- Enter a name for the cluster. The name cannot contain spaces or underscores.
-
Optionally, select one or more of the following packages:
-
Select Core if node(s) in the cluster should have the
core database functionality installed on them.
First-time setups should always have Core selected.
- Select Graph if a node in the cluster should have the graph server installed on it. See Graphs & Solvers Concepts for more information.
- Optionally, select to install KML (Kinetica Machine Learning) if a node should have KML installed on it. An existing Kubernetes cluster is required for KML processing. See Machine Learning for more information on KML features.
- Optionally, select to install KAgent if a node should also have KAgent installed on it. See KAgent for more information.
- Optionally, select to install RabbitMQ if setting up a ring for High Availability. Review High Availability Architecture and High Availability Configuration & Management for more information.
-
Select Core if node(s) in the cluster should have the
core database functionality installed on them.
-
For the Install Mode, select either
Online (install directly from the online Kinetica
repository) or Offline (install from uploaded packages).
If Offline is selected, click
Upload Packages, then upload a package file for each
component or driver desired for the installation.
If performing an offline installation, all necessary dependencies will need to be installed prior to cluster setup.
- For the Version, select either CUDA (GPU) or Intel (CPU-only) to determine the package variant to install.
- If the Version is set to CUDA, ensure Automatically install Nvidia driver is selected. This will automatically configure the server(s) for an Nvidia GPU driver and install the most compatible driver.
- Enter the license key.
- If KML is selected to install, upload a configuration file for an already-existing Kubernetes installation. Note that KML requires Kubernetes; see Machine Learning for more information.
- Click Next.