KubeDB

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Backup and Restore ClickHouse database using KubeStash

KubeStash allows you to backup and restore ClickHouse databases. It supports backups for ClickHouse instances running in both Standalone and clusterTopology (sharded, replicated clusters with ClickHouseKeeper) configurations. KubeStash makes managing your ClickHouse backups and restorations more straightforward and efficient.

This guide will give you an overview how you can take backup and restore your ClickHouse databases using KubeStash. Here, we are going to demonstrate the backup and restore process for a ClickHouse database using clusterTopology. The process is similar for Standalone configuration.

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 Minikube or Kind.
  • Install KubeDB in your cluster following the steps here.
  • Install KubeStash in your cluster following the steps here.
  • Install KubeStash kubectl plugin following the steps here.
  • If you are not familiar with how KubeStash backup and restore ClickHouse databases, please check the following guide here.

You should be familiar with the following KubeStash 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

Note: YAML files used in this tutorial are stored in docs/guides/clickhouse/backup/logical/examples directory of kubedb/docs repository.

Backup ClickHouse

This section will demonstrate how to backup a ClickHouse database. Here, we are going to deploy a ClickHouse database using KubeDB. Then, we are going to backup this database into an S3 bucket. Finally, we are going to restore the backed up data into another ClickHouse database.

Deploy Sample ClickHouse Database

Below is the YAML of a sample ClickHouse CR that we are going to create for this tutorial:

apiVersion: kubedb.com/v1alpha2
kind: ClickHouse
metadata:
  name: sample-clickhouse
  namespace: demo
spec:
  version: 25.7.1
  clusterTopology:
    clickHouseKeeper:
      externallyManaged: false
      spec:
        replicas: 3
        storage:
          storageClassName: "local-path"
          accessModes:
            - ReadWriteOnce
          resources:
            requests:
              storage: 1Gi
    cluster:
      name: appscode-cluster
      shards: 2
      replicas: 2
      podTemplate:
        spec:
          containers:
            - name: clickhouse
              resources:
                limits:
                  memory: 4Gi
                requests:
                  cpu: 1
                  memory: 2Gi
          initContainers:
            - name: clickhouse-init
              resources:
                limits:
                  memory: 1Gi
                requests:
                  cpu: 500m
                  memory: 512Mi
      storage:
        storageClassName: "local-path"
        accessModes:
          - ReadWriteOnce
        resources:
          requests:
            storage: 1Gi
  deletionPolicy: WipeOut

Create the above ClickHouse CR,

$ kubectl apply -f https://github.com/kubedb/docs/raw/v2026.7.10/docs/guides/clickhouse/backup/logical/examples/sample-clickhouse.yaml
clickhouse.kubedb.com/sample-clickhouse created

KubeDB will deploy a ClickHouse cluster (2 shards x 2 replicas, plus a 3-node ClickHouseKeeper ensemble) according to the above specification. It will also create the necessary Secrets and Services to access the database.

Let’s check if the database is ready to use,

$ kubectl get clickhouse -n demo sample-clickhouse
NAME                VERSION   STATUS   AGE
sample-clickhouse   25.7.1    Ready    3m27s

The database is Ready. Verify that KubeDB has created a Secret and Services for this database using the following commands,

$ kubectl get secret -n demo | grep sample-clickhouse
sample-clickhouse-auth                  kubernetes.io/basic-auth   2      81s
sample-clickhouse-fd9557                Opaque                     3      80s
sample-clickhouse-internal-auth-token   kubernetes.io/basic-auth   1      80s
sample-clickhouse-keeper-config         Opaque                     2      80s

$ kubectl get service -n demo -l=app.kubernetes.io/instance=sample-clickhouse
NAME                            TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)             AGE
sample-clickhouse               ClusterIP   10.43.52.87     <none>        9000/TCP,8123/TCP   81s
sample-clickhouse-keeper        ClusterIP   10.43.166.188   <none>        9181/TCP            80s
sample-clickhouse-keeper-pods   ClusterIP   None            <none>        9234/TCP            80s
sample-clickhouse-pods          ClusterIP   None            <none>        9000/TCP,8123/TCP   81s

Here, we have to use service sample-clickhouse and secret sample-clickhouse-auth to connect with the database. KubeDB creates an AppBinding CR that holds the necessary information to connect with the database.

