Feature-Centric Diagnostics for Distributed Systems
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Solution Overview
Problem
Identifying and resolving failures in distributed computer systems is challenging due to the complexity of analyzing failures across multiple components and the need for extensive information exchange between support teams, often resulting in substantial time and effort, which can damage a software provider's reputation.
Innovation Solution
A feature-centric diagnostic system is embedded within each component of a distributed computer system, enabling processors to execute diagnostic functions, communicate with system analyzers, and provide a unified interface to end users with recommendations for troubleshooting non-desired operational statuses, simplifying the identification of root causes and remediation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional troubleshooting methods are used with multiple components and extensive information exchange between support teams, then comprehensive failure analysis is achieved, but substantial time and effort are required
Solution Approach 1:
The system segments the distributed computer system into individual components, each with its own diagnostic module. Each component can be analyzed independently through its diagnostic module, which collects and analyzes component-specific data locally. This segmentation allows parallel analysis of multiple components simultaneously, reducing the overall troubleshooting time while maintaining comprehensive failure analysis capability.
Solution Approach 2:
The system introduces a centralized diagnostic server as an intermediary that coordinates between multiple diagnostic modules and support teams. The server aggregates diagnostic data from various components, performs centralized analysis, and provides unified troubleshooting guidance. This intermediary eliminates the need for extensive direct communication exchanges between support teams while ensuring comprehensive analysis through centralized coordination.
2Measurement precision
If comprehensive diagnostic information is collected from multiple components and configurations, then root cause identification accuracy is improved, but system complexity increases
Solution Approach 1:
The diagnostic system is segmented into modular diagnostic modules, each responsible for specific components or aspects of the distributed system. Each module independently collects and analyzes relevant data for its designated component, reducing the complexity of data collection while ensuring comprehensive coverage. The modular structure allows each module to focus on specific diagnostic tasks, improving root cause identification accuracy without overwhelming system complexity.
Solution Approach 2:
The diagnostic server provides universal diagnostic capabilities that can handle multiple types of components, configurations, and failure modes through a single unified platform. Rather than requiring separate complex diagnostic systems for each component type, the universal diagnostic server can analyze logs, configurations, and runtime data from various components using standardized procedures, thereby improving root cause identification accuracy while managing system complexity.
3Ease of manufacture
If multiple separate troubleshooting mechanisms are maintained for each component, then component-specific diagnostics are optimized, but overall system troubleshooting efficiency decreases
Solution Approach 1:
The system merges multiple component-specific diagnostic mechanisms into a unified diagnostic framework. Each component retains its optimized diagnostic capabilities through dedicated modules, but these modules are integrated and coordinated by a centralized diagnostic server. The server aggregates data from all components and provides unified analysis, enabling both component-specific optimization and system-level efficiency. This merging eliminates the need for separate troubleshooting processes while maintaining the benefits of component-specific diagnostic expertise.
Solution Approach 2:
The diagnostic server provides universal troubleshooting capabilities that can handle any component in the distributed system through standardized interfaces and analysis procedures. Rather than requiring separate troubleshooting teams and processes for each component, the universal diagnostic server can analyze failures across all components using consistent methods, thereby improving overall system troubleshooting efficiency while maintaining the optimized diagnostic approaches for individual components.
Data Source
AI summary
A distributed computer system includes components. The components include embedded computer processors that make up an application within the distributed computer system. The computer processors are accessible by an end user of the system. The computer processors are operable to communicate with a plurality of system analyzers, to generate an operational status of the application in the system based on the communication with the plurality of system analyzers, to generate one or more recommendations to address or troubleshoot a non-desired operational status of the application within the system, and to provide a unified interface to the end user that provides to the end user the one or more recommendations to address or troubleshoot the non-desired operational status of the application within the system.