KubeDB

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Storage Autoscaling of a Qdrant Database

This guide will show you how to use KubeDB to autoscale the storage of a Qdrant database.

Before You Begin

  • At first, you need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. If you do not already have a cluster, you can create one by using kind.

  • Install KubeDB Community, Enterprise and Autoscaler operator in your cluster following the steps here.

  • Install Metrics Server from here.

  • Install Prometheus from here.

  • You must have a StorageClass that supports volume expansion.

  • You should be familiar with the following KubeDB concepts:

To keep everything isolated, we are going to use a separate namespace called demo throughout this tutorial.

$ kubectl create ns demo
namespace/demo created

Storage Autoscaling of Database

At first, verify that your cluster has a storage class that supports volume expansion:

$ kubectl get storageclass
NAME                   PROVISIONER             RECLAIMPOLICY   VOLUMEBINDINGMODE      ALLOWVOLUMEEXPANSION   AGE
local-path (default)   rancher.io/local-path   Delete          WaitForFirstConsumer   false                  28d
longhorn (default)     driver.longhorn.io      Delete          Immediate              true                   25d
longhorn-static        driver.longhorn.io      Delete          Immediate              true                   28d

We can see from the output that longhorn storage class has ALLOWVOLUMEEXPANSION set to true. We will use it for this tutorial.

Now, we are going to deploy a Qdrant database using a supported version by KubeDB operator. Then we are going to apply QdrantAutoscaler to set up autoscaling.

Deploy Qdrant Database

In this section, we are going to deploy a Qdrant database with version 1.17.0. Then, in the next section we will set up autoscaling for this database using QdrantAutoscaler CRD. Below is the YAML of the Qdrant CR that we are going to create:

apiVersion: kubedb.com/v1alpha2
kind: Qdrant
metadata:
  name: qdrant-sample
  namespace: demo
spec:
  version: "1.17.0"
  replicas: 3
  storageType: Durable
  storage:
    storageClassName: "longhorn"
    accessModes:
    - ReadWriteOnce
    resources:
      requests:
        storage: 1Gi
  deletionPolicy: WipeOut

Let’s create the Qdrant CR we have shown above:

$ kubectl apply -f https://github.com/kubedb/docs/raw/v2026.4.27/docs/examples/qdrant/autoscaler/storage/qdrant.yaml
qdrant.kubedb.com/qdrant-sample created

Now, wait until qdrant-sample has status Ready:

$ kubectl get qdrant -n demo
NAME            VERSION   STATUS   AGE
qdrant-sample   1.17.0    Ready    101s

Let’s check the volume size from the Petset and from the persistent volumes:

$ kubectl get petset -n demo qdrant-sample -o json | jq '.spec.volumeClaimTemplates[].spec.resources.requests.storage'
"1Gi"

$ kubectl get pv -o custom-columns=NAME:.metadata.name,CAPACITY:.spec.capacity.storage,STORAGECLASS:.spec.storageClassName,CLAIM:.spec.claimRef.name | grep qdrant-sample
pvc-31485d1d-5048-4dc2-a2c3-18910b27b661   1Gi        longhorn       data-qdrant-sample-0
pvc-683755b9-023d-4d36-8318-8a22d5b79acb   1Gi        longhorn       data-qdrant-sample-1
pvc-d494f0aa-41b8-458d-ab56-39946c9b9bfe   1Gi        longhorn       data-qdrant-sample-2

You can see the Petset has 1GB storage and the capacity of all the persistent volumes is also 1GB.

We are now ready to apply the QdrantAutoscaler CRD to set up storage autoscaling for this database.

Storage Autoscaling

Here, we are going to set up storage autoscaling using a QdrantAutoscaler Object.

