您的Cassandra群集部署失败。副本状态已更改为永久\u失败。复制副本连续2次不正常

您的Cassandra群集部署失败。副本状态已更改为永久\u失败。复制副本连续2次不正常,cassandra,cluster-computing,google-compute-engine,Cassandra,Cluster Computing,Google Compute Engine,我尝试使用Google计算引擎部署Cassandra集群,但没有成功。我试了好几次,错误总是一样的: module: DEPLOYMENT_FAILED Replica module-1234 failed with status PERMANENTLY_FAILING: Replica State changed to PERMANENTLY_FAILING. Replica was unhealthy 2 consecutive times. 遵循以下简短的故障排除指南后,日志如下所示:

我尝试使用Google计算引擎部署Cassandra集群,但没有成功。我试了好几次,错误总是一样的:

module: DEPLOYMENT_FAILED
Replica module-1234 failed with status PERMANENTLY_FAILING: Replica State
changed to PERMANENTLY_FAILING. Replica was unhealthy 2 consecutive times.
遵循以下简短的故障排除指南后,日志如下所示:

antoniogallo88_gmail_com@cassandra-coord-v8ip:/gagent/metaOutput$ tail $(ls -1tr /gagent/metaOutput/stderr.*.txt | 
tail -n 1)
Still waiting for resourceview cassandranode-4da4e to have 3 members ...
Still waiting for resourceview cassandranode-4da4e to have 3 members ...
Still waiting for resourceview cassandranode-4da4e to have 3 members ...
Still waiting for resourceview cassandranode-4da4e to have 3 members ...
Still waiting for resourceview cassandranode-4da4e to have 3 members ...
Still waiting for resourceview cassandranode-4da4e to have 3 members ...
Still waiting for resourceview cassandranode-4da4e to have 3 members ...
Still waiting for resourceview cassandranode-4da4e to have 3 members ...
Still waiting for resourceview cassandranode-4da4e to have 3 members ...
[ERROR] resourceview cassandranode-4da4e does not have 3 members after 60 attempts.
你知道怎么解决这个问题吗

谢谢


Antonio

您可以检查您选择的实例类型(以内核为单位)和集群成员的数量是否超过您正在使用的项目的cpu配额吗?还要检查磁盘容量值和总磁盘配额

您可以在控制台的计算引擎>配额下检查最大允许磁盘和CPU配额

这听起来像是配额问题,即使控制台没有出现配额错误

您可以做的另一件事是创建另一个部署,然后快速切换到实例列表页面,查找名为“Cassandra coord foo”的实例,该实例是一个管理磁盘创建的短期实例。如果在部署期间ssh连接到该节点并运行以下命令,则可能会看到磁盘或CPU配额警告:

tail -f /gagent/metaOutput/*

Chris

我想了很久,它很可能与CPU配额有关,而不是磁盘配额。检查要部署到的区域中的CPU配额是否足够。Cassandra默认情况下,n1-highmem-4实例类型需要3*4+1=13个核。如果您使用的是免费的tier优惠券,那么我认为默认情况下您只能获得8个内核。使用计费方法注册时的默认值为16核。大多数点击部署默认配置都使用这个16核配额作为指导。我也有同样的问题,在用IP地址上的配额似乎也有同样的效果。