Network Analytics System for Dynamic Topology Insights
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Solution Overview
Problem
Computer networks face complexity and challenges in detecting, predicting, and troubleshooting issues due to their intricate configurations and numerous potential problems such as link failures, security vulnerabilities, and traffic fluctuations, making it difficult to maintain network health and performance.
Innovation Solution
The implementation of a system that dynamically generates topology, time, and location-based network insights by analyzing statistical changes in time series data, obtaining telemetry data, and generating insights on network trends and deviations, allowing for real-time monitoring and adaptive configuration adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If network configuration options are increased to provide flexibility and control, then network adaptability is improved, but device complexity increases
Solution Approach 1:
The patent introduces an intermediary system that sits between the network administrator and the complex network infrastructure. This intermediary automatically discovers network topology, collects telemetry data, and translates high-level intent statements into specific configuration commands, thereby shielding administrators from complexity while maintaining flexibility
Solution Approach 2:
The system implements self-service capabilities through automated network discovery, topology mapping, and configuration generation. The network infrastructure essentially configures itself based on collected telemetry data and high-level intent statements, reducing the burden on administrators despite increased network complexity
2Reliability
If network monitoring and analysis capabilities are enhanced to detect and predict issues, then network reliability is improved, but device complexity increases
Solution Approach 1:
The patent merges multiple monitoring and analysis functions into a unified system. The topology discovery, telemetry collection, statistical analysis, and insight generation are combined into a single integrated platform, reducing overall system complexity while improving reliability through comprehensive monitoring
Solution Approach 2:
The system implements continuous feedback loops where telemetry data is collected, analyzed against statistical baselines, and used to generate insights that feed back into network configuration and monitoring. This automated feedback mechanism improves reliability without requiring complex manual intervention
3Measurement precision
If statistical analysis of time series data is performed to identify trends and deviations, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary actions by continuously collecting and pre-processing telemetry data, maintaining statistical baselines, and pre-computing topological relationships. When analysis is needed, this pre-prepared data enables rapid trend detection and deviation identification without time-consuming computations
Data Source
AI summary
Technologies for dynamically generating topology and location based network insights are provided. In some examples, a method can include determining statistical changes in time series data including a series of data points associated with one or more conditions or parameters of a network; determining a period of time corresponding to one or more of the statistical changes in the time series data; obtaining telemetry data corresponding to a segment of the network and one or more time intervals, wherein a respective length of each time interval is based on a length of the period of time corresponding to the one or more of the statistical changes in the time series data; and generating, based on the telemetry data, insights about the segment of the network, the insights identifying a trend or statistical deviation in a behavior of the segment of the network during the one or more time intervals.