Natural Language Network Configuration via ML Translation
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Solution Overview
Problem
Configuring communications networks, particularly Content Delivery Networks (CDNs), is a tedious and technically challenging process due to their complexity and variability, which has hindered automation and required manual, labor-intensive methods despite the desire for flexibility and extensibility.
Innovation Solution
A natural language interface using machine learning and artificial intelligence models to generate network configurations from user inputs, translating natural language into structured data that defines network behaviors, such as caching, request handling, and security rules, facilitating automated configuration and validation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual configuration methods are used to maintain flexibility and extensibility, then network operators can customize configurations to suit business needs, but the process becomes tedious and labor-intensive
Solution Approach 1:
The patent introduces natural language as an intermediary between the user and the complex network configuration system. Users express their intent in plain language, and the system automatically translates this into detailed configuration parameters, eliminating the need for users to directly manipulate complex technical settings while preserving full configurability
Solution Approach 2:
The system enables self-service configuration by automatically generating, validating, and applying configuration settings based on natural language inputs. The network configuration system performs self-configuration tasks without requiring manual intervention in complex technical parameters, reducing labor-intensive operations while maintaining adaptability
2Adaptability or versatility
If comprehensive configuration options are provided to meet diverse business needs, then network extensibility is enhanced, but system complexity increases
Solution Approach 1:
Natural language serves as an intermediary layer that abstracts away the complexity of extensive configuration options. The system interprets simple natural language statements and automatically maps them to the appropriate complex configuration parameters, allowing full extensibility without exposing users to configuration complexity
Solution Approach 2:
The natural language interface acts as a universal input mechanism that can handle diverse configuration needs through a single, simple interface. Rather than providing separate complex interfaces for different configuration scenarios, the system uses one unified natural language interface to manage all configuration aspects, reducing overall system complexity while maintaining extensibility
Data Source
AI summary
Described herein are various examples of techniques for generating a network configuration and configuring a network based on said configuration. In some embodiments, there is provided a method comprising receiving a natural language input describing a desired behavior of a network and generating a network configuration based at least in part in the natural language input. Generating the network configuration may comprise generating structured data indicating one or more rules for the network to implement the desired behavior. The method may further comprise configuring the network based on the structured data indicating the one or more rules to implement the desired behavior of the network.