Storage Dependency Tree Visualization for Error Impact
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional storage systems lack an efficient method to determine the scope of dependencies between components, making it difficult to assess the impact of errors or changes on the system.
Innovation Solution
A computer-implemented method and system where a management server receives storage system object data, determines logical dependencies, and forms a tree structure to visualize these dependencies, allowing clients to render the tree and identify impacted components based on user input or error indications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional backend systems are used without dependency tracking, then system simplicity is maintained, but the ability to determine the scope of error impact is inefficient
Solution Approach 1:
The system performs preliminary actions by automatically discovering and storing dependency relationships between storage system objects before errors occur. The management server proactively builds a dependency graph that maps relationships between storage pools, LUNs, file systems, and other objects, enabling rapid error impact assessment without adding operational complexity to the storage system itself.
Solution Approach 2:
A management server acts as an intermediary between the storage system components and the dependency tracking functionality. This intermediary layer collects object data, determines dependencies, and presents the information without requiring changes to the core storage system architecture, thus improving measurement precision while minimizing device complexity.
2Reliability
If dependency tracking is implemented, then error impact assessment capability is improved, but system complexity increases
Solution Approach 1:
The management server performs self-service by automatically discovering dependencies between storage objects without requiring manual configuration or intervention. The system autonomously collects object data, analyzes relationships, and maintains the dependency graph, improving reliability through automated error impact assessment while avoiding the complexity of manual dependency management.
Solution Approach 2:
The system creates a virtual copy or representation of the storage system's dependency structure in the form of a dependency graph. This graphical model replicates the relationships between storage objects, enabling error impact assessment without physically modifying the storage system architecture. The graph serves as a simplified abstraction that improves reliability while containing complexity in the management layer.
3Productivity
If manual dependency determination is used, then system complexity is reduced, but time consumption for error impact analysis increases
Solution Approach 1:
The system replaces manual mechanical processes of dependency determination with automated electronic data processing. The management server electronically collects object data, processes relationships algorithmically, and generates dependency graphs instantaneously, dramatically improving productivity in error impact analysis. This substitution introduces complexity in the management server but eliminates the need for manual intervention.
Solution Approach 2:
The system implements feedback mechanisms where the management server continuously monitors storage object states and automatically updates the dependency graph based on changes in the storage system. This automated feedback loop enables real-time error impact assessment without manual input, improving productivity while the feedback processing complexity is contained within the management server's automated workflows.
Data Source
AI summary
Described are methods, systems, and apparatus, including computer program products for determining and managing the dependencies of components of a storage system. Storage system object data for a plurality of storage system objects on a storage system is received by a management server. A plurality of logical dependencies are determined by the management server based on the storage system object data, where each logical dependency reflects a dependency between at least two storage system objects of the plurality of storage system objects. A tree having a plurality of nodes and a plurality of edges is formed by the management server, where each edge connects a first node and a second node, the first node representing a first storage system object and the second node representing a second storage system object, and the edge representing a logical dependency between the first storage system object and the second storage system object.