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Quickstart

For the quickstart we have examples for Kind or k3s.

  • Kind - is suitable for CPU only installations.
  • k3s - is suitable for CPU or GPU installations.

Kubernetes >= 1.25

The current version of the chart supports kubernetes version 1.25 and above.

Please select your target Kubernetes variant:

Kind (kubernetes in docker kind.sigs.k8s.io)

This installation in a kind cluster is for trying out the operators and the database in a non-production environment.

CPU Only

This method currently only supports installing a CPU version of the database.

Please contact Kinetica Support to request a trial key.

Create Kind Cluster 1.29

Create a new Kind Cluster
wget https://raw.githubusercontent.com/kineticadb/charts/72.2.3/kinetica-operators/kind.yaml
kind create cluster --name kinetica --config kind.yaml
List Kind clusters
 kind get clusters

Set Kubernetes Context

Please set your Kubernetes Context to kind-kinetica before performing the following steps.

Kind - Install kinetica-operators including a sample db to try out

Review the values file charts/kinetica-operators/values.onPrem.kind.yaml. This is trying to install the operators and a simple db with workbench installation for a non production try out.

As you can see it is trying to create an ingress pointing towards local.kinetica. If you have a domain pointing to your machine, replace it with the correct domain name.

Kind - Install the Kinetica-Operators Chart
Add Kinetica Operators Chart Repo
helm repo add kinetica-operators https://kineticadb.github.io/charts/latest

FQDN or Local Access

By default we create an ingress pointing towards local.kinetica. If you have a domain pointing to your machine, replace/set the FQDN in the values.yaml with the correct domain name or by adding --set.

If you are on a local machine which is not having a domain name, you add the following entry to your /etc/hosts file or equivalent.

Configure local access - /etc/hosts
127.0.0.1  local.kinetica
Get & install the Kinetica-Operators Chart
wget https://raw.githubusercontent.com/kineticadb/charts/72.2.3/kinetica-operators/values.onPrem.kind.yaml

helm -n kinetica-system upgrade -i kinetica-operators kinetica-operators/kinetica-operators --create-namespace --values values.onPrem.kind.yaml --set db.gpudbCluster.license="your_license_key" --set dbAdminUser.password="your_password"

or if you have been asked by the Kinetica Support team to try a development version

Using a development version
helm search repo kinetica-operators --devel --versions

helm -n kinetica-system upgrade -i kinetica-operators kinetica-operators/kinetica-operators/ --create-namespace --values values.onPrem.kind.yaml --set db.gpudbCluster.license="your_license_key" --set dbAdminUser.password="your_password" --devel --version 72.2.3

Accessing the Workbench

You should be able to access the workbench at http://local.kinetica

k3s (k3s.io)

Install k3s 1.29

Install k3s
curl -sfL https://get.k3s.io | INSTALL_K3S_EXEC="--disable=traefik  --node-name kinetica-master --token 12345" K3S_KUBECONFIG_OUTPUT=~/.kube/config_k3s K3S_KUBECONFIG_MODE=644 INSTALL_K3S_VERSION=v1.29.2+k3s1 sh -

Once installed we need to set the current Kubernetes context to point to the newly created k3s cluster.

Select if you want local or remote access to the Kubernetes Cluster: -

For only local access to the cluster we can simply set the KUBECONFIG environment variable

Set kubectl context
export KUBECONFIG=/etc/rancher/k3s/k3s.yaml

For remote access i.e. outside the host/VM k3s is installed on: -

Copy /etc/rancher/k3s/k3s.yaml on your machine located outside the cluster as ~/.kube/config. Then edit the file and replace the value of the server field with the IP or name of your K3s server.

Copy the kube config and set the context
sudo chmod 600 /etc/rancher/k3s/k3s.yaml
mkdir -p ~/.kube
sudo cp /etc/rancher/k3s/k3s.yaml ~/.kube/config
sudo chown "${USER:=$(/usr/bin/logname)}:$USER" ~/.kube/config
# Edit the ~/.kube/config server field with the IP or name of your K3s server here
export KUBECONFIG=~/.kube/config

K3s - Install kinetica-operators including a sample db to try out

Review the values file charts/kinetica-operators/values.onPrem.k3s.yaml. This is trying to install the operators and a simple db with workbench installation for a non production try out.

FQDN or Local Access

By default we create an ingress pointing towards local.kinetica. If you have a domain pointing to your machine, replace/set the FQDN in the values.yaml with the correct domain name or by adding --set.

If you are on a local machine which is not having a domain name, you add the following entry to your /etc/hosts file or equivalent.

Configure local access - /etc/hosts
127.0.0.1  local.kinetica

K3S - Install the Kinetica-Operators Chart (CPU)

Add Kinetica Operators Chart Repo
helm repo add kinetica-operators https://kineticadb.github.io/charts/latest
Download Template values.yaml
wget https://raw.githubusercontent.com/kineticadb/charts/72.2.3/kinetica-operators/values.onPrem.k3s.yaml

helm -n kinetica-system install kinetica-operators kinetica-operators/kinetica-operators --create-namespace --values values.onPrem.k3s.yaml --set db.gpudbCluster.license="your_license_key" --set dbAdminUser.password="your_password"

or if you have been asked by the Kinetica Support team to try a development version

Using a development version
helm search repo kinetica-operators --devel --versions

helm -n kinetica-system install kinetica-operators kinetica-operators/kinetica-operators --create-namespace --values values.onPrem.k3s.yaml --set db.gpudbCluster.license="your_license_key" --set dbAdminUser.password="your_password" --devel --version 7.2.0-2.rc-2

K3S - Install the Kinetica-Operators Chart (GPU)

If you wish to try out the GPU capabilities, you can use the following values file, provided you are in a nvidia gpu capable machine.

k3s GPU Installation
wget https://raw.githubusercontent.com/kineticadb/charts/72.2.3/kinetica-operators/values.onPrem.k3s.gpu.yaml

helm -n kinetica-system install kinetica-operators charts/kinetica-operators/ --create-namespace --values values.onPrem.k3s.gpu.yaml --set db.gpudbCluster.license="your_license_key" --set dbAdminUser.password="your_password"

Accessing the Workbench

You should be able to access the workbench at http://local.kinetica

Uninstall k3s

uninstall k3s
/usr/local/bin/k3s-uninstall.sh

Default User

Username as per the values file mentioned above is kadmin and password is Kinetica1234!