name: Kubeflow - Serve Model using KFServing description: Serve Models using Kubeflow KFServing inputs: - {name: Action, type: String, default: 'create', description: 'Action to execute on KFServing'} - {name: Model Name, type: String, default: '', description: 'Name to give to the deployed model'} - {name: Default Model URI, type: String, default: '', description: 'Path of the S3 or GCS compatible directory containing default model.'} - {name: Canary Model URI, type: String, default: '', description: 'Optional Path of the S3 or GCS compatible directory containing canary model.'} - {name: Canary Model Traffic Percentage, type: String, default: '0', description: 'Optional Traffic to be sent to default model'} - {name: Namespace, type: String, default: 'kubeflow', description: 'Kubernetes namespace where the KFServing service is deployed.'} - {name: Framework, type: String, default: 'tensorflow', description: 'Machine Learning Framework for Model Serving.'} - {name: Default Custom Model Spec, type: String, default: '{}', description: 'Custom runtime default custom model container spec.'} - {name: Canary Custom Model Spec, type: String, default: '{}', description: 'Custom runtime canary custom model container spec.'} - {name: Autoscaling Target, type: String, default: '0', description: 'Autoscaling Target Number'} - {name: KFServing Endpoint, type: String, default: '', description: 'KFServing remote deployer API endpoint'} - {name: Service Account, type: String, default: '', description: 'Model Service Account'} outputs: - {name: Service Endpoint URI, type: String, description: 'URI of the deployed prediction service..'} implementation: container: image: aipipeline/kfserving-component:v0.3.0 command: ['python'] args: [ -u, kfservingdeployer.py, --action, {inputValue: Action}, --model-name, {inputValue: Model Name}, --default-model-uri, {inputValue: Default Model URI}, --canary-model-uri, {inputValue: Canary Model URI}, --canary-model-traffic, {inputValue: Canary Model Traffic Percentage}, --namespace, {inputValue: Namespace}, --framework, {inputValue: Framework}, --default-custom-model-spec,{inputValue: Default Custom Model Spec}, --canary-custom-model-spec, {inputValue: Canary Custom Model Spec}, --kfserving-endpoint, {inputValue: KFServing Endpoint}, --autoscaling-target, {inputValue: Autoscaling Target}, --service-account, {inputValue: Service Account}, --output-path, {outputPath: Service Endpoint URI} ]