Research on the Automated Deployment Inspection System for Business Systems Based on Cloud-Native Architecture

Gated Recurrent Yum Actor-Critic (GRYAC) architecture innovatively integrates cloud native technology, gated cycle unit (GRU) neural network and Actor-Critic algorithm, providing a powerful tool for the research of online automated inspection system of business systems based on cloud native architecture. The GRYAC uses the GRU to capture the time series features of various indicators in the business system, and automatically adjusts the check policies to optimize the robustness and availability of the system through the reinforcement learning strategy of the Actor-Critic algorithm. We have built a system architecture based on IaaS, PaaS, SaaS three-layer cloud service model to provide comprehensive support for the deployment, operation and application of automated inspection system. Finally, through comparative experiments and analysis between the model algorithm and the neural network, this paper verifies that the proposed cloud-native architect-based online automated inspection system not only has significant advantages in accuracy, decision science and overall efficiency improvement, but also has significant improvements in accuracy, recall rate, accuracy rate and F1 score. The results show that the automatic inspection system can effectively solve the complexity and uncertainty problems that the traditional inspection methods are difficult to deal with, and it also proves the feasibility of the automatic inspection model in the online business system.