KPI Recommendation Engine for Network Device Monitoring
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Solution Overview
Problem
There is a lack of an intuitive approach for selecting appropriate key performance indicators (KPIs) for network devices, making it difficult to monitor their health effectively in a network operations center, especially when dealing with various devices and roles.
Innovation Solution
A method is introduced to quickly identify and recommend KPIs based on the type and configuration of network devices by filtering out irrelevant operational information and ranking relevant KPIs using a relevancy ranking algorithm, allowing for efficient monitoring of network devices by grouping them based on functionality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple key performance indicators are used to monitor network devices, then the comprehensiveness of monitoring is improved, but the complexity of selecting and managing appropriate KPIs increases
Solution Approach 1:
The system automatically determines and recommends appropriate KPIs for network devices based on their type and configuration, eliminating the need for manual selection by operators. The automated KPI determination process uses device information to select from a set of possible KPIs, making the system self-configure and reducing operational complexity.
Solution Approach 2:
The system dynamically adjusts KPI selection based on changing device parameters such as device type, configuration, and role. By re-evaluating device characteristics, the system can adapt KPI recommendations to match current device states, ensuring appropriate monitoring parameters are selected without manual intervention.
2Adaptability or versatility
If manual selection of key performance indicators is performed, then the ability to customize monitoring is improved, but the time required for setup increases
Solution Approach 1:
The system pre-establishes a comprehensive set of possible KPIs and their relationships with device types and configurations. This preliminary preparation allows the system to quickly determine appropriate KPIs for any network device without requiring time-consuming manual selection or configuration during deployment.
Solution Approach 2:
The automated KPI determination process eliminates manual setup time by having the system self-configure monitoring parameters based on device information. Operators receive ready-to-use KPI recommendations that are automatically tailored to their specific network devices, significantly reducing setup time while maintaining customization capability.
3Quantity of substance
If all operational information is collected for network devices, then the completeness of data is improved, but the amount of irrelevant information increases
Solution Approach 1:
The system extracts and separates relevant operational information from irrelevant data by filtering KPIs based on device type and configuration. This extraction process identifies and isolates only the KPIs that are actually applicable to each network device, removing unnecessary information while preserving complete and accurate device performance data.
Solution Approach 2:
The system applies different KPI selection criteria to different network devices based on their specific characteristics. Each device receives customized KPI recommendations tailored to its type, configuration, and role, ensuring that only locally relevant information is collected and monitored, thereby reducing irrelevant data volume while maintaining completeness for each specific device.
Data Source
AI summary
Presented herein are embodiments for quickly identifying and recommending key performance indicators (KPIs) for network devices based on the type of network device and/or role of the device. The type or configuration of the network device may be obtained and compared to the capabilities of the network device. Operational or performance information of the network device, represented by strings, may be obtained based on the configuration information. Operational information that is not relevant to the configuration of the network device may be filtered out. The remaining operational information may be ranked as KPIs based on a relevance of the operational information with respect to the configuration information.