# US 2023/0065718 A1 · Inspecting network performance at diagnosis points

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- Number: US 2023/0065718 A1
- Document ID: US20230065718A1
- Status: Published application
- Kind: A1
- Application number: 17/894,121
- Filed: 2022-08-23
- Published: 2023-03-02
- Earliest claimed: 2017-10-02
- Assignees: salesforce.com, inc.
- Applicants: Salesforce.com, Inc.
- Inventors: Shauli Gal; Satish Raghunath; Kartikeya Chandrayana; Gabriel Tavridis; Kevin Wang
- Web page: https://patentgrep.com/patent/US20230065718A1

## CPC

- H04L 43/16: Threshold monitoring
- H04L 41/046: comprising network management agents or mobile agents therefor
- H04L 41/0816: the condition being an adaptation, e.g. in response to network events
- H04L 41/0894: Policy-based network configuration management
- H04L 43/04: Processing captured monitoring data, e.g. for logfile generation
- H04L 43/12: Network monitoring probes
- H04L 41/064: {involving time analysis}
- H04L 41/0895: Configuration of virtualised networks or elements, e.g. virtualised network function or OpenFlow elements
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)

## Abstract

A data-driven approach to network performance diagnosis and root-cause analysis is presented. By collecting and aggregating data attribute values across multiple components of a content delivery system and comparing against baselines for points of inspection, network performance diagnosis and root-cause analysis may be prioritized based on impact on content delivery. Recommended courses of action may be determined and provided based on the tracked network performance analysis at diagnosis points.

## Claims

### Claim 1

A method, comprising:
determining a plurality of diagnosis points associated with one or more components of a content delivery system;
periodically monitoring data associated with one or more diagnosis points in the plurality of diagnosis points by generating a metric associated with the one or more diagnosis points based on the monitored data, wherein the metric comprises one or more data attributes associated with one or more sub-components of the component;
responsive to the metric indicating an occurrence of an anomaly associated with a diagnosis point, identifying one or more components of the content delivery system that are likely contributors to an outcome associated with the metric; and
generating a repair recommendation for a component of the one or more components based on a set of rules.