标签 k8s 下的文章

Kubernetes集群跨节点挂载CephFS

Kubernetes集群中运行有状态服务或应用总是不那么容易的。比如,之前我在项目中使用了CephRBD,虽然遇到过几次问题,但总体算是运行良好。但最近发现CephRBD无法满足跨节点挂载的需求,我只好另辟蹊径。由于CephFS和CephRBD师出同门,它自然成为了这次我首要考察的目标。这里将跨节点挂载CephFS的考察过程记录一下,一是备忘,二则也可以为其他有相似需求的朋友提供些资料。

一、CephRBD的问题

这里先提一嘴CephRBD的问题。最近项目中有这样的需求:让集群中的Pod共享外部分布式存储,即多个Pod共同挂载一份存储,实现存储共享,这样可大大简化系统设计和复杂性。之前CephRBD都是挂载到一个Pod中运行的,CephRBD是否支持多Pod同时挂载呢?官方文档中给出了否定的答案: 基于CephRBD的Persistent Volume仅支持两种accessmode:
ReadWriteOnce和ReadOnlyMany,不支持ReadWriteMany。这样对于有读写需求的Pod来说,一个CephRBD pv仅能被一个node挂载一次。

我们来验证一下这个“不幸的”事实。

我们首先创建一个测试用的image:foo1。这里我利用了项目里写的CephRBD API服务,也可通过ceph命令手工创建:

# curl -v  -H "Content-type: application/json" -X POST -d '{"kind": "Images","apiVersion": "v1", "metadata": {"name": "foo1", "capacity": 512} ' http://192.168.3.22:8080/api/v1/pools/rbd/images
... ...
{
  "errcode": 0,
  "errmsg": "ok"
}

# curl http://192.168.3.22:8080/api/v1/pools/rbd/images
{
  "Kind": "ImagesList",
  "APIVersion": "v1",
  "Items": [
    {
      "name": "foo1"
    }
  ]
}

利用下面文件创建pv和pvc:

//ceph-pv.yaml

apiVersion: v1
kind: PersistentVolume
metadata:
  name: foo-pv
spec:
  capacity:
    storage: 512Mi
  accessModes:
    - ReadWriteMany
  rbd:
    monitors:
      - ceph_monitor_ip:port
    pool: rbd
    image: foo1
    user: admin
    secretRef:
      name: ceph-secret
    fsType: ext4
    readOnly: false
  persistentVolumeReclaimPolicy: Recycle

//ceph-pvc.yaml

kind: PersistentVolumeClaim
apiVersion: v1
metadata:
  name: foo-claim
spec:
  accessModes:
    - ReadWriteMany
  resources:
    requests:
      storage: 512Mi

创建后:

# kubectl get pv
[NAME                CAPACITY   ACCESSMODES   RECLAIMPOLICY   STATUS    CLAIM                        REASON    AGE
foo-pv              512Mi      RWO           Recycle         Bound     default/foo-claim                      20h

# kubectl get pvc
NAME                 STATUS    VOLUME              CAPACITY   ACCESSMODES   AGE
foo-claim            Bound     foo-pv              512Mi      RWO           20h

创建挂载上述image的Pod:

// ceph-pod2.yaml

apiVersion: v1
kind: Pod
metadata:
  name: ceph-pod2
spec:
  containers:
  - name: ceph-ubuntu2
    image: ubuntu:14.04
    command: ["tail", "-f", "/var/log/bootstrap.log"]
    volumeMounts:
    - name: ceph-vol2
      mountPath: /mnt/cephrbd/data
      readOnly: false
  volumes:
  - name: ceph-vol2
    persistentVolumeClaim:
      claimName: foo-claim

创建成功后,我们可以查看挂载目录的数据:

# kubectl exec ceph-pod2 ls /mnt/cephrbd/data
1.txt
lost+found

我们在同一个kubernetes node上再启动一个pod(可以把上面的ceph-pod2.yaml的pod name改为ceph-pod3),挂载同样的pv:

NAMESPACE                    NAME                                    READY     STATUS    RESTARTS   AGE       IP             NODE
default                      ceph-pod2                               1/1       Running   0          3m        172.16.57.9    xx.xx.xx.xx
default                      ceph-pod3                               1/1       Running   0          0s        172.16.57.10    xx.xx.xx.xx
# kubectl exec ceph-pod3 ls /mnt/cephrbd/data
1.txt
lost+found

我们通过ceph-pod2写一个文件,在ceph-pod3中将其读出:

# kubectl exec ceph-pod2 -- bash -c "for i in {1..10}; do sleep 1; echo 'pod2: Hello, World'>> /mnt/cephrbd/data/foo.txt ; done "
root@node1:~/k8stest/k8s-cephrbd/footest# kubectl exec ceph-pod3 cat /mnt/cephrbd/data/foo.txt
pod2: Hello, World
pod2: Hello, World
pod2: Hello, World
pod2: Hello, World
pod2: Hello, World
pod2: Hello, World
pod2: Hello, World
pod2: Hello, World
pod2: Hello, World
pod2: Hello, World

到目前为止,在一个node上多个Pod是可以以ReadWrite模式挂载同一个CephRBD的。

我们在另外一个节点启动一个试图挂载该pv的Pod,该Pod启动后一直处于pending状态,通过kubectl describe查看其详细信息,可以看到:

Events:
  FirstSeen    LastSeen    Count    From            SubobjectPath    Type        Reason        Message
  ---------    --------    -----    ----            -------------    --------    ------        -------
.. ...
  2m        37s        2    {kubelet yy.yy.yy.yy}            Warning        FailedMount    Unable to mount volumes for pod "ceph-pod2-master_default(a45f62aa-2bc3-11e7-9baa-00163e1625a9)": timeout expired waiting for volumes to attach/mount for pod "ceph-pod2-master"/"default". list of unattached/unmounted volumes=[ceph-vol2]
  2m        37s        2    {kubelet yy.yy.yy.yy}            Warning        FailedSync    Error syncing pod, skipping: timeout expired waiting for volumes to attach/mount for pod "ceph-pod2-master"/"default". list of unattached/unmounted volumes=[ceph-vol2]

查看kubelet.log中的错误日志:

