Router Policy Automation via Meta-Administrator Interface
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Solution Overview
Problem
The existing process for developing and implementing network policies is time-consuming, costly, and error-prone, requiring significant resources and resulting in policies becoming outdated quickly due to rapid network evolution.
Innovation Solution
A method and system that utilize a meta-administrator interface to specify policy rules, automatically generating an administrator interface for inputting rule data, which is then stored in data structures associated with a router, thereby bypassing traditional development and implementation stages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional policy development cycle is used, then policies can be developed with detailed engineering review and testing, but the development time becomes excessively long and policies become outdated quickly
Solution Approach 1:
The system enables self-service policy generation where administrators can directly create policies through automated interface generation and template-based rule creation, eliminating the need for lengthy multi-stage development cycles involving multiple teams. The automated interface generator creates ready-to-use policy configurations that can be immediately deployed after administrative review.
Solution Approach 2:
Policy templates and interface definitions are prepared in advance, allowing the system to generate complete policy configurations rapidly when needed. The metadata-driven approach pre-defines valid policy structures, constraints, and interfaces, so that when policy creation is required, the system can immediately instantiate proper configurations without lengthy design phases.
2Reliability
If traditional multi-stage development process is used, then policies can be thoroughly tested and validated, but the cost and complexity of implementation increase significantly
Solution Approach 1:
The automated interface generator serves multiple functions: it generates administrator interfaces, creates policy templates, validates policy structures, and prepares configuration data for deployment. This single unified system replaces multiple separate development tools and processes, reducing implementation complexity while maintaining validation quality.
Solution Approach 2:
The system introduces an automated interface generator as an intermediary between policy requirements and implementation. This intermediary automatically translates high-level policy definitions into complete, validated configurations, eliminating the need for manual coding and reducing the complexity of the implementation process while maintaining thorough validation.
3Reliability
If manual policy development with multiple review stages is used, then policies can be carefully crafted, but the error rate increases due to multiple handoffs
Solution Approach 1:
The system performs self-validation of policy configurations through automated interface generation and template-based rule creation. The metadata-driven approach includes built-in constraints and validation logic that automatically detect and prevent errors, eliminating the need for multiple manual review stages and reducing errors caused by human handoffs.
Solution Approach 2:
The automated interface generator provides immediate feedback on policy configuration validity, constraint satisfaction, and potential errors. This real-time validation allows administrators to correct issues during policy creation rather than discovering errors after deployment, significantly reducing the error rate while maintaining policy quality.
4Reliability
If traditional development cycle is used, then policies can be developed with comprehensive engineering input, but the number of required professionals and resources increases
Solution Approach 1:
The system enables administrators to independently create and deploy policies using automated interface generation and template-based configurations, eliminating the need for large teams of engineers, designers, and testers. The automated validation and generation processes replace manual work that would otherwise require multiple specialized professionals.
Solution Approach 2:
The system replaces the mechanical process of manual policy development involving multiple professionals with an automated computational system. The interface generator and template engine automatically perform tasks that would otherwise require human engineers, designers, and validators, significantly reducing the number of professionals needed while maintaining policy robustness through automated validation.
Data Source
AI summary
Methods, systems, and computer readable media for implementing a policy for a router are disclosed. One method includes providing a meta administrator interface configured to facilitate the specification of one or more rules that form a policy definition. The method further includes automatically generating, based on the policy definition, an administrator interface for inputting rule data associated with the policy definition. Even further, the method includes storing the input rule data in one or more data structures associated with a router.