Verify AppBinding:

Verify that the AppBinding has been created successfully using the following command,

$ kubectl get appbindings -n demo
NAME                TYPE                    VERSION   AGE
sample-clickhouse   kubedb.com/clickhouse   25.7.1    73s

Let’s check the YAML of the above AppBinding,

$ kubectl get appbindings -n demo sample-clickhouse -o yaml

apiVersion: appcatalog.appscode.com/v1alpha1
kind: AppBinding
metadata:
  name: sample-clickhouse
  namespace: demo
spec:
  appRef:
    apiGroup: kubedb.com
    kind: ClickHouse
    name: sample-clickhouse
    namespace: demo
  clientConfig:
    service:
      name: sample-clickhouse
      port: 9000
      scheme: http
  secret:
    apiGroup: ""
    kind: Secret
    name: sample-clickhouse-auth
  type: kubedb.com/clickhouse
  version: 25.7.1

KubeStash uses the AppBinding CR to connect with the target database. It requires the following two fields to be set in AppBinding’s .spec section.

Here,

  • .spec.clientConfig.service.name specifies the name of the Service that connects to the database.
  • .spec.secret specifies the name of the Secret that holds necessary credentials to access the database.
  • .spec.type specifies the type of the app that this AppBinding is pointing to. KubeDB generated AppBinding follows the following format: <app group>/<app resource type>.

Insert Sample Data:

Now, we are going to exec into one of the database pod and create some sample data. At first, find out the database Pods using the following command,

$ kubectl get pods -n demo --selector="app.kubernetes.io/instance=sample-clickhouse"
NAME                                            READY   STATUS    RESTARTS   AGE
sample-clickhouse-appscode-cluster-shard-0-0   1/1     Running   0          119s
sample-clickhouse-appscode-cluster-shard-0-1   1/1     Running   0          22s
sample-clickhouse-appscode-cluster-shard-1-0   1/1     Running   0          116s
sample-clickhouse-appscode-cluster-shard-1-1   1/1     Running   0          22s

And copy the username and password of the admin user to access the clickhouse-client shell.

$ kubectl get secret -n demo sample-clickhouse-auth -o jsonpath='{.data.username}' | base64 -d
admin⏎

$ kubectl get secret -n demo sample-clickhouse-auth -o jsonpath='{.data.password}' | base64 -d
fB9sH0(xeg3FBxs7⏎

Since sample-clickhouse is deployed with a clusterTopology (2 shards x 2 replicas), a plain MergeTree table would only live on a single node and would not be replicated or sharded. To properly use the cluster, we create a ReplicatedMergeTree table (for replication within a shard, coordinated through ClickHouseKeeper) on every node using ON CLUSTER, and a Distributed table on top of it (for transparently routing reads/writes across all shards).

Now, let’s exec into a Pod and create the database and tables,

$ kubectl exec -it -n demo sample-clickhouse-appscode-cluster-shard-0-0 -- clickhouse-client --user admin --password "fB9sH0(xeg3FBxs7"

# create a database named "playground" on every node of the cluster
:) CREATE DATABASE playground ON CLUSTER 'appscode-cluster';

# create the underlying replicated table on every shard/replica
:) CREATE TABLE playground.equipment_local ON CLUSTER 'appscode-cluster'
   (
       id UInt32,
       type String,
       quant UInt32,
       color String
   )
   ENGINE = ReplicatedMergeTree('/clickhouse/tables/{shard}/equipment_local', '{replica}')
   ORDER BY id;

