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Version: current [26.x]

Deploying Dremio to Kubernetes

You can follow these instructions to deploy Dremio in Kubernetes provisioned through a cloud provider or running in an on-premises environment.

Prerequisites

Before deploying Dremio to Kubernetes, you must make sure you have the following:

  • A hosted Kubernetes environment to deploy and manage the Dremio cluster.
    Each Dremio release is tested against Amazon EKS, Azure AKS, and GCP GKE to ensure compatibility. If you have a containerization platform built on top of Kubernetes but not listed here, please contact your provider and the Dremio Account Team regarding compatibility.
  • Helm 3 set up on a local machine to run Helm commands. For installation instructions, refer to Installing Helm.
  • A local kubectl configured to access your Kubernetes cluster. For installation instructions, refer to Installing kubectl.
  • Object Storage: AWS S3 (including S3-Compatible, e.g., Minio), Azure Storage, and GCP Cloud Storage.
  • Storage classes that support ReadWriteOnce (RWO) access mode and ideally can create expandable volumes.

Additional Prerequisites for the Free Trial

For the Free Trial, you will need to complete the steps in How to Obtain a Free Trial License. Once done, you will receive an email with a link to download the values-overrides.yaml configuration file, already with two key configurations for you to deploy your Free Trial without further due:

  • The free trial license.
  • Access to Dremio image repository in Quay.io. Unlike the Enterprise Edition, you won't need to create a RedHat account, log in to Quay.io, and get access to Dremio's Helm charts and images.

Additional Prerequisites for the Enterprise Edition

FREE TRIAL

Ignore the prerequisites in this section if deploying a Free Trial.

For the Enterprise Edition, you must:

  • Create an account on Quay.io to access Dremio's OCI repository, which stores Dremio's Helm charts and images.
    To get access, contact your Dremio account executive or Dremio Support.
    note

    If your internet access doesn't allow reaching Dremio's OCI repository in Quay.io, consider using a private mirror to fetch Dremio's Helm chart images.

  • Get a valid license key issued by Dremio to put in the Helm chart. To obtain the license, refer to Licensing.

Additional Prerequisites for the OpenShift

FREE TRIAL

Ignore the prerequisites in this section if deploying a Free Trial.

Before deploying Dremio onto OpenShift, you additionally need the following:

  • Have the OpenShift oc CLI command configured and authenticated. For the installation instructions, see OpenShift CLI (oc).

Node Tuning for OpenSearch on OpenShift

OpenSearch requires the vm.max_map_count kernel parameter to be set to at least 262144.

This parameter controls the maximum number of memory map areas a process can have, and OpenSearch uses memory-mapped files extensively for performance.

Without this setting, OpenSearch pods will fail to start with errors related to virtual memory limits.

Since the Helm chart sets setVMMaxMapCount: false for OpenShift compatibility (to avoid privileged init containers), you need to configure this kernel parameter at the node level. The recommended way to do it is a Node Tuning Operator. This Operator ships with OpenShift and provides a declarative way to configure kernel parameters.

Create a Tuned resource to configure the required kernel parameter:

The tuned-opensearch.yaml configuration file
apiVersion: tuned.openshift.io/v1
kind: Tuned
metadata:
name: openshift-opensearch
namespace: openshift-cluster-node-tuning-operator
spec:
profile:
- data: |
[main]
summary=Optimize systems running OpenSearch on OpenShift nodes
include=openshift-node
[sysctl]
vm.max_map_count=262144
name: openshift-opensearch
recommend:
- match:
- label: tuned.openshift.io/opensearch
type: pod
priority: 20
profile: openshift-opensearch

This YAML should be saved locally and applied to any cluster you intend to deploy Dremio:

oc apply -f tuned-opensearch.yaml

Step 1: Deploying Dremio to Kubernetes

To deploy the Dremio cluster in Kubernetes, do the following:

  1. Configure your values to deploy Dremio to Kubernetes in the file values-overrides.yaml. To configure it, follow along Configuring Your Values to Deploy Dremio to Kubernetes.

