SAN Event Mapping for Root Cause Analysis
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Solution Overview
Problem
Current models for analyzing Storage Area Networks (SANs) are limited in accurately representing system behavior and relationships, making it difficult to determine the impact of failures and their root causes, as they lack detailed information about system operation and only represent basic elements and configurations.
Innovation Solution
A method is introduced that represents selected components and their relationships in a SAN system, creating non-specific representations of events and their propagation, providing a mapping between events and observable events, and performing system analysis based on this mapping to improve analysis accuracy and root-cause determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a limited number of network elements and relationships are represented in the model, then the model complexity is reduced, but the measurement precision and analysis accuracy deteriorate
Solution Approach 1:
The patent segments the SAN system into distinct object classes (storage devices, hosts, switches, links) with hierarchical relationships. This segmentation allows the model to represent complex systems through manageable components while maintaining analysis accuracy by capturing essential relationships at each level of the hierarchy.
Solution Approach 2:
The patent introduces a new dimensional framework by adding multiple object classes and relationship types beyond traditional network elements. This includes dimensions for storage-specific relationships (LUN mappings, device paths) and event propagation paths, enabling accurate representation without linearly increasing complexity.
2Ease of manufacture
If basic elements and configurations are represented in the model, then the ease of manufacture and implementation is improved, but the loss of information about finer details of system operation increases
Solution Approach 1:
The patent creates universal object classes that can represent multiple specific SAN components (e.g., storage devices encompassing disks, arrays, volumes). This universality allows the model to capture fine-grained operational details through standardized interfaces, maintaining ease of implementation while preventing information loss about system operations.
Solution Approach 2:
The patent introduces event objects as intermediaries that capture detailed system operations and propagate them through the model. These event intermediaries carry fine-grained operational information without requiring complex direct representations of all system details, thus preserving information while maintaining implementation simplicity.
3Measurement precision
If detailed representations of all components and relationships are created, then the measurement precision and analysis accuracy are improved, but the device complexity and difficulty of operation increase
Solution Approach 1:
The patent applies local quality by allowing detailed representations only where necessary for accurate analysis. Different object classes have different levels of detail based on their analytical importance, enabling high precision for critical components while maintaining lower complexity for less critical elements, thus optimizing the balance between accuracy and complexity.
4Measurement precision
If comprehensive event mapping is performed between all events and observable events, then the measurement precision for root cause determination is improved, but the loss of time for performing analysis increases
Solution Approach 1:
The patent performs preliminary action by pre-establishing the event mapping framework and object relationships before analysis is needed. The model structure, object classes, and relationship definitions are prepared in advance, allowing rapid analysis execution while maintaining high root cause determination accuracy through the pre-configured event propagation paths.
Data Source
AI summary
A method, apparatus and computer program product for performing an analysis on a Storage Area Network (SAN) system, containing a plurality of components, is disclosed. The method comprises the steps of representing selected ones of the plurality of components and the relationship among the components, wherein the representation comprises the steps of creating at least one non-specific representation of the selected components and creating at least one non-specification representation of relations along which the events propagate amongst the selected components, providing a mapping between a plurality events and a plurality of observable events occurring among the components, wherein the mapping is represented as a value associating each event with each observable event, and performing the system analysis based on the mapping of events and observable events.