# create a Distributed table on top, so we can read/write across all shards through a single table
:) CREATE TABLE playground.equipment ON CLUSTER 'appscode-cluster'
   AS playground.equipment_local
   ENGINE = Distributed('appscode-cluster', 'playground', 'equipment_local', rand());

# insert some rows through the Distributed table
:) INSERT INTO playground.equipment VALUES (1,'Swing',10,'Red'),(2,'Slide',5,'Blue'),(3,'Monkey Bars',3,'Yellow');

# verify that data has been inserted successfully
:) SELECT * FROM playground.equipment ORDER BY id;

┌─id─┬─type────────┬─quant─┬─color──┐
│  1 │ Swing       │    10 │ Red    │
│  2 │ Slide       │     5 │ Blue   │
│  3 │ Monkey Bars │     3 │ Yellow │
└────┴─────────────┴───────┴────────┘

:) exit

Here,

  • {shard} and {replica} are macros that KubeDB automatically configures on every ClickHouse pod (visible via SELECT * FROM system.macros), so the same CREATE TABLE ... ON CLUSTER statement creates a correctly-parameterized replica path on each node.
  • The equipment_local table on the two replicas of a shard (e.g. shard-0-0 and shard-0-1) stays in sync via ClickHouseKeeper, while rand() in the Distributed engine definition spreads rows for the equipment table across the two shards.

We can verify this by checking the local table on each shard directly. In this run, all 3 rows happened to land on shard 0 (and were replicated to both of its replicas), while shard 1 has none — this is expected: with a handful of rows, ClickHouse doesn’t guarantee an even split across shards.

$ kubectl exec -it -n demo sample-clickhouse-appscode-cluster-shard-0-0 -- clickhouse-client --user admin --password "fB9sH0(xeg3FBxs7" -q "SELECT * FROM playground.equipment_local ORDER BY id"
1	Swing	10	Red
2	Slide	5	Blue
3	Monkey Bars	3	Yellow

$ kubectl exec -it -n demo sample-clickhouse-appscode-cluster-shard-0-1 -- clickhouse-client --user admin --password "fB9sH0(xeg3FBxs7" -q "SELECT * FROM playground.equipment_local ORDER BY id"
1	Swing	10	Red
2	Slide	5	Blue
3	Monkey Bars	3	Yellow

$ kubectl exec -it -n demo sample-clickhouse-appscode-cluster-shard-1-0 -- clickhouse-client --user admin --password "fB9sH0(xeg3FBxs7" -q "SELECT * FROM playground.equipment_local ORDER BY id"

Let’s insert a few more rows through the Distributed table to see the sharding actually spread the data out,

$ kubectl exec -n demo sample-clickhouse-appscode-cluster-shard-0-0 -- clickhouse-client --user admin --password "fB9sH0(xeg3FBxs7" -q \
  "INSERT INTO playground.equipment VALUES (4,'Item4',4,'Color4'),(5,'Item5',5,'Color5'),(6,'Item6',6,'Color6'),(7,'Item7',7,'Color7'),(8,'Item8',8,'Color8'),(9,'Item9',9,'Color9'),(10,'Item10',10,'Color10'),(11,'Item11',11,'Color11'),(12,'Item12',12,'Color12'),(13,'Item13',13,'Color13'),(14,'Item14',14,'Color14'),(15,'Item15',15,'Color15')"

$ kubectl exec -n demo sample-clickhouse-appscode-cluster-shard-0-0 -- clickhouse-client --user admin --password "fB9sH0(xeg3FBxs7" -q "SELECT count() FROM playground.equipment_local"
12

$ kubectl exec -n demo sample-clickhouse-appscode-cluster-shard-1-0 -- clickhouse-client --user admin --password "fB9sH0(xeg3FBxs7" -q "SELECT count() FROM playground.equipment_local"
3

$ kubectl exec -n demo sample-clickhouse-appscode-cluster-shard-0-0 -- clickhouse-client --user admin --password "fB9sH0(xeg3FBxs7" -q "SELECT count() FROM playground.equipment"
15

Now the data is spread across both shards (12 rows on shard 0, 3 rows on shard 1), while the Distributed table transparently reports all 15 rows regardless of which shard a client happens to connect to.

