主页
产品
OpenShift Container Platform
4.5
Metering
4.3. Configuring persistent storage

4.3. Configuring persistent storage

Metering requires persistent storage to persist data collected by the Metering Operator and to store the results of reports. A number of different storage providers and storage formats are supported. Select your storage provider and modify the example configuration files to configure persistent storage for your metering installation.

4.3.1. Storing data in Amazon S3
复制链接

Metering can use an existing Amazon S3 bucket or create a bucket for storage.

注意

Metering does not manage or delete any S3 bucket data. You must manually clean up S3 buckets that are used to store metering data.

Procedure

Edit the spec.storage section in the s3-storage.yaml file:

Example s3-storage.yaml file

apiVersion: metering.openshift.io/v1
kind: MeteringConfig
metadata:
  name: "operator-metering"
spec:
  storage:
    type: "hive"
    hive:
      type: "s3"
      s3:
        bucket: "bucketname/path/" 
        region: "us-west-1" 
        secretName: "my-aws-secret" 
        # Set to false if you want to provide an existing bucket, instead of
        # having metering create the bucket on your behalf.
        createBucket: true

apiVersion: metering.openshift.io/v1
kind: MeteringConfig
metadata:
  name: "operator-metering"
spec:
  storage:
    type: "hive"
    hive:
      type: "s3"
      s3:
        bucket: "bucketname/path/"


        region: "us-west-1"


        secretName: "my-aws-secret"


        # Set to false if you want to provide an existing bucket, instead of
        # having metering create the bucket on your behalf.
        createBucket: true

Copy to Clipboard

Toggle word wrap

1: Specify the name of the bucket where you would like to store your data. Optional: Specify the path within the bucket.
2: Specify the region of your bucket.
3: The name of a secret in the metering namespace containing the AWS credentials in the data.aws-access-key-id and data.aws-secret-access-key fields. See the example Secret object below for more details.
4: Set this field to false if you want to provide an existing S3 bucket, or if you do not want to provide IAM credentials that have CreateBucket permissions.

Use the following Secret object as a template:

Example AWS Secret object

apiVersion: v1
kind: Secret
metadata:
  name: my-aws-secret
data:
  aws-access-key-id: "dGVzdAo="
  aws-secret-access-key: "c2VjcmV0Cg=="

apiVersion: v1
kind: Secret
metadata:
  name: my-aws-secret
data:
  aws-access-key-id: "dGVzdAo="
  aws-secret-access-key: "c2VjcmV0Cg=="

Copy to Clipboard

Toggle word wrap

注意

The values of the aws-access-key-id and aws-secret-access-key must be base64 encoded.

Create the secret:

oc create secret -n openshift-metering generic my-aws-secret \
  --from-literal=aws-access-key-id=my-access-key \
  --from-literal=aws-secret-access-key=my-secret-key

$ oc create secret -n openshift-metering generic my-aws-secret \
  --from-literal=aws-access-key-id=my-access-key \
  --from-literal=aws-secret-access-key=my-secret-key

Copy to Clipboard

Toggle word wrap

注意

This command automatically base64 encodes your aws-access-key-id and aws-secret-access-key values.

The aws-access-key-id and aws-secret-access-key credentials must have read and write access to the bucket. The following aws/read-write.json file shows an IAM policy that grants the required permissions:

Example aws/read-write.json file

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "1",
            "Effect": "Allow",
            "Action": [
                "s3:AbortMultipartUpload",
                "s3:DeleteObject",
                "s3:GetObject",
                "s3:HeadBucket",
                "s3:ListBucket",
                "s3:ListMultipartUploadParts",
                "s3:PutObject"
            ],
            "Resource": [
                "arn:aws:s3:::operator-metering-data/*",
                "arn:aws:s3:::operator-metering-data"
            ]
        }
    ]
}

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "1",
            "Effect": "Allow",
            "Action": [
                "s3:AbortMultipartUpload",
                "s3:DeleteObject",
                "s3:GetObject",
                "s3:HeadBucket",
                "s3:ListBucket",
                "s3:ListMultipartUploadParts",
                "s3:PutObject"
            ],
            "Resource": [
                "arn:aws:s3:::operator-metering-data/*",
                "arn:aws:s3:::operator-metering-data"
            ]
        }
    ]
}

Copy to Clipboard

Toggle word wrap

If spec.storage.hive.s3.createBucket is set to true or unset in your s3-storage.yaml file, then you should use the aws/read-write-create.json file that contains permissions for creating and deleting buckets:

