Microservice Database Access Pattern Recommendation
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Solution Overview
Problem
Current microservices architectures lack automated solutions to recommend and implement optimal database access patterns, leading to potential performance degradation due to manual effort and lack of analysis for appropriate patterns based on transaction types and functionality.
Innovation Solution
A computer-implemented method that generates and implements database access patterns for microservices by analyzing field access graphs and user inputs, recommending CRUD or CQRS patterns based on transaction loads and database profiles to optimize performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual analysis and selection of database access patterns is performed, then flexibility and adaptability to specific microservice needs is improved, but development time and manual effort increase
Solution Approach 1:
The system performs self-service by automatically analyzing field access graphs and transaction patterns to select appropriate database access patterns without requiring manual intervention. The computer-generated recommendations are implemented automatically, eliminating the need for developers to manually analyze access patterns while maintaining adaptability to specific microservice needs through automated pattern recognition.
Solution Approach 2:
The system changes parameters by transforming manual analysis into automated parameter extraction from field access graphs. It analyzes transaction types, read/write ratios, and field access patterns to automatically determine optimal database access patterns, converting what was previously a manual decision-making process into an automated parameter-based selection system.
2Loss of time
If automated database access pattern recommendation is implemented, then development time is reduced, but system complexity increases
Solution Approach 1:
The system introduces an intermediary layer in the form of a computer-generated recommendation mechanism that sits between the microservice code and the database access layer. This intermediary automatically analyzes field access graphs and generates appropriate database access pattern recommendations, adding complexity only at this intermediate layer while keeping the core microservice architecture simple.
Solution Approach 2:
The system replaces the mechanical manual analysis process with an automated computer-based system. Instead of developers manually examining access patterns, the system uses automated algorithms to analyze field access graphs and generate recommendations, substituting human cognitive processing with computational automation.
3Ease of manufacture
If manual database access pattern selection is used, then implementation simplicity is maintained, but data access performance optimization is insufficient
Solution Approach 1:
The system implements feedback by analyzing actual field access patterns and transaction types to generate database access pattern recommendations. It continuously monitors and analyzes access graphs to provide feedback on optimal patterns, enabling performance optimization based on real access behavior rather than assumptions.
Solution Approach 2:
The system performs self-service optimization by automatically analyzing its own access patterns and generating recommendations for improvement. It monitors field access graphs and transaction types to identify optimal database access patterns, enabling the system to optimize its own performance without external intervention.
Data Source
AI summary
Recommending database access patterns for transactions in microservices is provided. A recommendation of a particular database access pattern to improve access by transactions to data in fields of tables in a database corresponding to a microservice is generated based on analysis of field access graphs for the tables accessed by the transactions. The recommendation of the particular database access pattern is output. The particular database access pattern is implemented to improve access by the transactions to the data in the fields of the tables in the database corresponding to the microservice to improve performance of the microservice based on user input and read view implementation guidance.