Now, we are ready to backup the database.

Prepare Backend

We are going to store our backed up data into an S3 bucket. We have to create a Secret with necessary credentials and a BackupStorage CR to use this backend. If you want to use a different backend, please read the respective backend configuration doc from here.

Note: ClickHouse currently supports S3, Azure Blob Storage, and Google Cloud Storage (via S3 compatibility mode) as backup storage backends.

Create Secret:

Let’s create a secret called s3-secret with access credentials to our desired S3 (or S3 compatible, e.g. Minio) bucket,

$ echo -n '<your-aws-access-key-id-here>' > AWS_ACCESS_KEY_ID
$ echo -n '<your-aws-secret-access-key-here>' > AWS_SECRET_ACCESS_KEY
$ kubectl create secret generic -n demo s3-secret \
    --from-file=./AWS_ACCESS_KEY_ID \
    --from-file=./AWS_SECRET_ACCESS_KEY
secret/s3-secret created

Create BackupStorage:

Now, create a BackupStorage using this secret. Below is the YAML of the BackupStorage CR we are going to create,

apiVersion: storage.kubestash.com/v1alpha1
kind: BackupStorage
metadata:
  name: s3-storage
  namespace: demo
spec:
  storage:
    provider: s3
    s3:
      bucket: kubestash
      prefix: clickhouse-backup
      secretName: s3-secret
      region: us-east-1
      endpoint: http://minio.demo.svc.cluster.local:80
  usagePolicy:
    allowedNamespaces:
      from: All
  default: true
  deletionPolicy: Delete

Let’s create the BackupStorage we have shown above,

$ kubectl apply -f https://github.com/kubedb/docs/raw/v2026.7.10/docs/guides/clickhouse/backup/logical/examples/backupstorage.yaml
backupstorage.storage.kubestash.com/s3-storage created

Now, we are ready to backup our database to our desired backend.

Create RetentionPolicy:

Now, let’s create a RetentionPolicy to specify how the old Snapshots should be cleaned up.

Below is the YAML of the RetentionPolicy object that we are going to create,

apiVersion: storage.kubestash.com/v1alpha1
kind: RetentionPolicy
metadata:
  name: demo-retention
  namespace: demo
spec:
  default: true
  failedSnapshots:
    last: 2
  successfulSnapshots:
    last: 2
  usagePolicy:
    allowedNamespaces:
      from: All

Let’s create the above RetentionPolicy,

$ kubectl apply -f https://github.com/kubedb/docs/raw/v2026.7.10/docs/guides/clickhouse/backup/logical/examples/retentionpolicy.yaml
retentionpolicy.storage.kubestash.com/demo-retention created

Backup

We have to create a BackupConfiguration targeting our sample-clickhouse ClickHouse database. Then, KubeStash will create a CronJob for each session to take periodic backup of that database.

Below is the YAML for the BackupConfiguration CR to backup the sample-clickhouse ClickHouse database that we have deployed earlier,

