Intelligent Quality Governance Framework and Adaptive Verification Model in Cloud Integration Scenarios

Abstract

The background of cloud integration is a huge system composed of numerous distributed services. The relationship between data flow and service invocation is constantly changing dynamically, thus making quality risks highly concealed and contagious. However, the traditional approach relies on manual analysis and static scanning to assess quality, which is difficult to meet the complex environmental requirements of various types, large quantities, high data density and frequent changes. For this purpose, this paper proposes the Intelligent Quality Governance Framework (IQGF), which establishes a representation system of quality measurement by integrating monitoring data, logs and call chains. At the same time, a self-regulating inspection model is proposed, which can automatically adjust the inspection range and plan according to the real-time risk information to achieve dynamic detection based on the operation status. This method shifts quality management from passive detection to active management, providing reliable quality assurance for large-scale cloud integration systems.