Native Storage Data Collection via Independent Plug-ins
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Solution Overview
Problem
Existing data collection techniques for storage area networks are intrusive and resource-intensive, requiring agents on multiple sources and lacking a standardized mechanism for collecting performance, capacity, and discovery data across different communication types.
Innovation Solution
A method and system for native data collection using a software structure with sharable communication interfaces to access multiple data sources, employing data collection plug-ins for performance, capacity, and discovery data, and distributing collected data according to a request, which can be triggered by events and managed through a policy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If agents are installed on each data source to collect data, then data collection coverage is improved, but system complexity and resource consumption increase
Solution Approach 1:
The patent extracts the data collection functionality from individual data sources by removing the need for agents on each source. Instead, a centralized data collection component polls data from multiple sources using standardized protocols, eliminating the complexity of distributed agent management while maintaining comprehensive data collection coverage
Solution Approach 2:
The patent creates a universal data collection interface that can collect data from multiple different data sources using various communication protocols (SNMP, CORBA, JDBC, Web services) through a single standardized mechanism. This multi-functional interface replaces the need for source-specific agents, reducing system complexity while maintaining broad data collection capability
2Reliability
If agents are installed on each data source to collect data, then data collection completeness is improved, but computing resource usage increases
Solution Approach 1:
The patent enables data sources to serve themselves by exposing standardized interfaces that the centralized data collection component can directly access. This self-service approach eliminates the need for resource-intensive agent processes on each data source, reducing computing resource consumption while maintaining complete data collection through direct polling of source interfaces
3Adaptability or versatility
If a standardized data collection mechanism is implemented across multiple communication types, then adaptability is improved, but implementation complexity increases
Solution Approach 1:
The patent introduces an intermediary data collection interface layer that handles the complexity of multiple communication protocols (SNMP, CORBA, JDBC, Web services). This mediator translates various source-specific protocols into a unified data collection mechanism, improving adaptability to different data sources while hiding implementation complexity from the rest of the system
Data Source
AI summary
A native data collection component may be implemented as a tool, appliance, application and/or utility, and including physical and/or logical implementations thereof. The native data collection component may be responsible for data orchestration, data collection, and aggregation and distribution of collected data from among multiple sources. Accordingly, the native data collection component may be independent of a particular data source and act as an independent performance characteristic collection mechanism. In an embodiment, the native data collection component may include three devices/sub-components: a data orchestration device, a data collection interface and a data aggregation and distribution device. Each sub-component may be service based and communication with each service may be done using state-less protocols. The data collection interface enables a software structure that includes data collection plug-ins that are independent of data sources and are not deployed into the SAN as agents of any of the data sources.