Abstract: With the in-depth digital transformation of enterprises, more and more enterprises have migrated their core businesses to the cloud. While the elastic scaling and "pay-as-you-go" features of cloud computing have significantly improved operational efficiency, risks such as natural disasters, cyberattacks, human operational errors, and hardware failures have also intensified. Once these risks occur, they will lead to cloud-based business interruptions and the loss of critical data, causing huge economic losses to enterprises. Therefore, Cloud Disaster Recovery（CDR）technology has become a core link in ensuring the stability of enterprises' information technology architectures and business continuity. CDR technology has gone through multiple stages of evolution, from early high-cost on-premises tape backups and self-built data centers, to gradual exploration combined with virtualization technology, and now to diversified disaster recovery solutions based on cloud computing. It has derived various business types such as cloud-based, hybrid cloud, and multi-cloud, with obvious differences in technical index requirements such as RTO (Recovery Time Objective) and RPO (Recovery Point Objective) among different types. However, systematic sorting and integrated research on the CDR technology system in the current industry are still relatively insufficient. Based on this, this paper integrates the current development status of CDR, the research first sorts out the key nodes in its development history, clarifies the core concepts of backup and disaster tolerance, and typical application scenarios in finance, manufacturing, medical care, etc. Then, it focuses on the "two locations and three centers" architecture, a mainstream architecture, to deeply analyze the research progress of key technologies such as data synchronization, distributed consistency verification, and fault detection. Finally, it summarizes existing challenges such as heterogeneous cloud resource synchronization and cluster split-brain recovery, and points out future research directions such as intelligent fault prediction using AI, providing technical references for enterprises to formulate disaster recovery and cloud migration strategies.

摘要： 随着企业数字化转型深入，越来越多企业将核心业务迁移至云端，云计算的弹性扩缩容与 “随买随用” 特性显著提升运营效率，但自然灾害、网络攻击、人为操作失误、硬件故障等风险也随之加剧，一旦发生将导致云上业务中断与关键数据丢失，给企业造成巨大经济损失，因此云灾备技术已成为保障企业信息技术架构稳定、确保业务连续性的核心环节。云灾备技术历经多阶段演进，从早期高成本的本地磁带备份与自建数据中心，逐步发展到结合虚拟化技术的初步探索，再到如今依托云计算实现的多元化灾备方案，衍生出云上、混合云、多云等多种业务类型，不同类型在RPO(Recovery Point Objective, 恢复点目标)、RTO(Recovery Time Objective, 恢复时间目标)等技术指标要求上存在明显差异。然而，当前行业内针对云灾备技术体系的系统性梳理与整合研究仍较为缺乏。基于此，本文综合现阶段云灾备发展现状，研究分析其发展历程中的关键节点、明确备份与容灾的核心概念及金融、制造、医疗等典型应用场景，再聚焦两地三中心这一主流云灾备架构，深入分析数据同步、分布式一致性校验、故障检测等关键技术的研究进展，最后总结异构云资源同步、集群脑裂恢复等现存挑战，并指出结合AI实现智能故障预测等未来研究方向，为企业制定容灾上云策略提供技术参考。