bitnamicharts/clickhouse

Bitnami Secure Images Helm chart for ClickHouse

ClickHouse is an open-source column-oriented OLAP database management system. Use it to boost your database performance while providing linear scalability and hardware efficiency.

Overview of ClickHouse

Trademarks: This software listing is packaged by Bitnami. The respective trademarks mentioned in the offering are owned by the respective companies, and use of them does not imply any affiliation or endorsement.

TL;DR

console
helm install my-release oci://REGISTRY_NAME/REPOSITORY_NAME/clickhouse

Note: You need to substitute the placeholders REGISTRY_NAME and REPOSITORY_NAME with a reference to your Helm chart registry and repository.

Introduction

Bitnami charts for Helm are carefully engineered, actively maintained and are the quickest and easiest way to deploy containers on a Kubernetes cluster that are ready to handle production workloads.

This chart bootstraps a https://github.com/clickhouse/clickhouse Deployment in a Kubernetes cluster using the Helm package manager.

Before you begin

• Kubernetes 1.23+
• Helm 3.8.0+
• PV provisioner support in the underlying infrastructure
• ReadWriteMany volumes for deployment scaling

Installing the chart

To install the chart with the release name my-release:

console
helm install my-release oci://REGISTRY_NAME/REPOSITORY_NAME/clickhouse

Note You need to substitute the placeholders REGISTRY_NAME and REPOSITORY_NAME with a reference to your Helm chart registry and repository. For example, in the case of Bitnami, you need to use REGISTRY_NAME=registry-1.docker.io and REPOSITORY_NAME=bitnamicharts.

The command deploys ClickHouse on the Kubernetes cluster in the default configuration. The Parameters section lists the parameters that can be configured during installation.

Note List all releases using helm list.

Configuration and installation details

This section covers resource requests, credentials, configuration, and exposure options.

Resource requests and limits

Bitnami charts allow setting resource requests and limits for all containers inside the chart deployment. These are inside the resources value (check parameter table). Setting requests is essential for production workloads and these should be adapted to your specific use case.

To make this process easier, the chart contains the resourcesPreset values, which automatically sets the resources section according to different presets. Check these presets in https://github.com/bitnami/charts/blob/main/bitnami/common/templates/_resources.tpl#L15. However, in production workloads using resourcesPreset is discouraged as it may not fully adapt to your specific needs. Find more information on container resource management in the official Kubernetes documentation.

Prometheus metrics

This chart can be integrated with Prometheus by setting metrics.enabled to true. This will expose ClickHouse native Prometheus endpoint in the service. It will have the necessary annotations to be automatically scraped by Prometheus.

Prometheus requirements

It is necessary to have a working installation of Prometheus or Prometheus Operator for the integration to work. Install the https://github.com/bitnami/charts/tree/main/bitnami/prometheus or the https://github.com/bitnami/charts/tree/main/bitnami/kube-prometheus to easily have a working Prometheus in your cluster.

Integration with Prometheus Operator

The chart can deploy ServiceMonitor objects for integration with Prometheus Operator installations. To do so, set the value metrics.serviceMonitor.enabled=true. Ensure that the Prometheus Operator CustomResourceDefinitions are installed in the cluster or it will fail with the following error:

text
no matches for kind "ServiceMonitor" in version "monitoring.coreos.com/v1"

Install the https://github.com/bitnami/charts/tree/main/bitnami/kube-prometheus for having the necessary CRDs and the Prometheus Operator.

Rolling vs immutable tags

It is strongly recommended to use immutable tags in a production environment. This ensures your deployment does not change automatically if the same tag is updated with a different image.

Bitnami will release a new chart updating its containers if a new version of the main container, significant changes, or critical vulnerabilities exist.

Update credentials

Bitnami charts configure credentials at first boot. Any further change in the secrets or credentials require manual intervention. Follow these instructions:

• Update the user password following the upstream documentation
• Update the password secret with the new values (replace the SECRET_NAME, and PASSWORD placeholders)

shell
kubectl create secret generic SECRET_NAME --from-literal=admin-password=PASSWORD --dry-run -o yaml | kubectl apply -f -

ClickHouse Keeper

By default, this chart deploys ClickHouse Keeper, a lightweight and easy-to-use alternative to Zookeeper as an independent StatefulSet. This is mandatory if you're using more than 1 ClickHouse replica or sharding.