I0428 11:39:15.737729    1241 reconciler.go:294] MountVolume operation started for volume "kubernetes.io/rbd/a45f62aa-2bc3-11e7-9baa-00163e1625a9-foo-pv" (spec.Name: "foo-pv") to pod "a45f62aa-2bc3-11e7-9baa-00163e1625a9" (UID: "a45f62aa-2bc3-11e7-9baa-00163e1625a9").
I0428 11:39:15.939183    1241 operation_executor.go:768] MountVolume.SetUp succeeded for volume "kubernetes.io/secret/923700ff-12c2-11e7-9baa-00163e1625a9-default-token-40z0x" (spec.Name: "default-token-40z0x") pod "923700ff-12c2-11e7-9baa-00163e1625a9" (UID: "923700ff-12c2-11e7-9baa-00163e1625a9").
E0428 11:39:17.039656    1241 disk_manager.go:56] failed to attach disk
E0428 11:39:17.039722    1241 rbd.go:228] rbd: failed to setup mount /var/lib/kubelet/pods/a45f62aa-2bc3-11e7-9baa-00163e1625a9/volumes/kubernetes.io~rbd/foo-pv rbd: image foo1 is locked by other nodes
E0428 11:39:17.039857    1241 nestedpendingoperations.go:254] Operation for "\"kubernetes.io/rbd/a45f62aa-2bc3-11e7-9baa-00163e1625a9-foo-pv\" (\"a45f62aa-2bc3-11e7-9baa-00163e1625a9\")" failed. No retries permitted until 2017-04-28 11:41:17.039803969 +0800 CST (durationBeforeRetry 2m0s). Error: MountVolume.SetUp failed for volume "kubernetes.io/rbd/a45f62aa-2bc3-11e7-9baa-00163e1625a9-foo-pv" (spec.Name: "foo-pv") pod "a45f62aa-2bc3-11e7-9baa-00163e1625a9" (UID: "a45f62aa-2bc3-11e7-9baa-00163e1625a9") with: rbd: image foo1 is locked by other nodes

可以看到“rbd: image foo1 is locked by other nodes”的日志。我们用试验证明了目前CephRBD仅能被k8s中的一个node挂载的事实。

二、Ceph集群安装mds以支持CephFS

这次我在两个Ubuntu 16.04的vm上新部署了一套Ceph,过程与之前第一次部署Ceph时大同小异,这里就不赘述了。要让Ceph支持CephFS,我们需要安装mds组件,有了前面的基础,通过ceph-deploy工具安装mds十分简单:

# ceph-deploy mds create yypdmaster yypdnode
[ceph_deploy.conf][DEBUG ] found configuration file at: /root/.cephdeploy.conf
[ceph_deploy.cli][INFO  ] Invoked (1.5.37): /usr/bin/ceph-deploy mds create yypdmaster yypdnode
[ceph_deploy.cli][INFO  ] ceph-deploy options:
[ceph_deploy.cli][INFO  ]  username                      : None
[ceph_deploy.cli][INFO  ]  verbose                       : False
[ceph_deploy.cli][INFO  ]  overwrite_conf                : False
[ceph_deploy.cli][INFO  ]  subcommand                    : create
[ceph_deploy.cli][INFO  ]  quiet                         : False
[ceph_deploy.cli][INFO  ]  cd_conf                       : <ceph_deploy.conf.cephdeploy.Conf instance at 0x7f60fb5e71b8>
[ceph_deploy.cli][INFO  ]  cluster                       : ceph
[ceph_deploy.cli][INFO  ]  func                          : <function mds at 0x7f60fba4e140>
[ceph_deploy.cli][INFO  ]  ceph_conf                     : None
[ceph_deploy.cli][INFO  ]  mds                           : [('yypdmaster', 'yypdmaster'), ('yypdnode', 'yypdnode')]
[ceph_deploy.cli][INFO  ]  default_release               : False
[ceph_deploy.mds][DEBUG ] Deploying mds, cluster ceph hosts yypdmaster:yypdmaster yypdnode:yypdnode
[yypdmaster][DEBUG ] connected to host: yypdmaster
[yypdmaster][DEBUG ] detect platform information from remote host
[yypdmaster][DEBUG ] detect machine type
[ceph_deploy.mds][INFO  ] Distro info: Ubuntu 16.04 xenial
[ceph_deploy.mds][DEBUG ] remote host will use systemd
[ceph_deploy.mds][DEBUG ] deploying mds bootstrap to yypdmaster
[yypdmaster][DEBUG ] write cluster configuration to /etc/ceph/{cluster}.conf
[yypdmaster][DEBUG ] create path if it doesn't exist
[yypdmaster][INFO  ] Running command: ceph --cluster ceph --name client.bootstrap-mds --keyring /var/lib/ceph/bootstrap-mds/ceph.keyring auth get-or-create mds.yypdmaster osd allow rwx mds allow mon allow profile mds -o /var/lib/ceph/mds/ceph-yypdmaster/keyring
[yypdmaster][INFO  ] Running command: systemctl enable ceph-mds@yypdmaster
[yypdmaster][WARNIN] Created symlink from /etc/systemd/system/ceph-mds.target.wants/ceph-mds@yypdmaster.service to /lib/systemd/system/ceph-mds@.service.
[yypdmaster][INFO  ] Running command: systemctl start ceph-mds@yypdmaster
[yypdmaster][INFO  ] Running command: systemctl enable ceph.target
[yypdnode][DEBUG ] connected to host: yypdnode
[yypdnode][DEBUG ] detect platform information from remote host
[yypdnode][DEBUG ] detect machine type
[ceph_deploy.mds][INFO  ] Distro info: Ubuntu 16.04 xenial
[ceph_deploy.mds][DEBUG ] remote host will use systemd
[ceph_deploy.mds][DEBUG ] deploying mds bootstrap to yypdnode
[yypdnode][DEBUG ] write cluster configuration to /etc/ceph/{cluster}.conf
[yypdnode][DEBUG ] create path if it doesn't exist
[yypdnode][INFO  ] Running command: ceph --cluster ceph --name client.bootstrap-mds --keyring /var/lib/ceph/bootstrap-mds/ceph.keyring auth get-or-create mds.yypdnode osd allow rwx mds allow mon allow profile mds -o /var/lib/ceph/mds/ceph-yypdnode/keyring
[yypdnode][INFO  ] Running command: systemctl enable ceph-mds@yypdnode
[yypdnode][WARNIN] Created symlink from /etc/systemd/system/ceph-mds.target.wants/ceph-mds@yypdnode.service to /lib/systemd/system/ceph-mds@.service.
[yypdnode][INFO  ] Running command: systemctl start ceph-mds@yypdnode
[yypdnode][INFO  ] Running command: systemctl enable ceph.target

非常顺利。安装后,可以在任意一个node上看到mds在运行:

# ps -ef|grep ceph
ceph      7967     1  0 17:23 ?        00:00:00 /usr/bin/ceph-osd -f --cluster ceph --id 1 --setuser ceph --setgroup ceph
ceph     15674     1  0 17:32 ?        00:00:00 /usr/bin/ceph-mon -f --cluster ceph --id yypdnode --setuser ceph --setgroup ceph
ceph     18019     1  0 17:35 ?        00:00:00 /usr/bin/ceph-mds -f --cluster ceph --id yypdnode --setuser ceph --setgroup ceph

mds是存储cephfs的元信息的,我的ceph是10.2.7版本:

