我无法创建管道。我什至无法在 AI Platform Pipelines Dashboard 上加载示例/教程，因为它似乎无法代理它需要的任何东西。
An error occurred
Error occured while trying to proxy to: ...
我查看了集群的详细信息，发现 3 个组件有错误：
Deployment metadata-grpc-deployment Does not have minimum availability
Deployment ml-pipeline Does not have minimum availability
Deployment ml-pipeline-persistenceagent Does not have minimum availability
创建集群涉及大约。在 GCP Kubernetes Engine 中单击 3 次，所以我认为我没有搞砸这一步。
任何人都知道如何实现“最低可用性”？
更新 1
节点有足够的资源并且准备就绪。YAML 文件看起来不错。我在不同的区域/区域中有 2 个集群，并且都有上面列出的部署错误。2 豆荚不好。
Name: ml-pipeline-65479485c8-mcj9x
Namespace: default
Priority: 0
Node: gke-cluster-3-default-pool-007784cb-qcsn/10.150.0.2
Start Time: Thu, 17 Sep 2020 22:15:19 +0000
Labels: app=ml-pipeline
app.kubernetes.io/name=kubeflow-pipelines-3
pod-template-hash=65479485c8
Annotations: kubernetes.io/limit-ranger: LimitRanger plugin set: cpu request for container ml-pipeline-api-server
Status: Running
IP: 10.4.0.8
IPs:
IP: 10.4.0.8
Controlled By: ReplicaSet/ml-pipeline-65479485c8
Containers:
ml-pipeline-api-server:
Container ID: ...
Image: ...
Image ID: ...
Ports: 8888/TCP, 8887/TCP
Host Ports: 0/TCP, 0/TCP
State: Running
Started: Fri, 18 Sep 2020 10:27:31 +0000
Last State: Terminated
Reason: Error
Exit Code: 255
Started: Fri, 18 Sep 2020 10:20:38 +0000
Finished: Fri, 18 Sep 2020 10:27:31 +0000
Ready: False
Restart Count: 98
Requests:
cpu: 100m
Liveness: exec [wget -q -S -O - http://localhost:8888/apis/v1beta1/healthz] delay=3s timeout=2s period=5s #success=1 #failure=3
Readiness: exec [wget -q -S -O - http://localhost:8888/apis/v1beta1/healthz] delay=3s timeout=2s period=5s #success=1 #failure=3
Environment:
HAS_DEFAULT_BUCKET: true
BUCKET_NAME:
PROJECT_ID: <set to the key 'project_id' of config map 'gcp-default-config'> Optional: false
POD_NAMESPACE: default (v1:metadata.namespace)
DEFAULTPIPELINERUNNERSERVICEACCOUNT: pipeline-runner
OBJECTSTORECONFIG_SECURE: false
OBJECTSTORECONFIG_BUCKETNAME:
DBCONFIG_DBNAME: kubeflow_pipelines_3_pipeline
DBCONFIG_USER: <set to the key 'username' in secret 'mysql-credential'> Optional: false
DBCONFIG_PASSWORD: <set to the key 'password' in secret 'mysql-credential'> Optional: false
Mounts:
/var/run/secrets/kubernetes.io/serviceaccount from ml-pipeline-token-77xl8 (ro)
Conditions:
Type Status
Initialized True
Ready False
ContainersReady False
PodScheduled True
Volumes:
ml-pipeline-token-77xl8:
Type: Secret (a volume populated by a Secret)
SecretName: ml-pipeline-token-77xl8
Optional: false
QoS Class: Burstable
Node-Selectors: <none>
Tolerations: node.kubernetes.io/not-ready:NoExecute op=Exists for 300s
node.kubernetes.io/unreachable:NoExecute op=Exists for 300s
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Warning BackOff 52m (x409 over 11h) kubelet, gke-cluster-3-default-pool-007784cb-qcsn Back-off restarting failed container
Warning Unhealthy 31m (x94 over 12h) kubelet, gke-cluster-3-default-pool-007784cb-qcsn Readiness probe failed:
Warning Unhealthy 31m (x29 over 10h) kubelet, gke-cluster-3-default-pool-007784cb-qcsn (combined from similar events): Readiness probe failed: c
annot exec in a stopped state: unknown
Warning Unhealthy 17m (x95 over 12h) kubelet, gke-cluster-3-default-pool-007784cb-qcsn Liveness probe failed:
Normal Pulled 7m26s (x97 over 12h) kubelet, gke-cluster-3-default-pool-007784cb-qcsn Container image "gcr.io/cloud-marketplace/google-cloud-ai
-platform/kubeflow-pipelines/apiserver:1.0.0" already present on machine
Warning Unhealthy 75s (x78 over 12h) kubelet, gke-cluster-3-default-pool-007784cb-qcsn Liveness probe errored: rpc error: code = DeadlineExceede
d desc = context deadline exceeded
另一个吊舱：
Name: ml-pipeline-persistenceagent-67db8b8964-mlbmv
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Warning BackOff 32s (x2238 over 12h) kubelet, gke-cluster-3-default-pool-007784cb-qcsn Back-off restarting failed container
解决方案
不要让谷歌处理任何存储。取消选中“使用托管存储”并手动设置您自己的工件集合。您实际上不需要在这些字段中输入任何内容，因为无论如何都会启动管道。