seldon-single-model

Chart to deploy a machine learning model in Seldon Core v1.

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

Source Code

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

• https://github.com/SeldonIO/seldon-core/tree/master/helm-charts/seldon-single-model

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