在服务更新期间保证流分析作业可靠性Guarantee Stream Analytics job reliability during service updates

作为完全托管服务的一部分的是快速引入新服务功能和改进的能力。Part of being a fully managed service is the capability to introduce new service functionality and improvements at a rapid pace. 因此,流分析可以每周(或更频繁地)进行服务更新部署。As a result, Stream Analytics can have a service update deploy on a weekly (or more frequent) basis. 无论进行多少次测试,由于引入了 bug,仍存在现有正在运行的作业可能会中断的风险。No matter how much testing is done there is still a risk that an existing, running job may break due to the introduction of a bug. 如果运行的是任务关键型作业,则需要避免这些风险。If you are running mission critical jobs, these risks need to be avoided. 可以遵循 Azure 的配对区域 模型来降低此风险。You can reduce this risk by following Azure's paired region model.

Azure 配对区域如何解决此问题?How do Azure paired regions address this concern?

流分析可以保证在单独的批处理中更新配对区域中的作业。Stream Analytics guarantees jobs in paired regions are updated in separate batches. 因此,在更新之间具有足够的时间间隔来识别潜在问题并修复它们。As a result there is a sufficient time gap between the updates to identify potential issues and remediate them.

同一组中多个区域中的部署可能会同时进行。Deployments in multiple regions in the same group may occur at the same time.

可用性和配对区域 一文具有关于配对区域的最新信息。The article on availability and paired regions has the most up-to-date information on which regions are paired.

建议将相同的作业部署到这两个配对区域。It is recommended to deploy identical jobs to both paired regions. 然后,应该监视这些作业,以便在发生意外情况时收到通知。You should then monitor these jobs to get notified when something unexpected happens. 如果其中一个作业在流分析服务更新后以失败状态结束,则可以联系客户支持以帮助确定根本原因。If one of these jobs ends up in a Failed state after a Stream Analytics service update, you can contact customer support to help identify the root cause. 还应将任何下游使用者故障转移到正常作业输出。You should also fail over any downstream consumers to the healthy job output.

后续步骤Next steps