External ZooKeeper support

You may want to have ClickHouse connect to an external Zoo[Keeper] rather than installing ClickHouse Keeper inside your cluster. Typical reasons for this are to use a managed database service, or to share a common database server for all your applications. To achieve this, the chart allows you to specify credentials for an external database with the externalZookeeper parameter. You should also disable the ClickHouse Keeper installation with the keeper.enabled option. Here is an example:

console
keeper.enabled=false
externalZookeeper.servers[0]=myexternalhost
externalZookeeper.port=2888

Configuring ClickHouse

ClickHouse configuration can be extended on two different ways:

• Using the configuration parameter you can override the default configuration file (config.xml) with your own configuration. Alternatively, you can use the existingConfigmap parameter to load a custom configuration file from a ConfigMap.
• Using the configdFiles and usersdFiles parameters you can add extra configuration files to be mounted at config.d and users.d respectively (see upstream documentation to learn more about these configuration files. Alternatively, you can use the existingConfigdConfigmap and existingUsersdConfigmap parameters to load custom configuration files from ConfigMaps.

Note The chart already mounts by default a series of configuration files auto-generated based on other values at config.d. These files are prefixed with 01-, 02-, etc. up to 06-. If you want to override these files, ensure you add a prefix with a higher number (e.g. 99-) to your custom configuration files. Otherwise, the default configuration files will override your custom ones.

Gateway API

This chart provides support for exposing ClickHouse using the Gateway API and its HTTPRoute resource. If you have a Gateway controller installed on your cluster, such as APISIX, Contour, Envoy Gateway, NGINX Gateway Fabric or Kong Ingress Controller you can utilize the Gateway controller to serve your application. To enable Gateway API integration, set httpRoute.enabled to true. The Gateway to be used can be customized by setting the httpRoute.parentRefs parameter. By default, it will reference a Gateway named gateway in the same namespace as the release.

You can specify the list of hostnames to be mapped to the deployment using the httpRoute.hostnames parameter. Additionally, you can customize the rules used to route the traffic to the service by modifying the httpRoute.matches and httpRoute.filters parameters or adding new rules using the httpRoute.extraRules parameter.

This chart also supports creating a BackendTLSPolicy to define the SNI the Gateway should use to connect to the ClickHouse backend pods and how the certificate served by these pods should be verified. To do so, set the backendTLSPolicy.enabled parameter to true. Please note it's required to secure traffic using TLS as explained in the Securing traffic using TLS section to be able to use this feature.

Ingress

This chart provides support for Ingress resources. If you have an ingress controller installed on your cluster, such as https://github.com/bitnami/charts/tree/main/bitnami/nginx-ingress-controller or https://github.com/bitnami/charts/tree/main/bitnami/contour you can utilize the ingress controller to serve your application. To enable Ingress integration, set ingress.enabled to true.

The most common scenario is to have one host name mapped to the deployment. In this case, the ingress.hostname property can be used to set the host name. The ingress.tls parameter can be used to add the TLS configuration for this host.

However, it is also possible to have more than one host. To facilitate this, the ingress.extraHosts parameter (if available) can be set with the host names specified as an array. The ingress.extraTLS parameter (if available) can also be used to add the TLS configuration for extra hosts.

Note For each host specified in the ingress.extraHosts parameter, it is necessary to set a name, path, and any annotations that the Ingress controller should know about. Not all annotations are supported by all Ingress controllers, but https://github.com/kubernetes/ingress-nginx/blob/master/docs/user-guide/nginx-configuration/annotations.md lists the annotations supported by many popular Ingress controllers.

Adding the TLS parameter (where available) will cause the chart to generate HTTPS URLs, and the application will be available on port 443. The actual TLS secrets do not have to be generated by this chart. However, if TLS is enabled, the Ingress record will not work until the TLS secret exists.

Learn more about Ingress controllers.

Securing traffic using TLS

This chart supports encrypting communications with ClickHouse using TLS. To enable this feature, set the tls.enabled.

