Automatically expand Portworx storage pools

You can use Autopilot to expand Portworx storage pools automatically when they begin to run out of space. Autopilot monitors the metrics in your cluster (e.g., via Prometheus) and detects high usage conditions. Once high usage conditions occur, Autopilot communicates with Portworx to resize the pool.

Autopilot uses Portworx APIs to expand storage pools, and these APIs currently support the following cloud providers:

• Azure
• AWS
• VMware vSphere

Prerequisites

• Portworx version: Autopilot uses Portworx APIs to expand storage pools which is available only in Portworx 2.3.1 and above
• Portworx cloud drives: Your Portworx installation must use one of the supported cloud drives where Portworx provisions the backing drives using the cloud provider
• Autopilot version: 1.0.0 and above

Example

note

You can also use the resize-disk scale type to expand Portworx storage pools. See the Autopilot reference documentation for details on each parameter for the Autopilot expand action.

The following example Autopilot rule uses the add-disk scale type to expand a 250GiB Portworx storage pool composed of a single 250GiB drive by 100% whenever its available capacity is lower than 50% up to a maximum volume size of 2TB:

apiVersion: autopilot.libopenstorage.org/v1alpha1
kind: AutopilotRule
metadata:
  name: pool-expand
spec:
  enforcement: required
  ##### conditions are the symptoms to evaluate. All conditions are AND'ed
  conditions:
    expressions:
    # pool available capacity less than 50%
    - key: "100 * ( px_pool_stats_available_bytes/ px_pool_stats_total_bytes)"
      operator: Lt
      values:
        - "50"
    # pool total capacity should not exceed 2TB
    - key: "px_pool_stats_total_bytes/(1024*1024*1024)"
      operator: Lt
      values:
       - "2000"
  ##### action to perform when condition is true
  actions:
    - name: "openstorage.io.action.storagepool/expand"
      params:
        # resize pool by scalepercentage of current size
        scalepercentage: "50"
        # when scaling, add disks to the pool
        scaletype: "add-disk"

Consider the key sections in this spec: 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:

• 100 * ( px_pool_stats_available_bytes/ px_pool_stats_total_bytes) gives the pool available percentage and the Lt operator puts a condition that pool available capacity percentage should be lower 50%.
• px_pool_stats_total_bytes/(1024*1024*1024) gives the total pool capacity in GiB, and the Lt operator to caps it to 400GiB.`

Conditions are combined using AND logic, requiring all conditions to be true for the rule to trigger.

The actions section specifies what action Portworx performs when the conditions are met. Action parameters modify action behavior, and different actions contain different action parameters.

Perform the following steps to deploy this example:

Create specs

note

The specs below create an application that writes 300 GiB of data to a 400 GiB volume. If your Storage pools are larger than that, you must change these numbers to ensure the capacity condition triggers.

Application and PVC specs

First, create the storage and application spec files:

1. 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: kubernetes.io/portworx-volume
   parameters:
     repl: "2"
   allowVolumeExpansion: true
   

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

   kind: PersistentVolumeClaim
   apiVersion: v1
   metadata:
     name: pgbench-data
   spec:
     storageClassName: postgres-pgbench-sc
     accessModes:
       - ReadWriteOnce
     resources:
       requests:
         storage: 400Gi
   ---
   kind: PersistentVolumeClaim
   apiVersion: v1
   metadata:
     name: pgbench-state
   spec:
     storageClassName: postgres-pgbench-sc
     accessModes:
       - ReadWriteOnce
     resources:
       requests:
         storage: 1Gi

3. Create postgres-app.yaml and place the following content inside it.

   The application in this example is a PostgreSQL database with a pgbench sidecar. The SIZE environment variable in this spec instructs pgbench to write 300GiB of data to the volume. Since the volume is 400GiB in size, Autopilot will resize the storage pool when the conditions threshold is crossed.

   apiVersion: apps/v1
   kind: Deployment
   metadata:
     name: pgbench
     labels:
       app: pgbench
   spec:
     selector:
       matchLabels:
         app: pgbench
     strategy:
       rollingUpdate:
         maxSurge: 1
         maxUnavailable: 1
       type: RollingUpdate
     replicas: 1
     template:
       metadata:
         labels:
           app: pgbench
       spec:
         schedulerName: stork
         containers:
           - image: postgres:9.5
             name: postgres
             ports:
             - containerPort: 5432
             env:
             - name: POSTGRES_USER
               value: pgbench
             - name: POSTGRES_PASSWORD
               value: superpostgres
             - name: PGBENCH_PASSWORD
               value: superpostgres
             - name: PGDATA
               value: /var/lib/postgresql/data/pgdata
             volumeMounts:
             - mountPath: /var/lib/postgresql/data
               name: pgbenchdb
           - name: pgbench
             image: portworx/torpedo-pgbench:latest
             imagePullPolicy: "Always"
             env:
               - name: PG_HOST
                 value: 127.0.0.1
               - name: PG_USER
                 value: pgbench
               - name: SIZE
                 value: "300"
             volumeMounts:
             - mountPath: /var/lib/postgresql/data
               name: pgbenchdb
             - mountPath: /pgbench
               name: pgbenchstate
         volumes:
         - name: pgbenchdb
           persistentVolumeClaim:
             claimName: pgbench-data
         - name: pgbenchstate
           persistentVolumeClaim:
             claimName: pgbench-state

AutopilotRule spec

Once you've created your storage and application specs, you can create an AutopilotRule that controls them.

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

apiVersion: autopilot.libopenstorage.org/v1alpha1
kind: AutopilotRule
metadata:
  name: pool-expand
spec:
  enforcement: required
  ##### conditions are the symptoms to evaluate. All conditions are AND'ed
  conditions:
    expressions:
    # pool available capacity less than 40%
    - key: "100 * ( px_pool_stats_available_bytes/ px_pool_stats_total_bytes)"
      operator: Lt
      values:
        - "50"
    # volume total capacity should not exceed 400GiB
    - key: "px_pool_stats_total_bytes/(1024*1024*1024)"
      operator: Lt
      values:
       - "400"
  ##### action to perform when condition is true
  actions:
    - name: "openstorage.io.action.storagepool/expand"
      params:
        # resize pool by scalepercentage of current size
        scalepercentage: "50"
        # when scaling, add disks to the pool
        scaletype: "add-disk"

Apply specs

Once you've designed your specs, deploy them.

kubectl apply -f autopilotrule-pool-expand-example.yaml
kubectl apply -f postgres-sc.yaml
kubectl apply -f postgres-vol.yaml
kubectl apply -f postgres-app.yaml

Monitor

Observe how the pgbench pod starts filling up the pgbench-data PVCs and, by extension, the underlying Portworx storage pools. As the pool usage exceeds 50%, Autopilot resizes the storage pools.

You can enter the following command to retrieve all the events generated for the pool-expand rule:

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

Known issues

Portworx is aware of the following known issues:

• When an autopilot pod restarts, it does not save previous state of resizing pools. This causes autopilot to trigger resize operations again for the same pools.