Example aws/read-write-create.json file

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "1",
            "Effect": "Allow",
            "Action": [
                "s3:AbortMultipartUpload",
                "s3:DeleteObject",
                "s3:GetObject",
                "s3:HeadBucket",
                "s3:ListBucket",
                "s3:CreateBucket",
                "s3:DeleteBucket",
                "s3:ListMultipartUploadParts",
                "s3:PutObject"
            ],
            "Resource": [
                "arn:aws:s3:::operator-metering-data/*",
                "arn:aws:s3:::operator-metering-data"
            ]
        }
    ]
}

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Sid": "1",
            "Effect": "Allow",
            "Action": [
                "s3:AbortMultipartUpload",
                "s3:DeleteObject",
                "s3:GetObject",
                "s3:HeadBucket",
                "s3:ListBucket",
                "s3:CreateBucket",
                "s3:DeleteBucket",
                "s3:ListMultipartUploadParts",
                "s3:PutObject"
            ],
            "Resource": [
                "arn:aws:s3:::operator-metering-data/*",
                "arn:aws:s3:::operator-metering-data"
            ]
        }
    ]
}

Copy to Clipboard

Toggle word wrap

4.3.2. Storing data in S3-compatible storage
复制链接

You can use S3-compatible storage such as Noobaa.

Procedure

Edit the spec.storage section in the s3-compatible-storage.yaml file:

Example s3-compatible-storage.yaml file

apiVersion: metering.openshift.io/v1
kind: MeteringConfig
metadata:
  name: "operator-metering"
spec:
  storage:
    type: "hive"
    hive:
      type: "s3Compatible"
      s3Compatible:
        bucket: "bucketname" 
        endpoint: "http://example:port-number" 
        secretName: "my-aws-secret"

apiVersion: metering.openshift.io/v1
kind: MeteringConfig
metadata:
  name: "operator-metering"
spec:
  storage:
    type: "hive"
    hive:
      type: "s3Compatible"
      s3Compatible:
        bucket: "bucketname"


        endpoint: "http://example:port-number"


        secretName: "my-aws-secret"

Copy to Clipboard

Toggle word wrap

1: Specify the name of your S3-compatible bucket.
2: Specify the endpoint for your storage.
3: The name of a secret in the metering namespace containing the AWS credentials in the data.aws-access-key-id and data.aws-secret-access-key fields. See the example Secret object below for more details.

Use the following Secret object as a template:

Example S3-compatible Secret object

apiVersion: v1
kind: Secret
metadata:
  name: my-aws-secret
data:
  aws-access-key-id: "dGVzdAo="
  aws-secret-access-key: "c2VjcmV0Cg=="

apiVersion: v1
kind: Secret
metadata:
  name: my-aws-secret
data:
  aws-access-key-id: "dGVzdAo="
  aws-secret-access-key: "c2VjcmV0Cg=="

Copy to Clipboard

Toggle word wrap

4.3.3. Storing data in Microsoft Azure
复制链接

To store data in Azure blob storage, you must use an existing container.

Procedure

Edit the spec.storage section in the azure-blob-storage.yaml file:

Example azure-blob-storage.yaml file

apiVersion: metering.openshift.io/v1
kind: MeteringConfig
metadata:
  name: "operator-metering"
spec:
  storage:
    type: "hive"
    hive:
      type: "azure"
      azure:
        container: "bucket1" 
        secretName: "my-azure-secret" 
        rootDirectory: "/testDir"

apiVersion: metering.openshift.io/v1
kind: MeteringConfig
metadata:
  name: "operator-metering"
spec:
  storage:
    type: "hive"
    hive:
      type: "azure"
      azure:
        container: "bucket1"


        secretName: "my-azure-secret"


        rootDirectory: "/testDir"

Copy to Clipboard

Toggle word wrap

1: Specify the container name.
2: Specify a secret in the metering namespace. See the example Secret object below for more details.
3: Optional: Specify the directory where you would like to store your data.

Use the following Secret object as a template:

Example Azure Secret object

apiVersion: v1
kind: Secret
metadata:
  name: my-azure-secret
data:
  azure-storage-account-name: "dGVzdAo="
  azure-secret-access-key: "c2VjcmV0Cg=="

apiVersion: v1
kind: Secret
metadata:
  name: my-azure-secret
data:
  azure-storage-account-name: "dGVzdAo="
  azure-secret-access-key: "c2VjcmV0Cg=="

Copy to Clipboard

Toggle word wrap

Create the secret:

oc create secret -n openshift-metering generic my-azure-secret \
  --from-literal=azure-storage-account-name=my-storage-account-name \
  --from-literal=azure-secret-access-key=my-secret-key

$ oc create secret -n openshift-metering generic my-azure-secret \
  --from-literal=azure-storage-account-name=my-storage-account-name \
  --from-literal=azure-secret-access-key=my-secret-key

Copy to Clipboard

Toggle word wrap

4.3.4. Storing data in Google Cloud Storage
复制链接

To store your data in Google Cloud Storage, you must use an existing bucket.