# ceph -v
ceph version 10.2.7 (50e863e0f4bc8f4b9e31156de690d765af245185)

虽然支持多 active mds并行运行,但官方文档建议保持一个active mds,其他mds作为standby(见下面ceph集群信息中的fsmap部分):

# ceph -s
    cluster ffac3489-d678-4caf-ada2-3dd0743158b6
    ... ...
      fsmap e6: 1/1/1 up {0=yypdnode=up:active}, 1 up:standby
     osdmap e19: 2 osds: 2 up, 2 in
            flags sortbitwise,require_jewel_osds
      pgmap v192498: 576 pgs, 5 pools, 126 MB data, 238 objects
            44365 MB used, 31881 MB / 80374 MB avail
                 576 active+clean

三、创建fs并测试挂载

我们在ceph上创建一个fs:

# ceph osd pool create cephfs_data 128
pool 'cephfs_data' created

# ceph osd pool create cephfs_metadata 128
pool 'cephfs_metadata' created

# ceph fs new test_fs cephfs_metadata cephfs_data
new fs with metadata pool 2 and data pool 1

# ceph fs ls
name: test_fs, metadata pool: cephfs_metadata, data pools: [cephfs_data ]

不过,ceph当前正式版功能中仅支持一个fs,对多个fs的支持仅存在于实验feature中:

# ceph osd pool create cephfs1_data 128
# ceph osd pool create cephfs1_metadata 128
# ceph fs new test_fs1 cephfs1_metadata cephfs1_data
Error EINVAL: Creation of multiple filesystems is disabled.  To enable this experimental feature, use 'ceph fs flag set enable_multiple true'

在物理机上挂载cephfs可以使用mount命令、mount.ceph(apt-get install ceph-fs-common)或ceph-fuse(apt-get install ceph-fuse),我们先用mount命令挂载:

我们将上面创建的cephfs挂载到主机的/mnt下:

#mount -t ceph ceph_mon_host:6789:/ /mnt -o name=admin,secretfile=admin.secret

# cat admin.secret //ceph.client.admin.keyring中的key
AQDITghZD+c/DhAArOiWWQqyMAkMJbWmHaxjgQ==

查看cephfs信息:

# df -h
ceph_mon_host:6789:/   79G   45G   35G  57% /mnt

可以看出:cephfs将两个物理节点上的磁盘全部空间作为了自己的空间。

通过ceph-fuse挂载,还可以限制对挂载路径的访问权限,我们来创建用户foo,让其仅仅拥有对/ceph-volume1-test路径具有只读访问权限:

# ceph auth get-or-create client.foo mon 'allow *' mds 'allow r path=/ceph-volume1-test' osd 'allow *'
# ceph-fuse -n client.foo -m 10.47.217.91:6789 /mnt -r /ceph-volume1-test
ceph-fuse[10565]: starting ceph client2017-05-03 16:07:25.958903 7f1a14fbff00 -1 init, newargv = 0x557e350defc0 newargc=11
ceph-fuse[10565]: starting fuse

查看挂载路径,并尝试创建文件:

# cd /mnt
root@yypdnode:/mnt# ls
1.txt
root@yypdnode:/mnt# touch 2.txt
touch: cannot touch '2.txt': Permission denied

由于foo用户只拥有对 /ceph-volume1-test的只读权限,因此创建文件失败了!

四、Kubernetes跨节点挂载CephFS

在K8s中,至少可以通过两种方式挂载CephFS,一种是通过Pod直接挂载;另外一种则是通过pv和pvc挂载。我们分别来看。

1、Pod直接挂载CephFS

//ceph-pod2-with-secret.yaml
apiVersion: v1
kind: Pod
metadata:
  name: ceph-pod2-with-secret
spec:
  containers:
  - name: ceph-ubuntu2
    image: ubuntu:14.04
    command: ["tail", "-f", "/var/log/bootstrap.log"]
    volumeMounts:
    - name: ceph-vol2
      mountPath: /mnt/cephfs/data
      readOnly: false
  volumes:
  - name: ceph-vol2
    cephfs:
      monitors:
      - ceph_mon_host:6789
      user: admin
      secretFile: "/etc/ceph/admin.secret"
      readOnly: false

注意:保证每个节点上都存在/etc/ceph/admin.secret文件。

查看Pod挂载的内容:

# docker ps|grep pod
bc96431408c7        ubuntu:14.04                                                  "tail -f /var/log/boo"   About a minute ago   Up About a minute                                                                        k8s_ceph-ubuntu2.66c44128_ceph-pod2-with-secret_default_3d8a05f8-33c3-11e7-bcd9-6640d35a0e90_fc483b8a
bcc65ab82069        gcr.io/google_containers/pause-amd64:3.0                      "/pause"                 About a minute ago   Up About a minute                                                                        k8s_POD.d8dbe16c_ceph-pod2-with-secret_default_3d8a05f8-33c3-11e7-bcd9-6640d35a0e90_02381204

root@yypdnode:~# docker exec bc96431408c7 ls /mnt/cephfs/data
1.txt
apps
ceph-volume1-test
test1.txt

我们再在另外一个node上启动挂载同一个cephfs的Pod,看是否可以跨节点挂载:

# kubectl get pods

NAMESPACE                    NAME                                    READY     STATUS    RESTARTS   AGE       IP             NODE
default                      ceph-pod2-with-secret                   1/1       Running   0          3m        172.30.192.2   iz2ze39jeyizepdxhwqci6z
default                      ceph-pod2-with-secret-on-master         1/1       Running   0          3s        172.30.0.51    iz25beglnhtz
... ...

# kubectl exec ceph-pod2-with-secret-on-master ls /mnt/cephfs/data
1.txt
apps
ceph-volume1-test
test1.txt

可以看到不同节点可以挂载同一CephFS。我们在一个pod中操作一下挂载的cephfs:

# kubectl exec ceph-pod2-with-secret-on-master -- bash -c "for i in {1..10}; do sleep 1; echo 'pod2-with-secret-on-master: Hello, World'>> /mnt/cephfs/data/foo.txt ; done "
root@yypdmaster:~/k8stest/cephfstest/footest# kubectl exec ceph-pod2-with-secret-on-master cat /mnt/cephfs/data/foo.txt
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World

2、通过PV和PVC挂载CephFS

挂载cephfs的pv和pvc在写法方面与上面挂载rbd的类似:

//ceph-pv.yaml
apiVersion: v1
kind: PersistentVolume
metadata:
  name: foo-pv
spec:
  capacity:
    storage: 512Mi
  accessModes:
    - ReadWriteMany
  cephfs:
    monitors:
      - ceph_mon_host:6789
    path: /
    user: admin
    secretRef:
      name: ceph-secret
    readOnly: false
  persistentVolumeReclaimPolicy: Recycle

