seldon-single-model

Version: 0.2.0

Chart to deploy a machine learning model in Seldon Core.

Usage

To use this chart, you will first need to add the seldonio Helm repo:

helm repo add seldonio https://storage.googleapis.com/seldon-charts
helm repo update

Once that’s done, you should then be able to use the inference graph template as:

helm template $MY_MODEL_NAME seldonio/seldon-single-model --namespace $MODELS_NAMESPACE

Note that you can also deploy the inference graph directly to your cluster using:

helm install $MY_MODEL_NAME seldonio/seldon-single-model --namespace $MODELS_NAMESPACE

Homepage: https://github.com/SeldonIO/seldon-core

Values

Key

Type

Default

Description

annotations

object

{}

Annotations applied to the deployment

apiVersion

string

"machinelearning.seldon.io/v1"

Version of the SeldonDeployment CRD

hpa.enabled

bool

false

Whether to add an HPA spec to the deployment

hpa.maxReplicas

int

5

Maximum number of replicas for HPA

hpa.metrics

list

[{"resource":{"name":"cpu","targetAverageUtilization":10},"type":"Resource"}]

Metrics that autoscaler should check

hpa.minReplicas

int

1

Minimum number of replicas for HPA

labels

object

{}

Labels applied to the deployment

model.env

object

{"LOG_LEVEL":"INFO"}

Environment variables injected into the model’s container

model.envSecretRefName

string

""

The model secret name for enviroment variables

model.image

string

""

Docker image used by the model

model.implementation

string

""

Implementation of Prepackaged Model Server

model.logger.enabled

bool

false

model.logger.url

string

""

model.mlflow.xtype

string

""

model.resources

object

{"requests":{"memory":"1Mi"}}

Resource requests and limits for the model’s container

model.uri

string

""

Model’s URI for prepackaged model server

protocol

string

"seldon"

replicas

int

1

Number of replicas for the predictor

transport

string

"rest"