  2. On your terminal, start the deployment by installing Dremio's Helm chart:

    Run the following command for any Kubernetes environment except for OpenShift:

    helm install <your-dremio-install-release> oci://quay.io/dremio/dremio-helm \
    --values <your-local-path>/values-overrides.yaml \
    --version <optional-helm-chart-version> \
    --set-file <optional-config-files> \
    --wait

    Where:

    • <your-dremio-install-release> - The name that identifies your Dremio installation. For example, dremio-1-0.
    • <your-local-path>/values-overrides.yaml - The path to reach your values-overrides.yaml configuration file.
    • (Optional) --version <optional-helm-chart-version> - The version of Dremio's Helm chart to be used. If not provided defaults to the latest.
    • (Optional) --set-file <optional-config-file> - An optional configuration file for deploying Dremio. For example, an Identity Provider configuration file, which is not defined in the values-overrides.yaml and can be provided here through this option.
  3. Monitor the deployment using the following commands:

    Run the following command for any Kubernetes environment except for OpenShift:

    kubectl get pods

    When all of the pods are in the Ready state, the deployment is complete.

    Troubleshooting
    • If a pod remains in Pending state for more than a few minutes, run the following command to view its status to check for issues, such as insufficient resources for scheduling:

      $ kubectl describe pods <pod-name>
    • If the events at the bottom of the output mention insufficient CPU or memory, do one of the following:

      • Adjust the values in the values-overrides.yaml configuration file and redeploy.

      • Add more resources to your Kubernetes cluster.

    • If a pod returns a failed state (especially dremio-master-0, the most important pod), use the following commands to collect the logs:

      Run the following command for any Kubernetes environment except for OpenShift:

      kubectl logs dremio-master-0

Step 2: Connecting to Dremio

Now that you've installed the Helm chart and deployed Dremio on Kubernetes, the next step is connecting to Dremio, where you have the following options:

Connecting to the Dremio Console

Run the following command to use the services dremio-client in Kubernetes to find the host for the Dremio Console:

$ kubectl get services dremio-client
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
... ... ... ... ... ...
  • If the value in the TYPE column of the output is LoadBalancer, access the Dremio UI through the address in the EXTERNAL_IP column and port 9047.
    For example, in the output below, the value under the EXTERNAL-IP column is 8.8.8.8. Therefore, access the Dremio UI through http://8.8.8.8:9047.

    $ kubectl get services dremio-client
    NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
    dremio-client LoadBalancer 10.99.227.180 8.8.8.8 31010:32260/TCP,9047:30620/TCP 2d

    If you want to change the exposed port on the load balancer, change the value of the setting coordinator.web.port in the file values-overrides.yaml.

  • If the value in the TYPE column of the output is NodePort, access the Dremio UI through http://localhost:30670.

OpenShift Route

To expose Dremio externally using OpenShift Routes do the following:

$ oc expose service dremio-client --port=9047 --name=dremio-ui

$ oc get route dremio-ui -o jsonpath='{.spec.host}'

Connecting to Dremio from BI Tools via ODBC/JDBC

Run the following command to use the services dremio-client in Kubernetes to find the host for ODBC/JDBC connections by using the following command:

$ kubectl get services dremio-client
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
... ... ... ... ... ...
  • If the value in the TYPE column of the output is LoadBalancer, access Dremio using ODBC/JDBC through the address in the EXTERNAL_IP column and port 31010.
    For example, in the output below, the value under the EXTERNAL-IP column is 8.8.8.8. Therefore, access Dremio using ODBC/JDBC in port 31010 through http://8.8.8.8:31010.

    $ kubectl get services dremio-client
    NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
    dremio-client LoadBalancer 10.99.227.180 8.8.8.8 31010:32260/TCP,9047:30620/TCP 2d

    If you want to change the exposed port on the load balancer, change the value of the setting coordinator.client.port in the file values-overrides.yaml.

  • If the value in the TYPE column of the output is NodePort, access Dremio using ODBC/JDBC through http://localhost:32390.

Connecting to Dremio from BI Tools via Apache Arrow Flight

Run the following command to use the services dremio-client in Kubernetes to find the host for Apache Arrow Flight connections by using the following command:

$ kubectl get services dremio-client
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
... ... ... ... ... ...
  • If the value in the TYPE column of the output is LoadBalancer, access Dremio using Apache Arrow Flight through the address in the EXTERNAL_IP column and port 32010.
    For example, in the output below, the value under the EXTERNAL-IP column is 8.8.8.8. Therefore, access Dremio using Apache Arrow Flight through http://8.8.8.8:32010.

    $ kubectl get services dremio-client
    NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
    dremio-client LoadBalancer 10.99.227.180 8.8.8.8 31010:32260/TCP,9047:30620/TCP 2d

    If you want to change the exposed port on the load balancer, change the value of the setting coordinator.flight.port in the file values-overrides.yaml.

  • If the value in the TYPE column of the output is NodePort, access Dremio using Apache Arrow Flight through http://localhost:31357.