Setting up (Kubernetes)¶
DSS is not responsible for setting up your local Docker daemon
The prerequisites for running workloads in Kubernetes are:
- You need to have an existing Docker daemon. The
dockercommand on the DSS machine must be fully functional and usable by the user running DSS. That includes the permission to build images, and thus access to a Docker socket.
- You need to have an image registry, accessible by your Kubernetes cluster
- The local
dockercommand must have permission to push images to your image registry
kubectlcommand must be installed on the DSS machine and be usable by the user running DSS
Before you can deploy to Kubernetes, at least one “base image” must be constructed.
After each upgrade of DSS, you must rebuild all base images
From the DSS data directory, run
You then need to create containerized execution configurations. In Administration > Settings > Containerized execution, click “Add another config” to create a new configuration.
Select Kubernetes and specify your image repository. You will then need to push the base image using the eponymous button.
Containerized execution configuration can be chosen:
- In the project settings. In that case, it will apply by default to all project activities that can run on containers
- In a recipe’s advanced settings
- In the “Execution environment” tab of in-memory machine learning Design screen