//ceph-pvc.yaml

kind: PersistentVolumeClaim
apiVersion: v1
metadata:
  name: foo-claim
spec:
  accessModes:
    - ReadWriteMany
  resources:
    requests:
      storage: 512Mi

使用pvc的pod:

//ceph-pod2.yaml
apiVersion: v1
kind: Pod
metadata:
  name: ceph-pod2
spec:
  containers:
  - name: ceph-ubuntu2
    image: ubuntu:14.04
    command: ["tail", "-f", "/var/log/bootstrap.log"]
    volumeMounts:
    - name: ceph-vol2
      mountPath: /mnt/cephfs/data
      readOnly: false
  volumes:
  - name: ceph-vol2
    persistentVolumeClaim:
      claimName: foo-claim

创建pv、pvc:

# kubectl create -f ceph-pv.yaml
persistentvolume "foo-pv" created
# kubectl create -f ceph-pvc.yaml
persistentvolumeclaim "foo-claim" created

# kubectl get pvc
NAME        STATUS    VOLUME    CAPACITY   ACCESSMODES   AGE
foo-claim   Bound     foo-pv    512Mi      RWX           4s
# kubectl get pv
NAME      CAPACITY   ACCESSMODES   RECLAIMPOLICY   STATUS    CLAIM               REASON    AGE
foo-pv    512Mi      RWX           Recycle         Bound     default/foo-claim             24s

启动pod,通过exec命令查看挂载情况:

# docker ps|grep pod
a6895ec0274f        ubuntu:14.04                                                  "tail -f /var/log/boo"   About a minute ago   Up About a minute                                                                        k8s_ceph-ubuntu2.66c44128_ceph-pod2_default_4e4fc8d4-33c6-11e7-bcd9-6640d35a0e90_1b37ed76
52b6811a6584        gcr.io/google_containers/pause-amd64:3.0                      "/pause"                 About a minute ago   Up About a minute                                                                        k8s_POD.d8dbe16c_ceph-pod2_default_4e4fc8d4-33c6-11e7-bcd9-6640d35a0e90_27e5f988
55b96edbf4bf        ubuntu:14.04                                                  "tail -f /var/log/boo"   14 minutes ago       Up 14 minutes                                                                            k8s_ceph-ubuntu2.66c44128_ceph-pod2-with-secret_default_9d383b0c-33c4-11e7-bcd9-6640d35a0e90_1656e5e0
f8b699bc0459        gcr.io/google_containers/pause-amd64:3.0                      "/pause"                 14 minutes ago       Up 14 minutes                                                                            k8s_POD.d8dbe16c_ceph-pod2-with-secret_default_9d383b0c-33c4-11e7-bcd9-6640d35a0e90_effdfae7
root@yypdnode:~# docker exec a6895ec0274f ls /mnt/cephfs/data
1.txt
apps
ceph-volume1-test
foo.txt
test1.txt

# docker exec a6895ec0274f cat /mnt/cephfs/data/foo.txt
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World
pod2-with-secret-on-master: Hello, World

五、pv的状态

如果你不删除pvc,一切都安然无事:

# kubectl get pv
NAME                CAPACITY   ACCESSMODES   RECLAIMPOLICY   STATUS    CLAIM                        REASON    AGE
foo-pv              512Mi      RWX           Recycle         Bound     default/foo-claim                      1h

# kubectl get pvc
NAME                 STATUS    VOLUME              CAPACITY   ACCESSMODES   AGE
foo-claim            Bound     foo-pv              512Mi      RWX           1h

但是如果删除pvc,pv的状态将变成failed:

删除pvc:

# kubectl get pv
NAME                CAPACITY   ACCESSMODES   RECLAIMPOLICY   STATUS    CLAIM                        REASON    AGE
foo-pv              512Mi      RWX           Recycle         Failed    default/foo-claim                      2h

# kubectl describe pv/foo-pv
Name:        foo-pv
Labels:        <none>
Status:        Failed
Claim:        default/foo-claim
Reclaim Policy:    Recycle
Access Modes:    RWX
Capacity:    512Mi
Message:    No recycler plugin found for the volume!
Source:
    Type:        RBD (a Rados Block Device mount on the host that shares a pod's lifetime)
    CephMonitors:    [xx.xx.xx.xx:6789]
    RBDImage:        foo1
    FSType:        ext4
    RBDPool:        rbd
    RadosUser:        admin
    Keyring:        /etc/ceph/keyring
    SecretRef:        &{ceph-secret}
    ReadOnly:        false
Events:
  FirstSeen    LastSeen    Count    From                SubobjectPath    Type        Reason            Message
  ---------    --------    -----    ----                -------------    --------    ------            -------
  29s        29s        1    {persistentvolume-controller }            Warning        VolumeFailedRecycle    No recycler plugin found for the volume!

我们在pv中指定的persistentVolumeReclaimPolicy是Recycle,但无论是cephrbd还是cephfs都不没有对应的recycler plugin,导致pv的status变成了failed,只能手工删除重建。

使用Fluentd和ElasticSearch Stack实现Kubernetes的集群Logging

在本篇文章中,我们继续来说Kubernetes

经过一段时间的探索,我们先后完成了Kubernetes集群搭建DNSDashboardHeapster等插件安装,集群安全配置,搭建作为Persistent Volume的CephRBD,以及服务更新探索和实现工作。现在Kubernetes集群层面的Logging需求逐渐浮上水面了。

随着一些小应用在我们的Kubernetes集群上的部署上线,集群的运行迈上了正轨。但问题随之而来,那就是如何查找和诊断集群自身的问题以及运行于Pod中应用的问题。日志,没错!我们也只能依赖Kubernetes组件以及Pod中应用输出的日志。不过目前我们仅能通过kubectl logs命令或Kubernetes Dashboard来查看Log。在没有cluster level logging的情况下,我们需要分别查看各个Pod的日志,操作繁琐,过程低效。我们迫切地需要为Kubernetes集群搭建一套集群级别的集中日志收集和分析设施。

对于任何基础设施或后端服务系统,日志都是极其重要的。对于受Google内部容器管理系统Borg启发而催生出的Kubernetes项目来说,自然少不了对Logging的支持。在“Logging Overview“中,官方概要介绍了Kubernetes上的几个层次的Logging方案,并给出Cluster-level logging的参考架构:

img{512x368}

Kubernetes还给出了参考实现:
– Logging Backend:Elastic Search stack(包括:Kibana)
– Logging-agent:fluentd

ElasticSearch stack实现的cluster level logging的一个优势在于其对Kubernetes集群中的Pod没有侵入性,Pod无需做任何配合性改动。同时EFK/ELK方案在业内也是相对成熟稳定的。