It is necessary to create a secret containing the TLS certificates and pass it to the chart using the tls.existingCASecret and tls.server.existingSecret parameters. Every secret should contain a tls.crt and tls.key keys including the certificate and key files respectively. For example: create the CA secret with the certificates files:

console
kubectl create secret generic ca-tls-secret --from-file=./tls.crt --from-file=./tls.key

You can manually create the required TLS certificates or relying on the chart auto-generation capabilities. The chart supports two different ways to auto-generate the required certificates:

• Using Helm capabilities. Enable this feature by setting tls.autoGenerated.enabled to true and tls.autoGenerated.engine to helm.
• Relying on cert-manager (please note it's required to have cert-manager installed in your K8s cluster). Enable this feature by setting tls.autoGenerated.enabled to true and tls.autoGenerated.engine to cert-manager. Please note it's supported to use an existing Issuer/ClusterIssuer for issuing the TLS certificates by setting the tls.autoGenerated.certManager.existingIssuer and tls.autoGenerated.certManager.existingIssuerKind parameters.

Additional environment variables

In case you want to add extra environment variables (useful for advanced operations like custom init scripts), you can use the extraEnvVars property.

yaml
clickhouse:
  extraEnvVars:
    - name: LOG_LEVEL
      value: error

Alternatively, you can use a ConfigMap or a Secret with the environment variables. To do so, use the extraEnvVarsCM or the extraEnvVarsSecret values.

Sidecars

If additional containers are needed in the same pod as ClickHouse (such as additional metrics or logging exporters), they can be defined using the sidecars parameter.

yaml
sidecars:
- name: your-image-name
  image: your-image
  imagePullPolicy: Always
  ports:
  - name: portname
    containerPort: 1234

If these sidecars export extra ports, extra port definitions can be added using the service.extraPorts parameter (where available), as shown in the following example:

yaml
service:
  extraPorts:
  - name: extraPort
    port: 11311
    targetPort: 11311

Note This Helm chart already includes sidecar containers for the Prometheus exporters (where applicable). These can be activated by adding the --enable-metrics=true parameter at deployment time. The sidecars parameter should therefore only be used for any extra sidecar containers.

If additional init containers are needed in the same pod, they can be defined using the initContainers parameter. Here is an example:

yaml
initContainers:
  - name: your-image-name
    image: your-image
    imagePullPolicy: Always
    ports:
      - name: portname
        containerPort: 1234

Learn more about sidecar containers and init containers.

Using custom scripts

For advanced operations, the Bitnami ClickHouse chart allows using custom init and start scripts that will be mounted in /docker-entrypoint.initdb.d and /docker-entrypoint.startdb.d . The init scripts will be run on the first boot whereas the start scripts will be run on every container start. For adding the scripts directly as values use the initdbScripts and startdbScripts values. For using Secrets use the initdbScriptsSecret and startdbScriptsSecret.

yaml
initdbScriptsSecret: init-scripts-secret
startdbScriptsSecret: start-scripts-secret

Pod affinity

This chart allows you to set your custom affinity using the affinity parameter. Find more information about pod affinity in the Kubernetes documentation.

As an alternative, use one of the preset configurations for pod affinity, pod anti-affinity, and node affinity available at the https://github.com/bitnami/charts/tree/main/bitnami/common#affinities chart. To do so, set the podAffinityPreset, podAntiAffinityPreset, or nodeAffinityPreset parameters.

Backup and restore

To back up and restore Helm chart deployments on Kubernetes, you need to back up the persistent volumes from the source deployment and attach them to a new deployment using Velero, a Kubernetes backup/restore tool. Find the instructions for using Velero in this guide.

FIPS parameters

The FIPS parameters only have effect if you are using images from the Bitnami Secure Images catalog.

For more information on this new support, please refer to the FIPS Compliance section.

MCP (Model Context Protocol) component

This chart includes an optional MCP (Model Context Protocol) component that provides a standardized interface for AI assistants and LLMs to interact with ClickHouse. When enabled, it deploys a separate service that exposes ClickHouse functionality using the MCP protocol. The upstream project is available at https://github.com/ClickHouse/mcp-clickhouse. To enable the MCP component, set mcp.enabled=true:

MCP Configuration

By default (mcp.useAdminCredentials=true), the MCP component automatically connects to the main ClickHouse instance using the admin credentials. The connection details are passed using environment variables.