Procedure

Edit the spec.storage section in the gcs-storage.yaml file:

Example gcs-storage.yaml file

apiVersion: metering.openshift.io/v1
kind: MeteringConfig
metadata:
  name: "operator-metering"
spec:
  storage:
    type: "hive"
    hive:
      type: "gcs"
      gcs:
        bucket: "metering-gcs/test1" 
        secretName: "my-gcs-secret"

apiVersion: metering.openshift.io/v1
kind: MeteringConfig
metadata:
  name: "operator-metering"
spec:
  storage:
    type: "hive"
    hive:
      type: "gcs"
      gcs:
        bucket: "metering-gcs/test1"


        secretName: "my-gcs-secret"

Copy to Clipboard

Toggle word wrap

1: Specify the name of the bucket. You can optionally specify the directory within the bucket where you would like to store your data.
2: Specify a secret in the metering namespace. See the example Secret object below for more details.

Use the following Secret object as a template:

Example Google Cloud Storage Secret object

apiVersion: v1
kind: Secret
metadata:
  name: my-gcs-secret
data:
  gcs-service-account.json: "c2VjcmV0Cg=="

apiVersion: v1
kind: Secret
metadata:
  name: my-gcs-secret
data:
  gcs-service-account.json: "c2VjcmV0Cg=="

Copy to Clipboard

Toggle word wrap

Create the secret:

oc create secret -n openshift-metering generic my-gcs-secret \
  --from-file gcs-service-account.json=/path/to/my/service-account-key.json

$ oc create secret -n openshift-metering generic my-gcs-secret \
  --from-file gcs-service-account.json=/path/to/my/service-account-key.json

Copy to Clipboard

Toggle word wrap

4.3.5. Storing data in shared volumes
复制链接

Metering does not configure storage by default. However, you can use any ReadWriteMany persistent volume (PV) or any storage class that provisions a ReadWriteMany PV for metering storage.

注意

NFS is not recommended to use in production. Using an NFS server on RHEL as a storage back end can fail to meet metering requirements and to provide the performance that is needed for the Metering Operator to work appropriately.

Other NFS implementations on the marketplace might not have these issues, such as a Parallel Network File System (pNFS). pNFS is an NFS implementation with distributed and parallel capability. Contact the individual NFS implementation vendor for more information on any testing that was possibly completed against OpenShift Container Platform core components.

Procedure

Modify the shared-storage.yaml file to use a ReadWriteMany persistent volume for storage:

apiVersion: metering.openshift.io/v1
kind: MeteringConfig
metadata:
  name: "operator-metering"
spec:
  storage:
    type: "hive"
    hive:
      type: "sharedPVC"
      sharedPVC:
        claimName: "metering-nfs" 
        # Uncomment the lines below to provision a new PVC using the specified storageClass. 
        # createPVC: true
        # storageClass: "my-nfs-storage-class"
        # size: 5Gi

apiVersion: metering.openshift.io/v1
kind: MeteringConfig
metadata:
  name: "operator-metering"
spec:
  storage:
    type: "hive"
    hive:
      type: "sharedPVC"
      sharedPVC:
        claimName: "metering-nfs"


        # Uncomment the lines below to provision a new PVC using the specified storageClass.


        # createPVC: true
        # storageClass: "my-nfs-storage-class"
        # size: 5Gi

Copy to Clipboard

Toggle word wrap

Select one of the configuration options below:

1: Set storage.hive.sharedPVC.claimName to the name of an existing ReadWriteMany persistent volume claim (PVC). This configuration is necessary if you do not have dynamic volume provisioning or want to have more control over how the persistent volume is created.
2: Set storage.hive.sharedPVC.createPVC to true and set the storage.hive.sharedPVC.storageClass to the name of a storage class with ReadWriteMany access mode. This configuration uses dynamic volume provisioning to create a volume automatically.

Create the following resource objects that are required to deploy an NFS server for metering. Use the oc create -f <file-name>.yaml command to create the object YAML files.

