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Version: 3.2

Automatically rebalance Portworx storage pools in GCP Anthos

Summary and Key concepts

Summary:​

This article explains how to use Portworx Autopilot to automatically rebalance storage pools when they deviate from average provisioned or used space across the cluster. Autopilot monitors storage metrics and triggers rebalancing actions when specific conditions are met, such as when a storage pool's provisioned or used space deviates by more than 20% from the mean. Two example Autopilot rules are provided: one using mean deviation across storage pools and another using absolute values. The steps also include creating PVCs and testing the rebalancing rule in a Kubernetes environment by pinning volumes to a single node to observe how Autopilot redistributes the volumes across the cluster.

Kubernetes Concepts:​

  • PersistentVolumeClaim (PVC): A request for storage by a Kubernetes user, which in this example, triggers storage pool rebalancing.
  • StorageClass: Specifies how storage is provisioned in Kubernetes. The article provides an example StorageClass that pins volumes to a single Portworx node.

Portworx Concepts:​

  • Autopilot: Automates storage management tasks such as expanding or rebalancing storage pools when they exceed defined thresholds.
  • Storage Pool: A Portworx construct representing a collection of storage resources, which Autopilot can scale or rebalance.

You can use Autopilot to rebalance Portworx storage pools automatically when they begin to run out of space.

Autopilot monitors the metrics in your cluster (for example, via Prometheus) and detects conditions that require rebalancing of existing volumes in the cluster.

Prerequisites​

  • Autopilot version: 1.3.0 or newer

Examples​

The following example Autopilot rule will rebalance all storage pools which meet either of following conditions:

  • Pool's provision space is over 20% or under 20% of mean value across pools
  • Pool's used space is over 20% or under 20% of mean value across pools
apiVersion: autopilot.libopenstorage.org/v1alpha1
kind: AutopilotRule
metadata:
  name: pool-rebalance
spec:
  conditions:
    requiredMatches: 1
    expressions:
    - keyAlias: PoolProvDeviationPerc
      operator: NotInRange
      values:
        - "-20"
        - "20"
    - keyAlias: PoolUsageDeviationPerc
      operator: NotInRange
      values:
        - "-20"
        - "20"
  actions:
    - name: "openstorage.io.action.storagepool/rebalance"

The AutopilotRule spec consists of two important sections: conditions and actions.

  • The conditions section establishes threshold criteria dictating when the rule must perform its action. In this example, that criteria contains 2 formulas:

    • PoolProvDeviationPerc is an alias for a Prometheus query that gives a storage pool's provisioned space deviation percentage relative to other pools in the cluster.
      • The NotInRange operator checks if the value of the metric is outside the range specified in the values.
        • In this case, the condition is met when the pool's provisioned space goes over 20% or under 20% compared to mean value across pools.
        • For example, if a particular pool's provisioned space is 25% lower compared to mean provisioned space across all pools in the cluster, then the condition is met.
    • PoolUsageDeviationPerc is an alias for a prometheus query that gives a storage pool's used space deviation percentage relative to other pools in the cluster.
      • The NotInRange operator checks if the value of the metric is outside the range specified in the values.
        • In this case, the condition is met when the pool's used space goes over 20% or under 20% compared to mean value across pools.
        • For example, if a particular pool's used space is 25% higher compared to mean used space across all pools in the cluster, then the condition is met.
    • requiredMatches indicates that only one of the expressions need to match for the conditions to be considered as being met.

  • The actions section in the above specs specify what action Portworx performs when the conditions are met. The action name here is the Storage Pool rebalance action.

Implement the Autopilot rule​

Perform the following steps to deploy this example.

Create specs​

note
  • Other rebalance rules: If you have other AutopilotRules in the cluster for pool rebalance, Portworx, Inc. recommends you delete them for this test. This will make it easier to confirm that the rule in this example was triggered.
  • TESTING ONLY: The specs below all volumes to initially land on a single Portworx node. This is done so that we can test the rebalance rule later on to rebalance the volumes across all nodes.

Application and PVC specs​

Create the storage and application spec files:

  1. Identify the ID of a single Portworx node in the cluster.

    List the cluster nodes and pick the first node. In this example, we will pick the first node xxxxxxxx-xxxx-xxxx-xxxx-75339f2ada81 in the list.