在本文中,我将为我们的Kubernetes 1.3.7集群安装ElasticSearch、Fluentd和Kibana。由于1.3.7版本略有些old,EFK能否在其上面run起来,我也是心中未知。能否像《生化危机:终章》那样有一个完美的结局,我们还需要一步一步“打怪升级”慢慢看。

一、Kubernetes 1.3.7集群的 “漏网之鱼”

Kubernetes 1.3.7集群是通过kube-up.sh搭建并初始化的。按照K8s官方文档有关elasticsearch logging的介绍,在kubernetes/cluster/ubuntu/config-default.sh中,我也发现了下面几个配置项:

// kubernetes/cluster/ubuntu/config-default.sh
# Optional: Enable node logging.
ENABLE_NODE_LOGGING=false
LOGGING_DESTINATION=${LOGGING_DESTINATION:-elasticsearch}

# Optional: When set to true, Elasticsearch and Kibana will be setup as part of the cluster bring up.
ENABLE_CLUSTER_LOGGING=false
ELASTICSEARCH_LOGGING_REPLICAS=${ELASTICSEARCH_LOGGING_REPLICAS:-1}

显然,当初如果搭建集群伊始时要是知道这些配置的意义,可能那个时候就会将elastic logging集成到集群中了。现在为时已晚,集群上已经跑了很多应用,无法重新通过kube-up.sh中断集群运行并安装elastic logging了。我只能手工进行安装了!

二、镜像准备

1.3.7源码中kubernetes/cluster/addons/fluentd-elasticsearch下的manifest已经比较old了,我们直接使用kubernetes最新源码中的manifest文件

k8s.io/kubernetes/cluster/addons/fluentd-elasticsearch$ ls *.yaml
es-controller.yaml  es-service.yaml  fluentd-es-ds.yaml  kibana-controller.yaml  kibana-service.yaml

分析这些yaml,我们需要三个镜像:

 gcr.io/google_containers/fluentd-elasticsearch:1.22
 gcr.io/google_containers/elasticsearch:v2.4.1-1
 gcr.io/google_containers/kibana:v4.6.1-1

显然镜像都在墙外。由于生产环境下的Docker引擎并没有配置加速器代理,因此我们需要手工下载一下这三个镜像。我采用的方法是通过另外一台配置了加速器的机器上的Docker引擎将三个image下载,并重新打tag,上传到我在hub.docker.com上的账号下,以elasticsearch:v2.4.1-1为例:

# docker pull  gcr.io/google_containers/elasticsearch:v2.4.1-1
# docker tag gcr.io/google_containers/elasticsearch:v2.4.1-1 bigwhite/elasticsearch:v2.4.1-1
# docker push bigwhite/elasticsearch:v2.4.1-1

下面是我们在后续安装过程中真正要使用到的镜像:

bigwhite/fluentd-elasticsearch:1.22
bigwhite/elasticsearch:v2.4.1-1
bigwhite/kibana:v4.6.1-1

三、启动fluentd

fluentd是以DaemonSet的形式跑在K8s集群上的,这样k8s可以保证每个k8s cluster node上都会启动一个fluentd(注意:将image改为上述镜像地址,如果你配置了加速器,那自然就不必了)。

# kubectl create -f fluentd-es-ds.yaml --record
daemonset "fluentd-es-v1.22" created

查看daemonset中的Pod的启动情况,我们发现:

kube-system                  fluentd-es-v1.22-as3s5                  0/1       CrashLoopBackOff   2          43s       172.16.99.6    10.47.136.60
kube-system                  fluentd-es-v1.22-qz193                  0/1       CrashLoopBackOff   2          43s       172.16.57.7    10.46.181.146

fluentd Pod启动失败,fluentd的日志可以通过/var/log/fluentd.log查看:

# tail -100f /var/log/fluentd.log

2017-03-02 02:27:01 +0000 [info]: reading config file path="/etc/td-agent/td-agent.conf"
2017-03-02 02:27:01 +0000 [info]: starting fluentd-0.12.31
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-mixin-config-placeholders' version '0.4.0'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-mixin-plaintextformatter' version '0.2.6'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-docker_metadata_filter' version '0.1.3'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-elasticsearch' version '1.5.0'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-kafka' version '0.4.1'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-kubernetes_metadata_filter' version '0.24.0'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-mongo' version '0.7.16'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-rewrite-tag-filter' version '1.5.5'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-s3' version '0.8.0'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-scribe' version '0.10.14'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-td' version '0.10.29'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-td-monitoring' version '0.2.2'
2017-03-02 02:27:01 +0000 [info]: gem 'fluent-plugin-webhdfs' version '0.4.2'
2017-03-02 02:27:01 +0000 [info]: gem 'fluentd' version '0.12.31'
2017-03-02 02:27:01 +0000 [info]: adding match pattern="fluent.**" type="null"
2017-03-02 02:27:01 +0000 [info]: adding filter pattern="kubernetes.**" type="kubernetes_metadata"
2017-03-02 02:27:02 +0000 [error]: config error file="/etc/td-agent/td-agent.conf" error="Invalid Kubernetes API v1 endpoint https://192.168.3.1:443/api: 401 Unauthorized"
2017-03-02 02:27:02 +0000 [info]: process finished code=256
2017-03-02 02:27:02 +0000 [warn]: process died within 1 second. exit.

从上述日志中的error来看:fluentd访问apiserver secure port(443)出错了:Unauthorized! 通过分析 cluster/addons/fluentd-elasticsearch/fluentd-es-image/build.sh和td-agent.conf,我们发现是fluentd image中的fluent-plugin-kubernetes_metadata_filter要去访问API Server以获取一些kubernetes的metadata信息。不过未做任何特殊配置的fluent-plugin-kubernetes_metadata_filter,我猜测它使用的是kubernetes为Pod传入的环境变量:KUBERNETES_SERVICE_HOST和KUBERNETES_SERVICE_PORT来得到API Server的访问信息的。但API Server在secure port上是开启了安全身份验证机制的,fluentd直接访问必然是失败的。

我们找到了fluent-plugin-kubernetes_metadata_filter项目在github.com上的主页,在这个页面上我们看到了fluent-plugin-kubernetes_metadata_filter支持的其他配置,包括:ca_file、client_cert、client_key等,显然这些字眼非常眼熟。我们需要修改一下fluentd image中td-agent.conf的配置,为fluent-plugin-kubernetes_metadata_filter增加一些配置项,比如:

// td-agent.conf
... ...
<filter kubernetes.**>
  type kubernetes_metadata
  ca_file /srv/kubernetes/ca.crt
  client_cert /srv/kubernetes/kubecfg.crt
  client_key /srv/kubernetes/kubecfg.key
</filter>
... ...

