Time Series Database Metadata Aggregation for Hybrid Cloud Resource Management
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Relational databases in traditional resource management systems prioritize data integrity and consistency, making it difficult to process data according to individual enterprise needs in hybrid cloud environments.
Innovation Solution
A method and apparatus for managing and controlling resources using a time series database, which involves acquiring metadata, aggregating it based on a configured strategy, and managing resources within the time series database to facilitate flexible and efficient data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If relational databases are used for resource management in hybrid clouds, then data integrity and consistency are maintained, but the system cannot process data differently according to individual enterprise needs
Solution Approach 1:
The patent changes the fundamental parameters of the database system by transitioning from relational database models to time series database models. This parameter change enables the system to handle different data types and query patterns while maintaining data integrity, thus resolving the contradiction between reliability and adaptability in hybrid cloud resource management
2Stability of the object's composition
If traditional resource management with relational databases is adopted, then permanent and stable data are processed effectively, but flexible data processing according to enterprise needs is difficult
Solution Approach 1:
The patent introduces dynamic capabilities to the resource management system by implementing configurable aggregation strategies and metadata-based resource identification. This allows the system to adapt its data processing behavior dynamically according to different enterprise needs while maintaining stable data storage, resolving the contradiction between stability and ease of operation
3Quantity of substance
If relational databases store complete uploaded data, then data completeness is achieved, but storage efficiency and retrieval speed for massive data are reduced
Solution Approach 1:
The patent extracts and separates metadata from complete resource data, storing only essential metadata in the time series database while maintaining complete data elsewhere. This extraction principle achieves data completeness when needed while improving storage efficiency and retrieval speed for massive data operations in hybrid cloud environments
Data Source
AI summary
A method and apparatus for managing and controlling a resource based on a time series database. The method includes: acquiring metadata of a resource; aggregating the metadata according to an aggregation strategy to obtain aggregated metadata; and managing and controlling the resource in the time series database based on the aggregated metadata. The aggregated metadata may be multiple data sets, each of which may be a type of metadata, so that massive metadata may be aggregated into the multiple sets, thereby realizing categorized storage of the metadata. In addition, the method for managing and controlling the resource is applied to the time series database.