    PX_POD=$(kubectl get pods -l name=portworx -n portworx -o jsonpath='{.items[0].metadata.name}')
    kubectl exec $PX_POD -n portworx -- /opt/pwx/bin/pxctl status
    Cluster ID: px-autopilot-demo
    Cluster UUID: xxxxxxxx-xxxx-xxxx-xxxx-a0534c91a417
    Status: OK

    Nodes in the cluster:
    ID                                      SCHEDULER_NODE_NAME                     DATA IP         CPU             MEM TOTAL       MEM FREE        CONTAINERS      VERSION                 Kernel                  OS                      STATUS
    xxxxxxxx-xxxx-xxxx-xxxx-75339f2ada81    xxxxxxxx-xxxx-xxxx-xxxx-2ff85c418afe    X.X.X.1      2.641509        8.4 GB          7.0 GB          N/A             2.6.0.0-d88b8c6         4.15.0-72-generic       Ubuntu 16.04.6 LTS      Online
    xxxxxxxx-xxxx-xxxx-xxxx-5431da0e8b0a    xxxxxxxx-xxxx-xxxx-xxxx-c0ae5965deac    X.X.X.3      3.666245        8.4 GB          6.9 GB          N/A             2.6.0.0-d88b8c6         4.15.0-72-generic       Ubuntu 16.04.6 LTS      Online
    xxxxxxxx-xxxx-xxxx-xxxx-63b06936395b    xxxxxxxx-xxxx-xxxx-xxxx-2b8561e244eb    X.X.X.2      3.530895        8.4 GB          7.0 GB          N/A             2.6.0.0-d88b8c6         4.15.0-72-generic       Ubuntu 16.04.6 LTS      Online

  2. Create postgres-sc.yaml and place the following content inside it.

    ##### Portworx storage class
    apiVersion: storage.k8s.io/v1
    kind: StorageClass
    metadata:
      name: postgres-pgbench-sc
    provisioner: pxd.portworx.com
    parameters:
      repl: "1"
      nodes: "xxxxxxxx-xxxx-xxxx-xxxx-75339f2ada81"
    allowVolumeExpansion: true
note

Notice how the nodes section pin the volumes from this StorageClass to initially land only on xxxxxxxx-xxxx-xxxx-xxxx-75339f2ada81. You should use this for testing only, and you must change the value to suit your environment.

  1. Create postgres-vol.yaml and place the following content inside it.

    kind: PersistentVolumeClaim
    apiVersion: v1
    metadata:
      name: pgbench-data
      labels:
        app: postgres
    spec:
      storageClassName: postgres-pgbench-sc
      accessModes:
        - ReadWriteOnce
      resources:
        requests:
          storage: 30Gi

    You will not deploy any application pod using this PVC. This tutorial only demonstrates rebalancing the pools.

  2. Create the StorageClass and create 3 PVCs in 3 unique namespaces:

    kubectl apply -f postgres-sc.yaml

    for i in {1..3}; do
      kubectl create ns pg$i || true
      kubectl apply -f postgres-vol.yaml -n pg$i
    done

  3. Wait until all PVCs are bound and confirm that one pool has all the volumes.

    The output from the following commands should show all PVCs as bound:

    kubectl get pvc -n pg1
    kubectl get pvc -n pg2
    kubectl get pvc -n pg3

    The output from this command should show that the provisioned space for the pool for the Portworx node that you selected in Step 1 has gone up by 90Gi since all the volumes are created there. You will see this in the PROVISIONED column of the output.

    kubectl exec $PX_POD -n portworx -- /opt/pwx/bin/pxctl cluster provision-status --output-type wide

AutopilotRule spec​

Once you've created the PVCs, you can create an AutopilotRule to rebalance the pools.

  1. Create a YAML spec for the autopilot rule named autopilotrule-pool-rebalance-example.yaml and place the following content inside it:

    apiVersion: autopilot.libopenstorage.org/v1alpha1
    kind: AutopilotRule
    metadata:
      name: pool-rebalance
    spec:
      conditions:
        requiredMatches: 1
        expressions:
        - keyAlias: PoolProvDeviationPerc
          operator: NotInRange
          values:
            - "-20"
            - "20"
        - keyAlias: PoolUsageDeviationPerc
          operator: NotInRange
          values:
            - "-20"
            - "20"
      actions:
        - name: "openstorage.io.action.storagepool/rebalance"

  2. Apply the rule:

    kubectl apply -f autopilotrule-pool-rebalance-example.yaml

Monitor​

Now that you've created the rule, Autopilot will now detect that one specific pool is over-provisioned and it will start rebalancing the 3 volumes across the pools.

Enter the following command to retrieve all the events generated for the pool-rebalance rule:

kubectl get events --field-selector involvedObject.kind=AutopilotRule,involvedObject.name=pool-rebalance --all-namespaces --sort-by .lastTimestamp

You should see events that will show the rule has triggered. About 30 seconds later, the rebalance actions will begin.

Once you see actions have begun on the pools, you can use pxctl to again check the cluster provision status.

Below should now show that the provisioned space for all your pools are balanced and spread evenly. You will see this in the PROVISIONED column of the output.

kubectl exec $PX_POD -n portworx -- /opt/pwx/bin/pxctl cluster provision-status --output-type wide
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