When usePasswordFiles=true (the default), the MCP container uses a bash script to read credentials from mounted secret files and then executes the MCP server with exec. This ensures proper signal handling and process management.

When usePasswordFiles=false, credentials are passed as environment variables:

• CLICKHOUSE_USER: Set to the ClickHouse admin username
• CLICKHOUSE_PASSWORD: Retrieved from the ClickHouse admin password secret

If you want to use custom ClickHouse credentials instead, set mcp.useAdminCredentials=false and provide your own credentials:

yaml
mcp:
  enabled: true
  useAdminCredentials: false
  extraEnvVars:
    - name: CLICKHOUSE_USER
      value: my-custom-user
    - name: CLICKHOUSE_PASSWORD
      valueFrom:
        secretKeyRef:
          name: my-clickhouse-credentials
          key: password

The MCP server listens on port 8000 by default and uses HTTP as the transport protocol. For a complete list of supported environment variables, see the https://github.com/ClickHouse/mcp-clickhouse#environment-variables.

You can configure additional MCP server options using extraEnvVars:

yaml
mcp:
  enabled: true
  extraEnvVars:
    - name: CLICKHOUSE_CONNECT_TIMEOUT
      value: "60"
    - name: CLICKHOUSE_SEND_RECEIVE_TIMEOUT
      value: "600"
    - name: CLICKHOUSE_MCP_QUERY_TIMEOUT
      value: "60"

Authentication and Authorization with kube-rbac-proxy

For enhanced security, you can enable authentication and authorization using a kube-rbac-proxy sidecar:

yaml
mcp:
  enabled: true
  auth:
    enabled: true
    allowedServiceAccounts:
      - namespace: default
        name: my-ai-assistant
      - namespace: ai-namespace
        name: another-service

When mcp.auth.enabled is set to true:

• A kube-rbac-proxy sidecar is deployed alongside the MCP container
• The proxy listens on port 8443 (HTTPS) by default and forwards authenticated requests to the MCP server
• RBAC rules are automatically created to allow access to the endpoint
• Only the MCP service account and the service accounts listed in mcp.auth.allowedServiceAccounts can access the endpoint
• The Service will expose the HTTPS port instead of the direct HTTP port

This provides Kubernetes-native authentication and authorization, ensuring that only authorized service accounts can interact with the MCP ClickHouse server.

TLS Configuration for kube-rbac-proxy

When authentication is enabled, TLS is always enabled and automatically configured for the kube-rbac-proxy sidecar. By default, the chart will auto-generate a self-signed certificate using Helm capabilities:

yaml
mcp:
  enabled: true
  auth:
    enabled: true
    tls:
      autoGenerated:
        enabled: true
        engine: helm  # or cert-manager

You can also provide your own TLS certificate:

yaml
mcp:
  enabled: true
  auth:
    enabled: true
    tls:
      autoGenerated:
        enabled: false
      existingSecret: my-tls-secret

Or provide the certificate directly:

yaml
mcp:
  enabled: true
  auth:
    enabled: true
    tls:
      autoGenerated:
        enabled: false
      cert: |
        -----BEGIN CERTIFICATE-----
        ...
        -----END CERTIFICATE-----
      key: |
        -----BEGIN RSA PRIVATE KEY-----
        ...
        -----END RSA PRIVATE KEY-----

For production environments with cert-manager, you can use the cert-manager engine:

yaml
mcp:
  enabled: true
  auth:
    enabled: true
    tls:
      autoGenerated:
        enabled: true
        engine: cert-manager
        certManager:
          existingIssuer: my-issuer
          existingIssuerKind: ClusterIssuer

Persistence

The https://github.com/bitnami/containers/tree/main/bitnami/clickhouse image stores the ClickHouse data and configurations at the /bitnami/clickhouse path of the container. Persistent Volume Claims are used to keep the data across deployments. This is known to work in GCE, AWS, and minikube.

Parameters

The following subsections list global, common, and component-specific parameters.

Global parameters

_Note: the README for this chart is longer than the DockerHub length limit of 25000, so it has been trimmed. The full README can be found at [***]