apiVersion: core.kubestash.com/v1alpha1
kind: BackupConfiguration
metadata:
  name: sample-clickhouse-backup
  namespace: demo
spec:
  target:
    apiGroup: kubedb.com
    kind: ClickHouse
    namespace: demo
    name: sample-clickhouse
  backends:
    - name: s3-backend
      storageRef:
        namespace: demo
        name: s3-storage
      retentionPolicy:
        name: demo-retention
        namespace: demo
  sessions:
    - name: frequent-backup
      scheduler:
        schedule: "*/5 * * * *"
        jobTemplate:
          backoffLimit: 1
      repositories:
        - name: s3-clickhouse-repo
          backend: s3-backend
          directory: /clickhouse
      addon:
        name: clickhouse-addon
        tasks:
          - name: logical-backup
  • .spec.target refers to the targeted sample-clickhouse ClickHouse database that we created earlier.
  • .spec.sessions[*].scheduler.schedule specifies that we want to backup the database at 5 minutes interval.
  • .spec.sessions[*].addon refers to the clickhouse-addon and the logical-backup task, which uses the ClickHouseBackup driver (clickhouse-backup) to take a logical backup of every shard.

Note: Unlike some other KubeDB addons, the clickhouse-addon backup and restore jobs run fine with the default (non-root) security context. You don’t need to set spec.sessions[*].addon.jobTemplate.spec.securityContext (e.g. runAsUser/runAsGroup/fsGroup) for ClickHouse backup or restore.

Let’s create the BackupConfiguration CR that we have shown above,

$ kubectl apply -f https://github.com/kubedb/docs/raw/v2026.7.10/docs/guides/clickhouse/backup/logical/examples/backupconfiguration.yaml
backupconfiguration.core.kubestash.com/sample-clickhouse-backup created

Verify Backup Setup Successful

If everything goes well, the phase of the BackupConfiguration should be Ready. The Ready phase indicates that the backup setup is successful. Let’s verify the Phase of the BackupConfiguration,

$ kubectl get backupconfiguration -n demo
NAME                       PHASE   PAUSED   AGE
sample-clickhouse-backup   Ready            11s

Additionally, we can verify that the Repository specified in the BackupConfiguration has been created using the following command,

$ kubectl get repo -n demo
NAME                 INTEGRITY   SNAPSHOT-COUNT   SIZE   PHASE   LAST-SUCCESSFUL-BACKUP   AGE
s3-clickhouse-repo               0                0 B    Ready                            16s

Verify CronJob:

It will also create a CronJob with the schedule specified in spec.sessions[*].scheduler.schedule field of the BackupConfiguration CR.

Verify that the CronJob has been created using the following command,

$ kubectl get cronjob -n demo
NAME                                               SCHEDULE      SUSPEND   ACTIVE   LAST SCHEDULE   AGE
trigger-sample-clickhouse-backup-frequent-backup   */5 * * * *   False     0        <none>          15s

Verify BackupSession:

KubeStash triggers an instant backup as soon as the BackupConfiguration is ready. After that, backups are scheduled according to the specified schedule.

$ kubectl get backupsession -n demo
NAME                                                 INVOKER-TYPE          INVOKER-NAME               PHASE       DURATION   AGE
sample-clickhouse-backup-frequent-backup-1789709796   BackupConfiguration   sample-clickhouse-backup   Succeeded   26s        30s

We can see from the above output that the backup session has succeeded. Now, we are going to verify whether the backed up data has been stored in the backend.

Verify Backup:

Once a backup is complete, KubeStash will update the respective Repository CR to reflect the backup. Check that the repository s3-clickhouse-repo has been updated by the following command,

$ kubectl get repository -n demo s3-clickhouse-repo
NAME                 INTEGRITY   SNAPSHOT-COUNT   SIZE   PHASE   LAST-SUCCESSFUL-BACKUP   AGE
s3-clickhouse-repo               1                0 B    Ready   2m27s                    2m28s

At this moment we have one Snapshot. Run the following command to check the respective Snapshot which represents the state of a backup run for an application.

