registered state of each component registered in the database, and • when the corresponding registered state differs from the true state, updating the database by replacing the registered state by the true state, called replacing data, - the real-time frequency being smaller than the safety frequency.