Configure a PersistentVolume resource object:

Example nfs_persistentvolume.yaml file

apiVersion: v1
kind: PersistentVolume
metadata:
  name: nfs
  labels:
    role: nfs-server
spec:
  capacity:
    storage: 5Gi
  accessModes:
  - ReadWriteMany
  storageClassName: nfs-server 
  nfs:
    path: "/"
    server: REPLACEME
  persistentVolumeReclaimPolicy: Delete

apiVersion: v1
kind: PersistentVolume
metadata:
  name: nfs
  labels:
    role: nfs-server
spec:
  capacity:
    storage: 5Gi
  accessModes:
  - ReadWriteMany
  storageClassName: nfs-server


  nfs:
    path: "/"
    server: REPLACEME
  persistentVolumeReclaimPolicy: Delete

Copy to Clipboard

Toggle word wrap

1: Must exactly match the [kind: StorageClass].metadata.name field value.

Configure a Pod resource object with the nfs-server role:

Example nfs_server.yaml file

apiVersion: v1
kind: Pod
metadata:
  name: nfs-server
  labels:
    role: nfs-server
spec:
  containers:
    - name: nfs-server
      image: <image_name> 
      imagePullPolicy: IfNotPresent
      ports:
        - name: nfs
          containerPort: 2049
      securityContext:
        privileged: true
      volumeMounts:
      - mountPath: "/mnt/data"
        name: local
  volumes:
    - name: local
      emptyDir: {}

apiVersion: v1
kind: Pod
metadata:
  name: nfs-server
  labels:
    role: nfs-server
spec:
  containers:
    - name: nfs-server
      image: <image_name>


      imagePullPolicy: IfNotPresent
      ports:
        - name: nfs
          containerPort: 2049
      securityContext:
        privileged: true
      volumeMounts:
      - mountPath: "/mnt/data"
        name: local
  volumes:
    - name: local
      emptyDir: {}

Copy to Clipboard

Toggle word wrap

1: Install your NFS server image.

Configure a Service resource object with the nfs-server role:

Example nfs_service.yaml file

apiVersion: v1
kind: Service
metadata:
  name: nfs-service
  labels:
    role: nfs-server
spec:
  ports:
  - name: 2049-tcp
    port: 2049
    protocol: TCP
    targetPort: 2049
  selector:
    role: nfs-server
  sessionAffinity: None
  type: ClusterIP

apiVersion: v1
kind: Service
metadata:
  name: nfs-service
  labels:
    role: nfs-server
spec:
  ports:
  - name: 2049-tcp
    port: 2049
    protocol: TCP
    targetPort: 2049
  selector:
    role: nfs-server
  sessionAffinity: None
  type: ClusterIP

Copy to Clipboard

Toggle word wrap

Configure a StorageClass resource object:

Example nfs_storageclass.yaml file

apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: nfs-server 
provisioner: example.com/nfs
parameters:
  archiveOnDelete: "false"
reclaimPolicy: Delete
volumeBindingMode: Immediate

apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: nfs-server


provisioner: example.com/nfs
parameters:
  archiveOnDelete: "false"
reclaimPolicy: Delete
volumeBindingMode: Immediate

Copy to Clipboard

Toggle word wrap

1: Must exactly match the [kind: PersistentVolume].spec.storageClassName field value.

警告

Configuration of your NFS storage, and any relevant resource objects, will vary depending on the NFS server image that you use for metering storage.

返回顶部

4.3. Configuring persistent storage

4.3.1. Storing data in Amazon S3
复制链接

4.3.2. Storing data in S3-compatible storage
复制链接

4.3.3. Storing data in Microsoft Azure
复制链接

4.3.4. Storing data in Google Cloud Storage
复制链接

4.3.5. Storing data in shared volumes
复制链接

学习

尝试、购买和销售

社区

关于红帽文档

让开源更具包容性

關於紅帽

Theme

Red Hat legal and privacy links

Red Hat legal and privacy links

4.3. Configuring persistent storage

4.3.1. Storing data in Amazon S3复制链接链接已复制到粘贴板!

4.3.2. Storing data in S3-compatible storage复制链接链接已复制到粘贴板!

4.3.3. Storing data in Microsoft Azure复制链接链接已复制到粘贴板!

4.3.4. Storing data in Google Cloud Storage复制链接链接已复制到粘贴板!

4.3.5. Storing data in shared volumes复制链接链接已复制到粘贴板!

学习

尝试、购买和销售

社区

关于红帽文档

让开源更具包容性

關於紅帽

Theme

Red Hat legal and privacy links

Red Hat legal and privacy links

4.3.1. Storing data in Amazon S3
复制链接

4.3.2. Storing data in S3-compatible storage
复制链接

4.3.3. Storing data in Microsoft Azure
复制链接

4.3.4. Storing data in Google Cloud Storage
复制链接

4.3.5. Storing data in shared volumes
复制链接