Storage Area Network Rule Engine Validator Functions
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Solution Overview
Problem
Conventional storage area network management applications face challenges due to complex configurations of resources, requiring time-consuming manual verification and are prone to errors if incompatibilities are not properly identified, and existing rule engines are cumbersome to maintain and use.
Innovation Solution
A rule engine process that utilizes validator functions to apply sets of rules to storage area network resources, identifying compatible and optimal configurations by selecting appropriate validator functions based on resource types and attributes, producing error and warning information to notify users of potential issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual verification of storage area network configuration is performed, then compatibility can be checked, but the process is time-consuming and error-prone
Solution Approach 1:
The system automatically performs compatibility verification by having the storage area network configuration itself be analyzed by the rule engine. The configuration data is processed to extract resource information, which is then validated against compatibility rules without requiring manual intervention, thus achieving self-service verification.
Solution Approach 2:
The patent replaces manual mechanical verification processes with an automated computational system. The rule engine uses software algorithms to process configuration data, apply compatibility rules, and generate validation results, substituting the mechanical manual checking process with an automated information processing system.
2Measurement precision
If comprehensive rule sets are used to ensure compatibility, then verification accuracy improves, but the rule engine becomes more complex and cumbersome to maintain
Solution Approach 1:
The compatibility rules are segmented into distinct rule sets that can be independently managed and applied to different resource types. The rule engine processes rules in organized groups, allowing comprehensive coverage without creating a monolithic complex system. Each rule set can be maintained separately, reducing overall maintenance difficulty.
Solution Approach 2:
The system manages rule complexity by parameterizing rule application based on resource types and configurations. Instead of maintaining a single complex rule set, the system adapts rule application dynamically based on the specific resources being validated, reducing the effective complexity of any individual rule set while maintaining comprehensive coverage.
3Reliability
If detailed compatibility rules are applied to all resources, then verification thoroughness improves, but the processing time and computational resources increase
Solution Approach 1:
The rule engine applies different levels of validation detail to different resource types based on their specific requirements. Instead of uniformly applying all rules to all resources, the system tailors the validation depth to match the local needs of each resource type, achieving thorough validation where needed while maintaining speed for simpler resources.
Solution Approach 2:
The system applies partial validation rules selectively rather than exhaustively applying all possible rules to every resource. This allows the validation process to be thorough enough for compatibility assurance while avoiding unnecessary computational overhead from applying overly detailed rules to all resources, thereby improving processing speed.
Data Source
AI summary
A rule engine process utilizes so-called validator functions to identify how to apply specified sets of different rules to respective types of resources in a storage area network environment. For example, a rule engine initially receives information indicating a given storage area network resource to be validated. The rule engine process identifies a type or characteristic associated with the given resource and, thereafter, selects one of multiple respective validator functions to test the given resource. The selected validator function specifies rule processing information such as which rules to apply to the identified type of resource, an order for applying the rules, and conditions whether certain rules will be applied to the given resource based on an outcome of previously applied rules. In one embodiment, application of a set of rules specified by a respective validator function can yield a range of different types of error and/or warning information.