$ kubectl get snapshots -n demo -l=kubestash.com/repo-name=s3-clickhouse-repo
NAME                                                              REPOSITORY           SESSION           SNAPSHOT-TIME          DELETION-POLICY   PHASE       AGE
s3-clickhouse-repo-sample-clickhckup-frequent-backup-1789709796   s3-clickhouse-repo   frequent-backup   2026-09-18T05:36:37Z   Delete            Succeeded   2m28s

Note: KubeStash creates a Snapshot with the following labels:

  • kubestash.com/app-ref-kind: <target-kind>
  • kubestash.com/app-ref-name: <target-name>
  • kubestash.com/app-ref-namespace: <target-namespace>
  • kubestash.com/repo-name: <repository-name>

These labels can be used to watch only the Snapshots related to our target Database or Repository.

If we check the YAML of the Snapshot, we can find the information about the backed up components of the database. For a ClickHouse cluster, KubeStash records the backup result for the shared metadata as well as for each shard,

$ kubectl get snapshots -n demo s3-clickhouse-repo-sample-clickhckup-frequent-backup-1789709796 -oyaml

apiVersion: storage.kubestash.com/v1alpha1
kind: Snapshot
metadata:
  annotations:
    kubedb.com/db-version: 25.7.1
  labels:
    kubestash.com/app-ref-kind: ClickHouse
    kubestash.com/app-ref-name: sample-clickhouse
    kubestash.com/app-ref-namespace: demo
    kubestash.com/repo-name: s3-clickhouse-repo
  name: s3-clickhouse-repo-sample-clickhckup-frequent-backup-1789709796
  namespace: demo
spec:
  appRef:
    apiGroup: kubedb.com
    kind: ClickHouse
    name: sample-clickhouse
    namespace: demo
  backupSession: sample-clickhouse-backup-frequent-backup-1789709796
  deletionPolicy: Delete
  repository: s3-clickhouse-repo
  session: frequent-backup
  snapshotID: 01M2SG8J9WZV2R65W251ATEGPN
  type: FullBackup
  version: v1
status:
  components:
    dump:
      clickHouseStats:
      - finishTime: "2026-09-18T05:36:40Z"
        host: dump-metadata
        id: 94c88a90-e5f5-46bf-bf21-b389d5b8d626
        startTime: "2026-09-18T05:36:39Z"
        status: SUCCESS
      - finishTime: "2026-09-18T05:36:50Z"
        host: dump-shard-0
        id: d0100062-d9d6-4ef1-bbab-3887137b6733
        startTime: "2026-09-18T05:36:49Z"
        status: SUCCESS
      - finishTime: "2026-09-18T05:36:50Z"
        host: dump-shard-1
        id: fa091258-5c37-4de8-8181-e73b94ceb85a
        startTime: "2026-09-18T05:36:49Z"
        status: SUCCESS
      driver: ClickHouseBackup
      path: repository/v1/frequent-backup/dump/full/1789709796
      phase: Succeeded
  conditions:
  - lastTransitionTime: "2026-09-18T05:36:37Z"
    message: Recent snapshot list updated successfully
    reason: SuccessfullyUpdatedRecentSnapshotList
    status: "True"
    type: RecentSnapshotListUpdated
  - lastTransitionTime: "2026-09-18T05:36:59Z"
    message: Metadata uploaded to backend successfully
    reason: SuccessfullyUploadedSnapshotMetadata
    status: "True"
    type: SnapshotMetadataUploaded
  phase: Succeeded
  snapshotTime: "2026-09-18T05:36:37Z"
  totalComponents: 1
  verificationStatus: NotVerified

Here, status.components.dump.clickHouseStats shows that a dump was taken for the cluster metadata (dump-metadata) as well as for each shard (dump-shard-0, dump-shard-1).

Now, if we navigate to the S3 bucket, we will see the backed up data stored under the clickhouse-backup/clickhouse/repository/v1/frequent-backup/dump directory. KubeStash also keeps the backup for Repository and Snapshot YAMLs, which can be found in the clickhouse-backup/clickhouse/repository and clickhouse-backup/clickhouse/snapshots directories respectively.

Restore

In this section, we are going to restore the database from the backup we have taken in the previous section. We are going to deploy a new database and initialize it from the backup.

