Mainframe Network Dependency Mapping for Latency Risk Assessment
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Solution Overview
Problem
Organizations using IBM mainframe computers face challenges in determining a complete and accurate view of network systems and dependencies, leading to unclear network traffic profiles and increased business application performance risks due to unknown network latency impacts.
Innovation Solution
A method and system for analyzing mainframe application network traffic by generating a dataset of IP entities, visualizing network dependencies, and categorizing systems by latency sensitivity using IT asset inventory data, including diagrammatic visualizations and latency sensitivity rings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If network traffic analysis is performed to identify dependencies and latency sensitivity, then understanding of network communications is improved, but complexity of analysis and processing is increased
Solution Approach 1:
The patent segments network traffic analysis into distinct components: capturing TCP communications records, generating IP entity inventories, creating diagrammatic visualizations, and categorizing systems into latency sensitivity rings. This segmentation allows the complex analysis to be broken down into manageable processing stages, reducing overall system complexity while maintaining comprehensive network understanding.
Solution Approach 2:
The patent introduces an intermediary analysis system that sits between the mainframe network traffic and the users/organizations. This intermediary captures, processes, and presents network communication data in an understandable format, shielding users from the complexity of raw network analysis while providing comprehensive network dependency and latency sensitivity information.
2Measurement precision
If comprehensive network traffic monitoring is implemented to assess dependencies, then accuracy of network profile is improved, but resource consumption is increased
Solution Approach 1:
The patent implements partial monitoring by focusing specifically on TCP communications with the mainframe system rather than monitoring all network traffic. This selective approach captures the essential network dependencies and latency sensitivities while reducing the overall resource consumption associated with comprehensive full-network monitoring.
Solution Approach 2:
The patent extracts only the relevant information from network traffic records that is necessary for assessing dependencies and latency sensitivity. By extracting and analyzing only the essential data elements rather than processing all available network information, the system achieves accurate network profiling with reduced resource consumption.
3Reliability
If detailed analysis of network communications is performed, then identification of latency risks is improved, but time required for analysis is increased
Solution Approach 1:
The patent performs preliminary action by capturing and storing TCP communications records during normal network operations before latency issues manifest. This allows the system to have network dependency and traffic pattern information readily available for rapid analysis when latency risks need to be assessed, reducing the time required for on-demand analysis.
Solution Approach 2:
The system enables self-service by automatically categorizing IP entities into latency sensitivity rings and generating diagrammatic visualizations without requiring manual analysis. This automation provides reliable latency risk identification while minimizing the time investment required from analysts or operators.
Data Source
AI summary
A computer-implemented method including obtaining records of TCP communications for a mainframe computing system for a time period. The method also can include generating, using the records, a first dataset including an inventory of IP entities that communicated with the mainframe computing system over TCP during the time period. The method additionally can include generating one or more visualizations based at least in part on information in the first dataset. The one or more visualizations can include a diagrammatic visualization including representations of LPARs of the mainframe computing system, system groups of the IP entities, and respective volumes of network traffic between the mainframe computing system and the system groups of the IP entities for the time period. The method further can include generating an allocation of the IP entities into rings representing respective potential latency sensitivities. The method additionally can include causing to be displayed outputs including the one or more visualizations and the allocation of the IP entities. Other embodiments are described.