> For the complete documentation index, see [llms.txt](https://docs.seldon.ai/seldon-enterprise-platform/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.seldon.ai/seldon-enterprise-platform/production-environment/seldon-core-2.md).

# Seldon Core 2

Seldon Core 2 provides a state of the art solution for machine learning inference.

### Prerequisites

* Set up and connect to a Kubernetes cluster running version 1.23 or later. For instructions on connecting to your Kubernetes cluster, refer to the documentation provided by your cloud provider.
* Install [kubectl](https://kubernetes.io/docs/tasks/tools/#kubectl), the Kubernetes command-line tool.
* Install [Helm](https://helm.sh/docs/intro/install/), the package manager for Kubernetes.

To use Seldon Core 2 in a production environment:

1. [Create namespaces](#creating-namespaces)
2. [Install Seldon Core 2](#installing-seldon-core-2)

### Creating Namespaces

* Create a namespace to contain the main components of Seldon. For example, create the namespace `seldon-system`:

  ```bash
  kubectl create ns seldon-system || echo "Namespace seldon-system already exists"
  ```
* Create a namespace to contain Kafka. For example, create the namespace `kafka`:

  ```bash
  kubectl create ns kafka || echo "Namespace kafka already exists"
  ```
* Create a namespace to contain the components related to request logging. For example, create the namespace `seldon-logs`:

  ```bash
  kubectl create ns seldon-logs || echo "Namespace seldon-logs already exists"
  ```
* Create a namespace that is accessible by Seldon Enterprise Platform, Seldon Core 2 runtime that defines core components required in each model, and Seldon Core 2 pre-configured servers to host the models. For example, create the namespace `seldon`:

  ```bash
  kubectl create ns seldon || echo "Namespace seldon already exists"
  ```
* Annotate the namespace `seldon` so that it is accessible in the Seldon Enterprise Platform UI:

  ```bash
  kubectl label ns seldon seldon.restricted=false --overwrite=true
  ```

### Installing Seldon Core 2

1. Add and update the Helm charts `seldon-charts` to the repository.

   ```bash
   helm repo add seldon-charts https://seldonio.github.io/helm-charts/
   helm repo update seldon-charts
   ```
2. Install Custom resource definitions for Seldon Core 2.

   ```bash
   helm upgrade seldon-core-v2-crds seldon-charts/seldon-core-v2-crds \
   --version 2.8.5 \
   --namespace default \
   --install 
   ```
3. Create a YAML file to specify the initial configuration for Seldon Core 2 operator. For example, create the `components-values.yaml` file. Use your preferred text editor to create and save the file with the following content:

   ```yaml
   controller:
     clusterwide: true

   dataflow:
     resources:
       cpu: 500m

   envoy:
     service:
       type: ClusterIP

   kafka:
     bootstrap: seldon-kafka-bootstrap.kafka:9092
     topics:
       numPartitions: 4

   opentelemetry:
     enable: false

   scheduler:
     service:
       type: ClusterIP

   serverConfig:
     mlserver:
       resources:
         cpu: 1
         memory: 2Gi

     triton:
       resources:
         cpu: 1
         memory: 2Gi

   serviceGRPCPrefix: "http2-"
   ```

   This configuration installs the Seldon Core 2 Operator to work across an entire Kubernetes cluster. If you wish to install the operator in a specific namespace instead, set `clusterwide` to `false` in the `components-values.yaml` file.
4. Change to the directory that contains the `components-values.yaml` file and then install Seldon Core 2 operator in the namespace `seldon-system`.

   ```bash
    helm upgrade seldon-core-v2-components seldon-charts/seldon-core-v2-setup \
    --version 2.8.5 \
    -f components-values.yaml \
    --namespace seldon-system \
    --install
   ```
5. Install Seldon Core 2 runtimes in the namespace `seldon`.

   ```bash
   helm upgrade seldon-core-v2-runtime seldon-charts/seldon-core-v2-runtime \
   --version 2.8.5 \
   --namespace seldon \
   --install
   ```

   <div data-gb-custom-block data-tag="hint" data-style="warning" class="hint hint-warning"><p>One of the runtime components installed in this step is the <code>Dataflow Engine</code>. It requires a running Kafka instance to function properly. Ensure that you have a Kafka bootstrap server running at <code>seldon-kafka-bootstrap.kafka:9092</code>, as specified in the YAML file in step 3. If this is not the case, you can still proceed with the next step and resolve this issue in a later step, when you <a href="/pages/buUHGNpfYJ24aaKUWhgP">install Kafka</a>.</p></div>
6. Create a YAML file to specify the initial configuration for Seldon Core 2 servers. For example, create the `servers-values.yaml` file. Use your preferred text editor to create and save the file with the following content:

   ```yaml
   mlserver:
    replicas: 1

   triton:
     replicas: 1
   ```
7. Change to the directory that contains the `servers-values.yaml` file and then install Seldon Core 2 servers in the namespace `seldon`.

   ```bash
    helm upgrade seldon-core-v2-servers seldon-charts/seldon-core-v2-servers \
    --version 2.8.5 \
    -f servers-values.yaml \
    --namespace seldon \
    --install
   ```

### Additional Resources

* [Seldon Core 2 Documentation](https://docs.seldon.ai/seldon-core-2)
* [GKE Documentation](https://cloud.google.com/kubernetes-engine/docs)
* [AWS Documentation](https://docs.aws.amazon.com/)
* [Azure Documentation](https://learn.microsoft.com/azure/)