Below is the YAML for the ClickHouse CR we are going to deploy to restore the backed up data into,

apiVersion: kubedb.com/v1alpha2
kind: ClickHouse
metadata:
  name: restored-clickhouse
  namespace: demo
spec:
  version: 25.7.1
  clusterTopology:
    clickHouseKeeper:
      externallyManaged: false
      spec:
        replicas: 3
        storage:
          storageClassName: "local-path"
          accessModes:
            - ReadWriteOnce
          resources:
            requests:
              storage: 1Gi
    cluster:
      name: appscode-cluster
      shards: 2
      replicas: 2
      podTemplate:
        spec:
          containers:
            - name: clickhouse
              resources:
                limits:
                  memory: 4Gi
                requests:
                  cpu: 1
                  memory: 2Gi
          initContainers:
            - name: clickhouse-init
              resources:
                limits:
                  memory: 1Gi
                requests:
                  cpu: 500m
                  memory: 512Mi
      storage:
        storageClassName: "local-path"
        accessModes:
          - ReadWriteOnce
        resources:
          requests:
            storage: 1Gi
  deletionPolicy: WipeOut

Let’s create the above database,

$ kubectl apply -f https://github.com/kubedb/docs/raw/v2026.7.10/docs/guides/clickhouse/backup/logical/examples/restored-clickhouse.yaml
clickhouse.kubedb.com/restored-clickhouse created

Wait until the database goes into Ready state,

$ kubectl get clickhouse -n demo restored-clickhouse
NAME                  VERSION   STATUS   AGE
restored-clickhouse   25.7.1    Ready    3m

Create RestoreSession:

Now, we need to create a RestoreSession CR pointing to the targeted ClickHouse database.

Below is the content of the YAML file of the RestoreSession object that we are going to create to restore backed up data into the newly created ClickHouse database named restored-clickhouse.

apiVersion: core.kubestash.com/v1alpha1
kind: RestoreSession
metadata:
  name: sample-clickhouse-restore
  namespace: demo
spec:
  target:
    apiGroup: kubedb.com
    kind: ClickHouse
    namespace: demo
    name: restored-clickhouse
  dataSource:
    repository: s3-clickhouse-repo
    snapshot: latest
  addon:
    name: clickhouse-addon
    tasks:
      - name: logical-backup-restore

Here,

  • .spec.target refers to the newly created restored-clickhouse ClickHouse object to where we want to restore backup data.
  • .spec.dataSource.repository specifies the Repository object that holds the backed up data.
  • .spec.dataSource.snapshot specifies to restore from the latest Snapshot.
  • .spec.addon refers to the clickhouse-addon and the logical-backup-restore task.

As noted earlier, the clickhouse-addon restore job also runs fine with the default security context, so spec.addon.jobTemplate.spec.securityContext is not required here either.

Let’s create the RestoreSession CR we have shown above,

$ kubectl apply -f https://github.com/kubedb/docs/raw/v2026.7.10/docs/guides/clickhouse/backup/logical/examples/restoresession.yaml
restoresession.core.kubestash.com/sample-clickhouse-restore created

Once you have created the RestoreSession object, KubeStash will create a restore Job. Run the following command to watch the phase of the RestoreSession object,

$ watch kubectl get restoresession -n demo
NAME                        REPOSITORY            PHASE       DURATION   AGE
sample-clickhouse-restore   s3-clickhouse-repo    Succeeded   22s        30s

The Succeeded phase means that the restore process has been completed successfully.

Verify Restored Data:

In this section, we are going to verify whether the desired data has been restored successfully. We are going to connect to the database server and check whether the database and the table we created earlier in the original database are restored.

