Learning Environment
Install Seldon Core 2 in a local learning environment.
You can install Seldon Core 2 on your local computer that is running a Kubernetes cluster using kind.
Seldon publishes the Helm charts that are required to install Seldon Core 2. For more information about the Helm charts and the related dependencies,see Helm charts and Dependencies.
Note: These instructions guide you through installing Seldon Core 2 on a local Kubernetes cluster, focusing on ease of learning. Ensure your kind cluster is running on hardware with at least 32GB of RAM and a load balancer such as MetalLB is configured.
Prerequisites
Install a Kubernetes cluster that is running version 1.27 or later.
Install kubectl, the Kubernetes command-line tool.
Note: Ansible automates provisioning, configuration management, and handles all dependencies required for Seldon Core 2. With Helm, you need to configure and manage the dependencies yourself.
Installing Seldon Core 2
Create a namespace to contain the main components of Seldon Core 2. For example, create the
seldon-mesh
namespace.Add and update the Helm charts,
seldon-charts
, to the repository.Install Custom resource definitions for Seldon Core 2.
Install Seldon Core 2 operator in the
seldon-mesh
namespace.This configuration installs the Seldon Core 2 operator across an entire Kubernetes cluster. To perform cluster-wide operations, create
ClusterRoles
and ensure your user has the necessary permissions during deployment. With cluster-wide operations, you can createSeldonRuntimes
in any namespace.You can configure the installation to deploy the Seldon Core 2 operator in a specific namespace so that it control resources in the provided namespace. To do this, set
controller.clusterwide
tofalse
.Install Seldon Core 2 runtimes in the
seldon-mesh
namespace.Install Seldon Core 2 servers in the
seldon-mesh
namespace. Two example servers namedmlserver-0
, andtriton-0
are installed so that you can load the models to these servers after installation.Check Seldon Core 2 operator, runtimes, servers, and CRDS are installed in the
seldon-mesh
namespace. It might take a couple of minutes for all the Pods to be ready. To check the status of the Pods in real time use this command:kubectl get pods -w -n seldon-mesh
.The output should be similar to this:
Note: Pods with names starting with seldon-dataflow-engine
, seldon-pipelinegateway
, and seldon-modelgateway
may generate log errors until they successfully connect to Kafka. This occurs because Kafka is not yet fully integrated with Seldon Core 2.
Next Steps
If you installed Seldon Core 2 using Helm, you need to complete the installation of other components in the following order:
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