Service Mesh Traffic Capture for Asynchronous Error Simulation
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Solution Overview
Problem
In complex distributed systems with asynchronous relationships between services, it is challenging to identify and address errors in transactions across multiple services, as traditional tools lack the capability to simulate and reproduce complex invocation sequences effectively.
Innovation Solution
A computer-implemented method for a service mesh that involves identifying errors in transactions with asynchronous relationships, recording and modifying user invocation data to correct errors, and simulating the execution of modified data to confirm error correction, thereby allowing for the reproduction of complex invocation sequences from production environments to simulation environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional tools are used to monitor distributed systems, then normal workloads can be monitored, but complex invocation sequences with asynchronous relationships cannot be effectively reproduced or simulated
Solution Approach 1:
The patent creates a simulation environment that copies the production environment's service mesh architecture, allowing complex invocation sequences to be reproduced. Traffic capture agents in the simulation environment replicate the behavior of production services, enabling faithful reproduction of asynchronous relationships and transaction flows without affecting the actual production system.
Solution Approach 2:
The patent introduces a traffic capture agent as an intermediary component that sits between the production environment and the simulation environment. This agent captures traffic data from production and injects it into the simulation environment, mediating the transfer of complex invocation sequences while maintaining isolation between production and simulation.
2Measurement precision
If traffic capture is performed in production environment, then errors can be identified, but normal workloads will be impacted
Solution Approach 1:
Instead of capturing traffic directly from the production environment, the patent creates a copy of the traffic flow in a separate simulation environment. The traffic capture agent replicates production traffic patterns and injects them into the simulation environment, allowing error detection through simulation without interfering with production workload performance.
Solution Approach 2:
The patent segments the traffic monitoring function into two separate environments: production and simulation. The traffic capture agent operates in the simulation environment to handle error detection, while the production environment continues to handle normal workloads without interference. This segmentation isolates the measurement activity from the production system.
3Measurement precision
If sampling rate is increased to capture all traffic for error analysis, then error detection improves, but system overhead increases
Solution Approach 1:
The patent extracts the traffic capture and analysis function from the production environment and places it in a separate simulation environment. The traffic capture agent extracts traffic patterns from production and processes them in the simulation environment, allowing full-rate capture for error detection without imposing overhead on the production system resources.
Data Source
AI summary
A computer-implemented method for a service mesh to simulate and address a situation in which there are several transactions among services with an asynchronous relationship between the services is provided. The computer-implemented method includes identifying that the situation occurs with a response provided to a user upon a user invocation of one of the services, analyzing the situation to determine that the asynchronous relationship between the services caused an error in at least one of the several transactions, recording data of a next user invocation of the one of the services, modifying the data of the next user invocation of the one of the services to correct the error and to thereby generate modified data, simulating an execution of the next user invocation of the service using the modified data and confirming that the modified data corrects the error based on results of the simulating.