这里我不想重新制作image,那么怎么办呢?Kubernetes提供了ConfigMap这一强大的武器,我们可以将新版td-agent.conf制作成kubernetes的configmap资源,并挂载到fluentd pod的相应位置以替换image中默认的td-agent.conf。

需要注意两点:
* 在基于td-agent.conf创建configmap资源之前,需要将td-agent.conf中的注释行都删掉,否则生成的configmap的内容可能不正确;
* fluentd pod将创建在kube-system下,因此configmap资源也需要创建在kube-system namespace下面,否则kubectl create无法找到对应的configmap。

# kubectl create configmap td-agent-config --from-file=./td-agent.conf -n kube-system
configmap "td-agent-config" created

# kubectl get configmaps -n kube-system
NAME              DATA      AGE
td-agent-config   1         9s

# kubectl get configmaps td-agent-config -o yaml
apiVersion: v1
data:
  td-agent.conf: |
    <match fluent.**>
      type null
    </match>

    <source>
      type tail
      path /var/log/containers/*.log
      pos_file /var/log/es-containers.log.pos
      time_format %Y-%m-%dT%H:%M:%S.%NZ
      tag kubernetes.*
      format json
      read_from_head true
    </source>
... ...

fluentd-es-ds.yaml也要随之做一些改动,主要是增加两个mount: 一个是mount 上面的configmap td-agent-config,另外一个就是mount hostpath:/srv/kubernetes以获取到相关client端的数字证书:

  spec:
      containers:
      - name: fluentd-es
        image: bigwhite/fluentd-elasticsearch:1.22
        command:
          - '/bin/sh'
          - '-c'
          - '/usr/sbin/td-agent 2>&1 >> /var/log/fluentd.log'
        resources:
          limits:
            memory: 200Mi
          #requests:
            #cpu: 100m
            #memory: 200Mi
        volumeMounts:
        - name: varlog
          mountPath: /var/log
        - name: varlibdockercontainers
          mountPath: /var/lib/docker/containers
          readOnly: true
        - name: td-agent-config
          mountPath: /etc/td-agent
        - name: tls-files
          mountPath: /srv/kubernetes
      terminationGracePeriodSeconds: 30
      volumes:
      - name: varlog
        hostPath:
          path: /var/log
      - name: varlibdockercontainers
        hostPath:
          path: /var/lib/docker/containers
      - name: td-agent-config
        configMap:
          name: td-agent-config
      - name: tls-files
        hostPath:
          path: /srv/kubernetes

接下来,我们重新创建fluentd ds,步骤不赘述。这回我们的创建成功了:

kube-system                  fluentd-es-v1.22-adsrx                  1/1       Running    0          1s        172.16.99.6    10.47.136.60
kube-system                  fluentd-es-v1.22-rpme3                  1/1       Running    0          1s        172.16.57.7    10.46.181.146

但通过查看/var/log/fluentd.log,我们依然能看到“问题”:

2017-03-02 03:57:58 +0000 [warn]: temporarily failed to flush the buffer. next_retry=2017-03-02 03:57:59 +0000 error_class="Fluent::ElasticsearchOutput::ConnectionFailure" error="Can not reach Elasticsearch cluster ({:host=>\"elasticsearch-logging\", :port=>9200, :scheme=>\"http\"})!" plugin_id="object:3fd99fa857d8"
  2017-03-02 03:57:58 +0000 [warn]: suppressed same stacktrace
2017-03-02 03:58:00 +0000 [warn]: temporarily failed to flush the buffer. next_retry=2017-03-02 03:58:03 +0000 error_class="Fluent::ElasticsearchOutput::ConnectionFailure" error="Can not reach Elasticsearch cluster ({:host=>\"elasticsearch-logging\", :port=>9200, :scheme=>\"http\"})!" plugin_id="object:3fd99fa857d8"
2017-03-02 03:58:00 +0000 [info]: process finished code=9
2017-03-02 03:58:00 +0000 [error]: fluentd main process died unexpectedly. restarting.

由于ElasticSearch logging还未创建,这是连不上elasticsearch所致。

四、启动elasticsearch

启动elasticsearch:

# kubectl create -f es-controller.yaml
replicationcontroller "elasticsearch-logging-v1" created

# kubectl create -f es-service.yaml
service "elasticsearch-logging" created

get pods:

kube-system                  elasticsearch-logging-v1-3bzt6          1/1       Running    0          7s        172.16.57.8    10.46.181.146
kube-system                  elasticsearch-logging-v1-nvbe1          1/1       Running    0          7s        172.16.99.10   10.47.136.60

elastic search logging启动成功后,上述fluentd的fail日志就没有了!

不过elastic search真的运行ok了么?我们查看一下elasticsearch相关Pod日志:

# kubectl logs -f elasticsearch-logging-v1-3bzt6 -n kube-system
F0302 03:59:41.036697       8 elasticsearch_logging_discovery.go:60] kube-system namespace doesn't exist: the server has asked for the client to provide credentials (get namespaces kube-system)
goroutine 1 [running]:
k8s.io/kubernetes/vendor/github.com/golang/glog.stacks(0x19a8100, 0xc400000000, 0xc2, 0x186)
... ...
main.main()
    elasticsearch_logging_discovery.go:60 +0xb53

[2017-03-02 03:59:42,587][INFO ][node                     ] [elasticsearch-logging-v1-3bzt6] version[2.4.1], pid[16], build[c67dc32/2016-09-27T18:57:55Z]
[2017-03-02 03:59:42,588][INFO ][node                     ] [elasticsearch-logging-v1-3bzt6] initializing ...
[2017-03-02 03:59:44,396][INFO ][plugins                  ] [elasticsearch-logging-v1-3bzt6] modules [reindex, lang-expression, lang-groovy], plugins [], sites []
... ...
[2017-03-02 03:59:44,441][INFO ][env                      ] [elasticsearch-logging-v1-3bzt6] heap size [1007.3mb], compressed ordinary object pointers [true]
[2017-03-02 03:59:48,355][INFO ][node                     ] [elasticsearch-logging-v1-3bzt6] initialized
[2017-03-02 03:59:48,355][INFO ][node                     ] [elasticsearch-logging-v1-3bzt6] starting ...
[2017-03-02 03:59:48,507][INFO ][transport                ] [elasticsearch-logging-v1-3bzt6] publish_address {172.16.57.8:9300}, bound_addresses {[::]:9300}
[2017-03-02 03:59:48,547][INFO ][discovery                ] [elasticsearch-logging-v1-3bzt6] kubernetes-logging/7_f_M2TKRZWOw4NhBc4EqA
[2017-03-02 04:00:18,552][WARN ][discovery                ] [elasticsearch-logging-v1-3bzt6] waited for 30s and no initial state was set by the discovery
[2017-03-02 04:00:18,562][INFO ][http                     ] [elasticsearch-logging-v1-3bzt6] publish_address {172.16.57.8:9200}, bound_addresses {[::]:9200}
[2017-03-02 04:00:18,562][INFO ][node                     ] [elasticsearch-logging-v1-3bzt6] started
[2017-03-02 04:01:15,754][WARN ][discovery.zen.ping.unicast] [elasticsearch-logging-v1-3bzt6] failed to send ping to [{#zen_unicast_1#}{127.0.0.1}{127.0.0.1:9300}]
SendRequestTransportException[[][127.0.0.1:9300][internal:discovery/zen/unicast]]; nested: NodeNotConnectedException[[][127.0.0.1:9300] Node not connected];
... ...
Caused by: NodeNotConnectedException[[][127.0.0.1:9300] Node not connected]
    at org.elasticsearch.transport.netty.NettyTransport.nodeChannel(NettyTransport.java:1141)
    at org.elasticsearch.transport.netty.NettyTransport.sendRequest(NettyTransport.java:830)
    at org.elasticsearch.transport.TransportService.sendRequest(TransportService.java:329)
    ... 12 more

