[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC)：2024-12-30。"],[[["This principle focuses on testing data recovery processes to ensure systems can recover from data loss or corruption, caused by issues like software bugs or natural disasters."],["Successful data recovery testing is determined by data integrity, recovery time objective (RTO), and recovery point objective (RPO), and includes verification of the entire application stack and all the critical infrastructure services with the restored data."],["Regular and frequent backups are crucial to minimize data loss and meet RPO targets, and the frequency should align with the defined RPO, using tools like Cloud Storage, Cloud SQL automated backups, or Spanner backups."],["It is important to verify that backups contain consistent and usable snapshots, and test restorations in non-production environments by regularly simulating data recovery scenarios."],["Setting a clear RPO based on business requirements and monitoring it, along with monitoring backup health and using tools such as Google Cloud Backup and DR service, are also needed."]]],[]]
