Data Storage Volume Response Time Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data storage systems lack an efficient method to identify performance problems and their potential causes, making it difficult to diagnose and address issues affecting data storage volume performance.
Innovation Solution
A method and system that display sorted maximum response times for data storage volumes, allowing users to select and analyze volumes with performance issues through a graphical user interface, providing additional information on workload and performance characteristics, and visualizing component-level utilization to identify potential sources of problems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional data storage performance monitoring methods are used, then system operation continues without interruption, but performance problems and their causes cannot be efficiently identified
Solution Approach 1:
The system proactively collects and analyzes performance data from multiple sources (storage devices, hosts, networks) before problems become critical. By continuously monitoring response times, I/O operations, and system utilization, the performance analysis tool prepares diagnostic information in advance, enabling rapid problem identification when performance degradation occurs.
Solution Approach 2:
The performance analysis tool acts as an intermediary between raw performance data and system administrators. It collects data from various components (storage devices, hosts, networks), processes this information through analysis algorithms, and presents synthesized performance metrics and diagnostic insights, bridging the gap between complex system operations and human understanding.
2Measurement precision
If detailed performance data is collected from all storage volumes, then comprehensive analysis capability is achieved, but system complexity and data processing burden increase
Solution Approach 1:
The performance analysis tool extracts only the most relevant performance metrics from the vast amount of available data. It focuses on collecting specific data points such as response times, I/O operation counts, and utilization percentages from storage volumes, hosts, and networks, rather than processing all possible system parameters, thereby reducing complexity while maintaining diagnostic precision.
Solution Approach 2:
The system applies different data collection and analysis strategies to different storage volumes based on their specific characteristics. Rather than uniformly monitoring all volumes with the same level of detail, it adapts the measurement approach to local conditions, collecting comprehensive data for problematic volumes while using lighter monitoring for healthy volumes, thus optimizing the balance between precision and complexity.
Data Source
AI summary
Described are techniques for identifying a data storage volume exhibiting a performance problem. First information indicating a sorted ordering of a plurality of maximum response times is displayed for a plurality of data storage volume. A first of the plurality of data storage volumes having a largest one of the plurality of maximum response times is selected. In response to such selecting, additional information is displayed in the user interface about the first data storage volume. The additional information includes at least one workload or performance characteristic of the first data storage volume.