At first, check if the database has gone into Ready state by the following command,

$ kubectl get clickhouse -n demo restored-clickhouse
NAME                  VERSION   STATUS   AGE
restored-clickhouse   25.7.1    Ready    6m

Now, find out the database Pods using the following command,

$ kubectl get pods -n demo --selector="app.kubernetes.io/instance=restored-clickhouse"
NAME                                              READY   STATUS    RESTARTS   AGE
restored-clickhouse-appscode-cluster-shard-0-0   1/1     Running   0          2m46s
restored-clickhouse-appscode-cluster-shard-0-1   1/1     Running   0          2m41s
restored-clickhouse-appscode-cluster-shard-1-0   1/1     Running   0          2m44s
restored-clickhouse-appscode-cluster-shard-1-1   1/1     Running   0          2m40s

And copy the username and password of the admin user to access the clickhouse-client shell.

$ kubectl get secret -n demo restored-clickhouse-auth -o jsonpath='{.data.username}' | base64 -d
admin⏎

$ kubectl get secret -n demo restored-clickhouse-auth -o jsonpath='{.data.password}' | base64 -d
1OfTqKc8IzNgoLMi⏎

Now, let’s exec into the Pod and verify the restored data. This time we check more than just the row values — since our equipment table is a Distributed table on top of a ReplicatedMergeTree table, we also verify that both the table engines and the per-shard data distribution were restored correctly.

$ kubectl exec -it -n demo restored-clickhouse-appscode-cluster-shard-0-0 -- clickhouse-client --user admin --password '1OfTqKc8IzNgoLMi'

:) SHOW DATABASES;

┌─name───────────────┐
│ INFORMATION_SCHEMA  │
│ default             │
│ information_schema  │
│ playground          │
│ system              │
└────────────────────┘

:) SHOW CREATE TABLE playground.equipment_local;

CREATE TABLE playground.equipment_local
(
    `id` UInt32,
    `type` String,
    `quant` UInt32,
    `color` String
)
ENGINE = ReplicatedMergeTree('/clickhouse/tables/{shard}/equipment_local', '{replica}')
ORDER BY id

:) SHOW CREATE TABLE playground.equipment;

CREATE TABLE playground.equipment
(
    `id` UInt32,
    `type` String,
    `quant` UInt32,
    `color` String
)
ENGINE = Distributed('appscode-cluster', 'playground', 'equipment_local', rand())

:) SELECT count() FROM playground.equipment;

15

:) exit

The ReplicatedMergeTree and Distributed table definitions came back exactly as they were, and the Distributed table again reports all 15 rows. Let’s also confirm the per-shard split survived the restore, matching the original 12/3 split,

$ kubectl exec -n demo restored-clickhouse-appscode-cluster-shard-0-0 -- clickhouse-client --user admin --password '1OfTqKc8IzNgoLMi' -q "SELECT count() FROM playground.equipment_local"
12

$ kubectl exec -n demo restored-clickhouse-appscode-cluster-shard-1-0 -- clickhouse-client --user admin --password '1OfTqKc8IzNgoLMi' -q "SELECT count() FROM playground.equipment_local"
3

$ kubectl exec -n demo restored-clickhouse-appscode-cluster-shard-0-1 -- clickhouse-client --user admin --password '1OfTqKc8IzNgoLMi' -q "SELECT count() FROM playground.equipment_local"
12

So, from the above output, we can see that the playground database, the equipment_local/equipment tables, and the exact per-shard row distribution (including the shard-0 replica) from the original database are all restored successfully.

Cleanup

To cleanup the Kubernetes resources created by this tutorial, run:

kubectl delete restoresessions.core.kubestash.com -n demo sample-clickhouse-restore
kubectl delete backupconfigurations.core.kubestash.com -n demo sample-clickhouse-backup
kubectl delete retentionpolicies.storage.kubestash.com -n demo demo-retention
kubectl delete backupstorage -n demo s3-storage
kubectl delete secret -n demo s3-secret
kubectl delete clickhouse -n demo restored-clickhouse
kubectl delete clickhouse -n demo sample-clickhouse

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