总结了一下,日志中有两个错误:
- 无法访问到API Server,这个似乎和fluentd最初的问题一样;
- elasticsearch两个节点间互ping失败。

要想找到这两个问题的原因,还得回到源头,去分析elastic search image的组成。

通过cluster/addons/fluentd-elasticsearch/es-image/run.sh文件内容:

/elasticsearch_logging_discovery >> /elasticsearch/config/elasticsearch.yml

chown -R elasticsearch:elasticsearch /data

/bin/su -c /elasticsearch/bin/elasticsearch elasticsearch

我们了解到image中,其实包含了两个程序,一个为/elasticsearch_logging_discovery,该程序执行后生成一个配置文件: /elasticsearch/config/elasticsearch.yml。该配置文件后续被另外一个程序:/elasticsearch/bin/elasticsearch使用。

我们查看一下已经运行的docker中的elasticsearch.yml文件内容:

# docker exec 3cad31f6eb08 cat /elasticsearch/config/elasticsearch.yml
cluster.name: kubernetes-logging

node.name: ${NODE_NAME}
node.master: ${NODE_MASTER}
node.data: ${NODE_DATA}

transport.tcp.port: ${TRANSPORT_PORT}
http.port: ${HTTP_PORT}

path.data: /data

network.host: 0.0.0.0

discovery.zen.minimum_master_nodes: ${MINIMUM_MASTER_NODES}
discovery.zen.ping.multicast.enabled: false

这个结果中缺少了一项:

discovery.zen.ping.unicast.hosts: ["172.30.0.11", "172.30.192.15"]

这也是导致第二个问题的原因。综上,elasticsearch logging的错误其实都是由于/elasticsearch_logging_discovery无法访问API Server导致 /elasticsearch/config/elasticsearch.yml没有被正确生成造成的,我们就来解决这个问题。

我查看了一下/elasticsearch_logging_discovery的源码,elasticsearch_logging_discovery是一个典型通过client-go通过service account访问API Server的程序,很显然这就是我在《在Kubernetes Pod中使用Service Account访问API Server》一文中提到的那个问题:默认的service account不好用。

解决方法:在kube-system namespace下创建一个新的service account资源,并在es-controller.yaml中显式使用该新创建的service account。

创建一个新的serviceaccount在kube-system namespace下:

//serviceaccount.yaml
apiVersion: v1
kind: ServiceAccount
metadata:
  name: k8s-efk

# kubectl create -f serviceaccount.yaml -n kube-system
serviceaccount "k8s-efk" created

# kubectl get serviceaccount -n kube-system
NAME      SECRETS   AGE
default   1         139d
k8s-efk   1         17s

在es-controller.yaml中,使用service account “k8s-efk”:

//es-controller.yaml
... ...
spec:
  replicas: 2
  selector:
    k8s-app: elasticsearch-logging
    version: v1
  template:
    metadata:
      labels:
        k8s-app: elasticsearch-logging
        version: v1
        kubernetes.io/cluster-service: "true"
    spec:
      serviceAccount: k8s-efk
      containers:
... ...

重新创建elasticsearch logging service后,我们再来查看elasticsearch-logging pod的日志:

# kubectl logs -f elasticsearch-logging-v1-dklui -n kube-system
[2017-03-02 08:26:46,500][INFO ][node                     ] [elasticsearch-logging-v1-dklui] version[2.4.1], pid[14], build[c67dc32/2016-09-27T18:57:55Z]
[2017-03-02 08:26:46,504][INFO ][node                     ] [elasticsearch-logging-v1-dklui] initializing ...
[2017-03-02 08:26:47,984][INFO ][plugins                  ] [elasticsearch-logging-v1-dklui] modules [reindex, lang-expression, lang-groovy], plugins [], sites []
[2017-03-02 08:26:48,073][INFO ][env                      ] [elasticsearch-logging-v1-dklui] using [1] data paths, mounts [[/data (/dev/vda1)]], net usable_space [16.9gb], net total_space [39.2gb], spins? [possibly], types [ext4]
[2017-03-02 08:26:48,073][INFO ][env                      ] [elasticsearch-logging-v1-dklui] heap size [1007.3mb], compressed ordinary object pointers [true]
[2017-03-02 08:26:53,241][INFO ][node                     ] [elasticsearch-logging-v1-dklui] initialized
[2017-03-02 08:26:53,241][INFO ][node                     ] [elasticsearch-logging-v1-dklui] starting ...
[2017-03-02 08:26:53,593][INFO ][transport                ] [elasticsearch-logging-v1-dklui] publish_address {172.16.57.8:9300}, bound_addresses {[::]:9300}
[2017-03-02 08:26:53,651][INFO ][discovery                ] [elasticsearch-logging-v1-dklui] kubernetes-logging/Ky_OuYqMRkm_918aHRtuLg
[2017-03-02 08:26:56,736][INFO ][cluster.service          ] [elasticsearch-logging-v1-dklui] new_master {elasticsearch-logging-v1-dklui}{Ky_OuYqMRkm_918aHRtuLg}{172.16.57.8}{172.16.57.8:9300}{master=true}, added {{elasticsearch-logging-v1-vjxm3}{cbzgrfZATyWkHfQYHZhs7Q}{172.16.99.10}{172.16.99.10:9300}{master=true},}, reason: zen-disco-join(elected_as_master, [1] joins received)
[2017-03-02 08:26:56,955][INFO ][http                     ] [elasticsearch-logging-v1-dklui] publish_address {172.16.57.8:9200}, bound_addresses {[::]:9200}
[2017-03-02 08:26:56,956][INFO ][node                     ] [elasticsearch-logging-v1-dklui] started
[2017-03-02 08:26:57,157][INFO ][gateway                  ] [elasticsearch-logging-v1-dklui] recovered [0] indices into cluster_state
[2017-03-02 08:27:05,378][INFO ][cluster.metadata         ] [elasticsearch-logging-v1-dklui] [logstash-2017.03.02] creating index, cause [auto(bulk api)], templates [], shards [5]/[1], mappings []
[2017-03-02 08:27:06,360][INFO ][cluster.metadata         ] [elasticsearch-logging-v1-dklui] [logstash-2017.03.01] creating index, cause [auto(bulk api)], templates [], shards [5]/[1], mappings []
[2017-03-02 08:27:07,163][INFO ][cluster.routing.allocation] [elasticsearch-logging-v1-dklui] Cluster health status changed from [RED] to [YELLOW] (reason: [shards started [[logstash-2017.03.01][3], [logstash-2017.03.01][3]] ...]).
[2017-03-02 08:27:07,354][INFO ][cluster.metadata         ] [elasticsearch-logging-v1-dklui] [logstash-2017.03.02] create_mapping [fluentd]
[2017-03-02 08:27:07,988][INFO ][cluster.metadata         ] [elasticsearch-logging-v1-dklui] [logstash-2017.03.01] create_mapping [fluentd]
[2017-03-02 08:27:09,578][INFO ][cluster.routing.allocation] [elasticsearch-logging-v1-dklui] Cluster health status changed from [YELLOW] to [GREEN] (reason: [shards started [[logstash-2017.03.02][4]] ...]).

