API Domain Detection via Consumer Usage Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing API management systems face challenges in automatically detecting which APIs are consumed together to define useful API domains, relying on manual definitions by providers without considering consumer usage patterns.
Innovation Solution
An API management system that automatically detects API domains by analyzing consumer registration and runtime data, using complex event processing techniques to identify groups of APIs invoked together, and incorporates an approval process involving both providers and consumers for domain proposals and extensions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If API domains are manually defined by providers, then provider control and governance are maintained, but the system cannot automatically detect useful API domain groupings based on consumer usage patterns
Solution Approach 1:
The system enables self-service by automatically detecting API domains based on consumer registration and runtime data without requiring manual definition by providers. The API management system autonomously analyzes consumption patterns, identifies related APIs, and proposes domains that reflect actual usage behavior, allowing the system to serve itself in the domain detection process.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring consumer registration data and runtime API call data, using this information to detect and refine API domain groupings. The detected domains are then fed back into the system for governance decisions, creating a closed-loop process that adapts to actual consumption patterns over time.
2Measurement precision
If API domains are defined based on consumer usage patterns, then relevant API groupings are identified, but provider approval and governance are compromised
Solution Approach 1:
The system uses feedback loops where consumer usage data drives automatic domain detection, and provider approval processes validate these detections. The feedback mechanism ensures that detected domains reflect actual usage patterns while maintaining provider oversight through explicit approval requirements before domains are finalized.
Solution Approach 2:
The system performs preliminary actions by automatically detecting and proposing API domains based on usage patterns before final governance decisions are made. This preliminary detection phase identifies potential domains that can then be reviewed and approved by providers, ensuring both accuracy in identification and maintenance of governance control.
3Productivity
If manual API domain definition is used, then governance is simplified, but revenue opportunities are lost due to inability to identify bundled API consumption patterns
Solution Approach 1:
The system performs self-service by automatically analyzing consumer registration data and runtime API call data to detect usage patterns and identify revenue opportunities. The API management system autonomously processes consumption data, identifies related APIs that are commonly used together, and proposes bundled domains that can enable new revenue streams without requiring manual analysis.
Solution Approach 2:
The system replaces manual mechanical processes of domain definition with automated computational analysis. Instead of providers manually identifying useful API groupings, the system uses algorithms that process consumption data, detect patterns, and generate domain proposals, substituting human expertise with automated intelligence that scales efficiently.
4Measurement precision
If automated domain detection is implemented, then API domain identification is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing consumer registration data and runtime API call data in a structured format. This preparation allows the automated detection process to query and analyze existing data efficiently rather than collecting and processing data in real-time, reducing the time required for domain detection while maintaining precision.
Solution Approach 2:
The system applies partial action by focusing the detection algorithm on specific criteria that define meaningful API groupings, such as temporal proximity and functional relatedness, rather than analyzing all possible API combinations. This selective approach maintains detection precision while significantly reducing computational overhead and processing time.
Data Source
AI summary
Certain example embodiments described herein relate to an application programming interface (API) management system and/or method that automatically detects API domains, e.g., by analyzing consumer registration and runtime data, while also allowing API providers to provide approval for proposed detected domains and/or continued governance. The technology set forth herein not only provides an automatic detection mechanism, but also provides the capability of full management/control, while also allowing API producers to dynamically expand or otherwise modify their API domain offerings based on usage, etc. This dynamic process can be fully or partially automated and is efficient.