Universal Adapter for Cloud Resource Discovery
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Solution Overview
Problem
Existing performance monitoring tools in computing environments require multiple adapters and code changes for each endpoint, making it inefficient to discover new resources or metrics, as API calls and responses differ significantly across endpoints.
Innovation Solution
A management node with a data collection unit that retrieves resource definition data, generates an adapter instance, and populates a resource model by parsing API responses, allowing for generic communication with multiple endpoints and eliminating the need for multiple adapters and code changes through resource definition data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple adapters are used for different endpoints, then communication with various endpoints is achieved, but device complexity increases and ease of operation deteriorates
Solution Approach 1:
The patent implements a universal adapter that can communicate with multiple different endpoints (cloud infrastructure providers, SaaS providers, on-premise systems) through a single unified interface. This universal adapter replaces the need for multiple specialized adapters, thereby reducing device complexity while maintaining adaptability across different endpoint types.
Solution Approach 2:
The patent introduces an intermediary component (the universal adapter with standardized interface) that mediates between the monitoring system and various endpoints. This intermediary translates and standardizes communications from different endpoint types, allowing the core system to interact with all endpoints through a common protocol without requiring endpoint-specific adapters.
2Adaptability or versatility
If code changes are made for each endpoint, then endpoint-specific functionality is achieved, but ease of manufacture deteriorates and productivity decreases
Solution Approach 1:
The patent uses configuration files that serve as templates or copies defining endpoint-specific parameters, resource models, and metric definitions. Instead of modifying code for each endpoint, the system loads and instantiates appropriate configuration files, allowing endpoint-specific functionality to be achieved through data configuration rather than code changes, thereby improving productivity.
Solution Approach 2:
The patent implements a dynamic configuration system where the adapter can load different configuration files based on the endpoint type. This allows the system to adapt its behavior, resource models, and metric collection parameters dynamically at runtime without requiring code recompilation or modification, enabling flexible endpoint-specific functionality while maintaining high productivity.
3Adaptability or versatility
If multiple adapters are maintained, then endpoint diversity is supported, but ease of repair worsens and loss of time increases
Solution Approach 1:
The patent merges multiple endpoint-specific adapter functionalities into a single universal adapter implementation. By consolidating the adapter logic into one unified component that handles multiple endpoint types through configuration, the system reduces the number of separate adapters that need to be maintained, updated, and debugged, thereby improving ease of repair while maintaining support for endpoint diversity.
Data Source
AI summary
In one example, a computer implemented method may include retrieving resource definition data corresponding to an endpoint. The resource definition data includes adapter information and resource type information. Further, an adapter instance may be generated using the adapter information to establish communication with the endpoint. Furthermore, an API response may be obtained, via the adapter instance, from the endpoint by querying the endpoint using an API call. Further, the API response may be parsed. Further, a resource model corresponding to the resource definition data may be populated using the parsed API response. The resource model may include resource information and associated metric information corresponding to a resource type in the resource type information. Furthermore, a resource and/or metric data associated with the resource may be determined using the populated resource model. The resource may be associated with an application being executed in the endpoint.