Research And Implementation Of Container-Oriented Disaster Sensing System

Disaster recovery awareness technology constitutes a fundamental basis for ensuring the safety and security of business data.The intelligent disaster recovery perception of a business system can analyze the operating conditions of the system in real-time and provide a disaster recovery solution that maximizes the protection of the system and data security.Currently,the industry possesses relatively comprehensive monitoring tools for containers,capable of monitoring and alerting individual operating indicators of containers.However,research on awareness of containers remains limited while the perception evaluation system related to container indicators is still incomplete.Furthermore,the industry’s alarm system for container monitoring is relatively simple,lacks dynamic adaptability,and its disaster recovery mechanism requires optimization.In light of these existing issues,this paper aims to model the time series data of container operation for container scenarios and use it to generate and predict dynamic baselines,thus enabling intelligent perception analysis of container operation status.On this basis,this paper has designed a complete container disaster recovery perception evaluation system,assigning weights to each index item based on their degree of impact on disaster recovery perception and evaluating containers in a hierarchical manner.Finally,this paper configures real-time alarm rules according to the scoring information of the evaluation system for disaster recovery,providing a reliable reference for intelligent disaster recovery.The main research work and innovations of this paper are as follows:(1)This paper establishes a container awareness monitoring system that cooperates with container monitoring technologies to meet the container’s disaster recovery awareness requirements.This includes designing and implementing a disaster recovery awareness system that encompasses functions such as data collection,persistence,processing,analysis,and abnormal alarm functions.(2)An improved adaptive parameter optimization time series analysis algorithm is proposed,which generates and predicts the dynamic baseline of each index,and helps users configure disaster recovery strategies reasonably.After experimental comparison,the timing prediction algorithm of the model in this paper has shown better results in various comparison experiments of the model.(3)This paper develops a hierarchical disaster recovery perception evaluation system and configures corresponding disaster recovery alarm rules.The overall monitoring of the container is designed hierarchically according to item category and importance,and the alarm rules are configured based on the difference in frequency and severity.Through the disaster recovery perception evaluation system,the system generates quantitative results and charts the security risk information faced by container resources to assist users in intelligent container disaster recovery.