Resource Abstraction Layer for Metric Data Linking
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Solution Overview
Problem
Conventional database architectures face inefficiencies in monitoring and managing granular resources such as disks, processors, and web pages due to high memory overhead and data intensity, particularly when tracking configuration items at a detailed level.
Innovation Solution
A resource abstraction layer is introduced, allowing resources to be linked to configuration items for metric tracking without requiring full allocation and tracking as configuration items, thereby reducing memory usage and improving query performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If granular resources are tracked as configuration items in the database, then measurement precision and data granularity are improved, but memory usage and query performance deteriorate
Solution Approach 1:
The patent segments the configuration item tracking system into two parts: coarse-grained configuration items remain in the database, while fine-grained resources are tracked separately through metric bindings. This segmentation allows precise resource monitoring without storing all granular details in the main configuration tables, reducing memory overhead while maintaining measurement precision.
Solution Approach 2:
The patent introduces a new dimension for resource tracking by creating metric bindings that associate resources with configuration items through metric data. Instead of expanding the configuration item hierarchy to include all granular resources, the system adds a metric binding layer that provides fine-grained tracking without increasing database memory requirements.
2Measurement precision
If granular resources are tracked as configuration items in the database, then measurement precision and data granularity are improved, but query performance deteriorates
Solution Approach 1:
The patent extracts granular resource tracking from the configuration item database structure and places it in the metric binding system. By taking out detailed resource information from the main configuration tables and storing it as separate metric data with bindings, the system maintains precise resource monitoring capabilities while improving query performance by reducing database table complexity and join operations.
Solution Approach 2:
The patent introduces metric bindings as an intermediary layer between configuration items and granular resources. This intermediary allows the system to track detailed resource metrics without requiring the configuration item database to directly store or manage all granular resource details, thereby maintaining measurement precision while improving query efficiency through reduced database complexity.
3Measurement precision
If configuration items are tracked at detailed levels, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the tracking system into configuration items for high-level asset management and metric bindings for detailed resource monitoring. This segmentation simplifies the database structure by keeping configuration tables focused on asset metadata while delegating detailed resource tracking to the metric binding system, thereby reducing device complexity while maintaining measurement precision.
Solution Approach 2:
The patent makes the metric binding system multi-functional by using it to track both resource associations and detailed metrics. This universal approach allows the system to achieve detailed measurement precision without creating separate complex database structures for each type of granular tracking, thereby reducing overall device complexity while maintaining high measurement precision.
Data Source
AI summary
The present approach relates generally to systems and methods for outputting metric data from resources with a database accessible by a client instance. The client instance is hosted by one or more data centers and accessible by one or more remote client networks. In accordance with the present approach, a request to track metric data related to a resource is received. Further, a configuration item (CI) is retrieved from a database accessible by the client instance based at least in part on data associated with the request. Further, a type of CI is identified. Even further, a resource type associated with the type of the CI is identified based at least in part on a resource abstraction layer accessible by the client instance. Further still, the resource type is linked to the resource table and metric data associated with the resource is outputted.