Create QdrantAutoscaler Object

In order to set up storage autoscaling for this database, we have to create a QdrantAutoscaler CR with our desired configuration. Below is the YAML of the QdrantAutoscaler object that we are going to create:

apiVersion: autoscaling.kubedb.com/v1alpha1
kind: QdrantAutoscaler
metadata:
  name: qdrant-as-storage
  namespace: demo
spec:
  databaseRef:
    name: qdrant-sample
  storage:
    node:
      trigger: "On"
      usageThreshold: 20
      scalingThreshold: 20
      expansionMode: "Online"

Here,

  • spec.databaseRef.name specifies that we are performing storage autoscaling on qdrant-sample database.
  • spec.storage.node.trigger specifies that storage autoscaling is enabled for the Qdrant nodes.
  • spec.storage.node.usageThreshold specifies the storage usage threshold — if storage usage exceeds 20%, storage autoscaling will be triggered.
  • spec.storage.node.scalingThreshold specifies the scaling threshold — storage will be scaled to 20% of the current amount.
  • spec.storage.node.expansionMode specifies the expansion mode of the volume expansion QdrantOpsRequest created by QdrantAutoscaler. longhorn supports online volume expansion so expansionMode is set to Online.

Let’s create the QdrantAutoscaler CR we have shown above:

$ kubectl apply -f https://github.com/kubedb/docs/raw/v2026.4.27/docs/examples/qdrant/autoscaler/storage/qdrant-as-storage.yaml
qdrantautoscaler.autoscaling.kubedb.com/qdrant-as-storage created

Verify Autoscaler is set up successfully

Let’s check that the QdrantAutoscaler resource is created successfully:

$ kubectl get qdrantautoscaler -n demo
NAME                AGE
qdrant-as-storage   33s

$ kubectl describe qdrantautoscaler qdrant-as-storage -n demo
Name:         qdrant-as-storage
Namespace:    demo
Labels:       <none>
Annotations:  <none>
API Version:  autoscaling.kubedb.com/v1alpha1
Kind:         QdrantAutoscaler
Spec:
  Database Ref:
    Name:  qdrant-sample
  Storage:
    Node:
      Expansion Mode:   Online
      Scaling Threshold:  20
      Trigger:            On
      Usage Threshold:    20
Events:                   <none>

So, the QdrantAutoscaler resource is created successfully. The operator will now continuously watch the storage usage of the Qdrant pods. When the usage crosses the usageThreshold, it will create a QdrantOpsRequest to expand the storage.

Now, for this demo, we are going to manually fill up the persistent volume to exceed the usageThreshold using the dd command to see if storage autoscaling is working:

$ kubectl exec -n demo qdrant-sample-0 -- df -h /qdrant/storage
Filesystem                                              Size  Used Avail Use% Mounted on
/dev/longhorn/pvc-9d79a391-6777-4be5-8f9e-0139d178aada  974M  296K  958M   1% /qdrant/storage

$ kubectl exec -n demo qdrant-sample-0 -- bash -c "dd if=/dev/zero of=/qdrant/storage/file.img bs=250M count=1 && df -h /qdrant/storage"
1+0 records in
1+0 records out
262144000 bytes (262 MB, 250 MiB) copied, 2.01673 s, 130 MB/s
Filesystem                                              Size  Used Avail Use% Mounted on
/dev/longhorn/pvc-9d79a391-6777-4be5-8f9e-0139d178aada  974M  251M  708M  27% /qdrant/storage

Now let’s watch the QdrantOpsRequest in the demo namespace:

$ kubectl get qdrantopsrequest -n demo -w
NAME                              TYPE              STATUS        AGE
qdops-qdrant-sample-ka4wgv        VolumeExpansion   Progressing   2s
qdops-qdrant-sample-ka4wgv        VolumeExpansion   Successful    8m

After the QdrantOpsRequest completes successfully, let’s check the updated storage:

$ kubectl get pv -o custom-columns=NAME:.metadata.name,CAPACITY:.spec.capacity.storage,STORAGECLASS:.spec.storageClassName,CLAIM:.spec.claimRef.name | grep qdrant-sample
pvc-31485d1d-5048-4dc2-a2c3-18910b27b661   1168Mi    longhorn       data-qdrant-sample-0
pvc-683755b9-023d-4d36-8318-8a22d5b79acb   1168Mi    longhorn       data-qdrant-sample-1
pvc-d494f0aa-41b8-458d-ab56-39946c9b9bfe   1168Mi    longhorn       data-qdrant-sample-2

The storage has been automatically scaled from 1Gi to ~1168Mi as we specified a scalingThreshold of 20%.

Cleaning Up

To clean up the Kubernetes resources created by this tutorial, run:

kubectl delete qdrant -n demo qdrant-sample
kubectl delete qdrantautoscaler -n demo qdrant-as-storage
kubectl delete ns demo

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