Cloud Provisioning Readiness Verification System
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Solution Overview
Problem
Current cloud provisioning processes face challenges such as configuration errors, provisioning downtime, and manual labor-intensive readiness processes, which lead to inefficiencies and customer dissatisfaction, especially due to differing interpretations between customers and server providers.
Innovation Solution
An automated cloud provisioning readiness check system that collects and analyzes configuration data using a processor-based system, employing rule-based analysis and remediation to determine readiness and automatically adjust configurations, reducing manual errors and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual readiness verification processes are used, then flexibility in handling different customer interpretations is maintained, but provisioning time and manual labor increase significantly
Solution Approach 1:
The system performs self-service by automatically collecting configuration data, executing readiness checks against stored rules, and determining provisioning readiness without requiring manual verification. The processor-based system independently completes the entire readiness verification process, eliminating dependency on manual operations while maintaining accuracy through predefined rules.
Solution Approach 2:
The system performs preliminary action by collecting and analyzing configuration data before the actual provisioning process begins. Readiness checks are executed in advance to determine whether provisioning can proceed, allowing potential issues to be identified and resolved before they cause delays during the provisioning itself.
2Productivity
If automated readiness checks are implemented, then provisioning efficiency improves, but system complexity increases
Solution Approach 1:
The automated readiness check system is segmented into distinct functional components: a data collection module that gathers configuration information, a rules storage module that maintains readiness criteria, and an analysis module that executes checks. This segmentation allows each component to perform its specific function independently, making the overall complex system manageable and maintainable through modular design.
Solution Approach 2:
The processor-based system acts as an intermediary between the configuration data and the provisioning process. It mediates by automatically analyzing configurations against readiness rules and determining whether provisioning should proceed, eliminating the need for manual intervention while managing the complexity through a centralized automated decision-making layer.
3Reliability
If configuration settings are automatically adjusted, then provisioning readiness improves, but risk of unauthorized changes increases
Solution Approach 1:
The system implements feedback by continuously monitoring configuration settings and comparing them against readiness rules. When configurations are found to be non-compliant, the system can trigger alerts or automated corrections, ensuring that only properly configured systems proceed to provisioning. This feedback loop maintains reliability by preventing unauthorized or incorrect configurations from affecting the provisioning process.
Data Source
AI summary
Technology described herein can verify readiness of a customer tenant/customer for cloud provisioning based on the customer tenant. An example method comprises collecting, by a system comprising a processor, data based on user input from a customer tenant via a user interface, the data comprising information of a configuration setting that is to be used for cloud provisioning of a device based on the configuration setting. The method comprises, in response to collecting the configuration setting, analyzing, by the system, the configuration setting by comparing the configuration setting with respect to a selected rules check. The method comprises, in response to the analyzing of the configuration setting, determining, by the system, whether the configuration setting is acceptable for use in the cloud provisioning based on the configuration setting.