Proactive Microservice Migration via CTMC Failure Analysis
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Solution Overview
Problem
Existing server failure management techniques do not proactively migrate microservices from servers likely to fail, leading to potential downtime and inefficiencies in maintaining service availability.
Innovation Solution
A method that utilizes a directed acyclic graph (DAG) and Continuous Time Markov Chain (CTMC) models to identify vulnerable execution paths in a microservice-based application, computing weights and failure probabilities to proactively migrate microservices from servers with high failure risks to more reliable servers before actual failure occurs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If microservices are migrated proactively from servers with high failure probability, then service availability and reliability are improved, but system complexity and computational overhead increase due to CTMC modeling and path analysis
Solution Approach 1:
The patent performs preliminary analysis by building CTMC models for servers and identifying vulnerable execution paths before failures occur. Failure probabilities are computed in advance, and microservices are proactively migrated from high-risk servers to low-risk servers, preventing service disruptions rather than reacting to them.
Solution Approach 2:
The patent introduces a migration management system as an intermediary that orchestrates the complex interactions between multiple servers, microservices, and execution paths. This intermediary component manages the CTMC modeling, vulnerability assessment, and migration decision-making, isolating the complexity from the core microservice operations.
2Measurement precision
If comprehensive CTMC modeling is performed for all servers to identify vulnerable paths, then migration accuracy improves, but computational time and processing resources increase
Solution Approach 1:
The patent applies local quality by focusing computational resources on servers and execution paths that are most critical to service availability. Instead of uniformly analyzing all servers with equal depth, the system identifies vulnerable paths and concentrates detailed CTMC modeling on high-impact areas, optimizing the balance between precision and computational cost.
Data Source
AI summary
A method, computer program product, and computer system for proactive microservice migration prior to server failure. A directed acyclic graph representing a microservice-based application and including nodes representing microservices is received. Multiple execution paths passing through the nodes are identified. Multiple unique servers configured to provide the microservices are identified. A Continuous Time Markov Chain model generated for each unique server is characterized by a failure rate and a repair rate of each unique server. A weight is computed for each unique server. A failure probability of each execution path is computed in dependence on the weight, and both failure and repair rate, of the unique servers. One or more vulnerable paths are selected from the multiple execution paths, wherein the failure probability of each selected vulnerable path exceeds a specified failure probability threshold. All microservices on at least one vulnerable path are migrated to one or more other servers.