elasticsearch logging启动运行ok!

五、启动kibana

有了elasticsearch logging的“前车之鉴”,这次我们也把上面新创建的serviceaccount:k8s-efk显式赋值给kibana-controller.yaml:

//kibana-controller.yaml
... ...
spec:
      serviceAccount: k8s-efk
      containers:
      - name: kibana-logging
        image: bigwhite/kibana:v4.6.1-1
        resources:
          # keep request = limit to keep this container in guaranteed class
          limits:
            cpu: 100m
          #requests:
          #  cpu: 100m
        env:
          - name: "ELASTICSEARCH_URL"
            value: "http://elasticsearch-logging:9200"
          - name: "KIBANA_BASE_URL"
            value: "/api/v1/proxy/namespaces/kube-system/services/kibana-logging"
        ports:
        - containerPort: 5601
          name: ui
          protocol: TCP
... ...

启动kibana,并观察pod日志:

# kubectl create -f kibana-controller.yaml
# kubectl create -f kibana-service.yaml
# kubectl logs -f kibana-logging-3604961973-jby53 -n kube-system
ELASTICSEARCH_URL=http://elasticsearch-logging:9200
server.basePath: /api/v1/proxy/namespaces/kube-system/services/kibana-logging
{"type":"log","@timestamp":"2017-03-02T08:30:15Z","tags":["info","optimize"],"pid":6,"message":"Optimizing and caching bundles for kibana and statusPage. This may take a few minutes"}

kibana缓存着实需要一段时间,请耐心等待!可能是几分钟。之后你将会看到如下日志:

# kubectl logs -f kibana-logging-3604961973-jby53 -n kube-system
ELASTICSEARCH_URL=http://elasticsearch-logging:9200
server.basePath: /api/v1/proxy/namespaces/kube-system/services/kibana-logging
{"type":"log","@timestamp":"2017-03-02T08:30:15Z","tags":["info","optimize"],"pid":6,"message":"Optimizing and caching bundles for kibana and statusPage. This may take a few minutes"}
{"type":"log","@timestamp":"2017-03-02T08:40:04Z","tags":["info","optimize"],"pid":6,"message":"Optimization of bundles for kibana and statusPage complete in 588.60 seconds"}
{"type":"log","@timestamp":"2017-03-02T08:40:04Z","tags":["status","plugin:kibana@1.0.0","info"],"pid":6,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-03-02T08:40:05Z","tags":["status","plugin:elasticsearch@1.0.0","info"],"pid":6,"state":"yellow","message":"Status changed from uninitialized to yellow - Waiting for Elasticsearch","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-03-02T08:40:05Z","tags":["status","plugin:kbn_vislib_vis_types@1.0.0","info"],"pid":6,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-03-02T08:40:05Z","tags":["status","plugin:markdown_vis@1.0.0","info"],"pid":6,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-03-02T08:40:05Z","tags":["status","plugin:metric_vis@1.0.0","info"],"pid":6,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-03-02T08:40:06Z","tags":["status","plugin:spyModes@1.0.0","info"],"pid":6,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-03-02T08:40:06Z","tags":["status","plugin:statusPage@1.0.0","info"],"pid":6,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-03-02T08:40:06Z","tags":["status","plugin:table_vis@1.0.0","info"],"pid":6,"state":"green","message":"Status changed from uninitialized to green - Ready","prevState":"uninitialized","prevMsg":"uninitialized"}
{"type":"log","@timestamp":"2017-03-02T08:40:06Z","tags":["listening","info"],"pid":6,"message":"Server running at http://0.0.0.0:5601"}
{"type":"log","@timestamp":"2017-03-02T08:40:11Z","tags":["status","plugin:elasticsearch@1.0.0","info"],"pid":6,"state":"yellow","message":"Status changed from yellow to yellow - No existing Kibana index found","prevState":"yellow","prevMsg":"Waiting for Elasticsearch"}
{"type":"log","@timestamp":"2017-03-02T08:40:14Z","tags":["status","plugin:elasticsearch@1.0.0","info"],"pid":6,"state":"green","message":"Status changed from yellow to green - Kibana index ready","prevState":"yellow","prevMsg":"No existing Kibana index found"}

接下来,通过浏览器访问下面地址就可以访问kibana的web页面了,注意:Kinaba的web页面加载也需要一段时间。

https://{API Server external IP}:{API Server secure port}/api/v1/proxy/namespaces/kube-system/services/kibana-logging/app/kibana#/settings/indices/

下面是创建一个index(相当于mysql中的一个database)页面:

img{512x368}

取消“Index contains time-based events”,然后点击“Create”即可创建一个Index。

点击页面上的”Setting” -> “Status”,可以查看当前elasticsearch logging的整体状态,如果一切ok,你将会看到下图这样的页面:

img{512x368}

创建Index后,可以在Discover下看到ElasticSearch logging中汇聚的日志:

img{512x368}

六、小结

以上就是在Kubernetes 1.3.7集群上安装Fluentd和ElasticSearch stack,实现kubernetes cluster level logging的过程。在使用kubeadm安装的Kubernetes 1.5.1环境下安装这些,则基本不会遇到上述这些问题。

另外ElasticSearch logging默认挂载的volume是emptyDir,实验用可以。但要部署在生产环境,必须换成Persistent Volume,比如:CephRBD

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