Microservices Task Distribution via Correlated Data
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Solution Overview
Problem
In microservices applications, maintaining data consistency and accuracy across different data formats and computing resources is challenging, leading to reduced accuracy and inefficient task distribution, which affects overall application performance.
Innovation Solution
A microservices platform that correlates data items with a unique identifier and determines task distribution based on computing resource metrics, using a service layer, persistence adaptation layer, and persistence layer to ensure data consistency and efficient resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is transmitted to multiple data stores with different formats, then data consistency is improved, but device complexity increases
Solution Approach 1:
The patent introduces a service layer as an intermediary between the data source and multiple data stores. This service layer receives data in a first format, transforms it into multiple different formats, and distributes it to various data stores. The service layer acts as a mediator that handles format conversion and data routing, thereby maintaining data consistency across heterogeneous stores without increasing the complexity of individual data stores or the data source.
Solution Approach 2:
The patent segments the data processing system into distinct functional layers: a data source layer, a service layer for transformation and routing, and multiple data store layers with different formats. This segmentation allows each component to specialize in specific tasks - the service layer handles format conversion while data stores focus on storage, thereby maintaining data consistency without requiring each component to handle all format types.
2Productivity
If tasks are distributed without considering computing resource metrics, then task distribution speed is improved, but productivity decreases
Solution Approach 1:
The patent implements a feedback mechanism where the service layer receives computing resource metrics from available computing resources, uses this feedback information to make informed task distribution decisions, and continuously monitors task execution results. This feedback loop enables the system to distribute tasks to optimal resources based on real-time resource availability and performance data, thereby improving productivity while minimizing distribution time through intelligent decision-making.
Solution Approach 2:
The patent makes the task distribution process dynamic by continuously monitoring computing resource metrics and adapting task assignment decisions in real-time. Rather than using static distribution rules, the system dynamically adjusts task routing based on current resource availability, performance characteristics, and task requirements, thereby optimizing productivity without significant time loss.
Data Source
AI summary
A system includes one or more devices to receive a first set of data. The system transmits the first set of data to a first data store for storage. The first data store is of a first data format type. The system transmits the first set of data to a node of a plurality of nodes. The node to perform an action on the first set of data and a second set of data to generate a third set of data. The node to transmit the third set of data to a third data store. The third data store being of a third data format type that is different than the first data format type and the second data format type. The system transmits the third set of data from the third data store to the first data store for reporting.