Microservice Parameter Reduction via Profile-Based Interception
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In microservice architectures, transferring large amounts of parameter data between services can consume network, memory, and CPU resources, leading to increased overhead and performance degradation, especially when target microservices perform machine learning processes.
Innovation Solution
Implement a vertical reduction interceptor that receives a data reduction condition from a vertical reduction database based on user profiles to intercept and reduce the dimensionality of parameter data before transmission to target microservices, optimizing data passage in a service mesh.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If large amounts of parameter data are transferred between microservices, then data completeness is improved, but network, memory, and CPU resources are consumed leading to performance degradation
Solution Approach 1:
The patent extracts only the necessary parameters from the complete parameter data before transmission to the target microservice. The vertical reduction interceptor identifies and extracts only the parameters that the target microservice actually needs based on its profile, eliminating unnecessary data transfer while maintaining data completeness for the receiving service.
Solution Approach 2:
The patent applies local quality by customizing the parameter reduction strategy according to the specific needs of each target microservice. Each microservice has a profile that defines its parameter requirements, allowing the system to tailor the data transmission to match the local quality needs of individual services rather than using a uniform approach.
2Loss of energy
If parameter data dimensionality is reduced, then resource consumption is minimized, but data processing capability may be compromised
Solution Approach 1:
The patent performs preliminary action by pre-defining the parameter reduction rules and intercepting data transmission before it reaches the target microservice. The vertical reduction interceptor applies pre-established reduction strategies based on microservice profiles to ensure that only necessary parameters are transmitted, maintaining data processing capability while reducing resource consumption.
Solution Approach 2:
The system implements feedback mechanisms where the vertical reduction interceptor monitors and adjusts parameter selection based on the target microservice's profile and actual needs. This feedback loop ensures that the reduced parameter set maintains sufficient information for reliable data processing while optimizing resource usage.
3Productivity
If a vertical reduction interceptor is implemented, then data transmission is optimized, but system complexity increases
Solution Approach 1:
The patent introduces a vertical reduction interceptor as an intermediary component that mediates between the data sender and the target microservice. This interceptor handles the complexity of parameter reduction independently, allowing the main system to benefit from optimized data transmission without directly managing the reduction logic in each service.
Solution Approach 2:
The vertical reduction interceptor serves multiple functions: it intercepts data transmissions, determines target microservices based on profiles, applies parameter reduction strategies, and optimizes data routing. By consolidating these functions into a single multi-functional component, the system achieves data transmission optimization without proportionally increasing overall system complexity.
Data Source
AI summary
A method of optimizing parameter data passing between microservices in a service mesh includes receiving, by a vertical reduction interceptor, a data reduction condition of a target microservice. The data reduction condition is provided by a vertical reduction database. The method further includes intercepting, by the vertical reduction interceptor, a sender microservice that sends the parameter data to the target microservice and reducing, upon identifying that the parameter data meets the data reduction condition of the target microservice, a dimension of the parameter data based on the data reduction condition. The parameter data is sent to the target microservice. The data reduction condition is based on a specified user profile.