Implementation:SeldonIO Seldon core Seldon Model Load For Monitoring
Appearance
| Property | Value |
|---|---|
| Implementation Name | Seldon Model Load For Monitoring |
| Type | External Tool Doc |
| Overview | Concrete CLI tool for deploying monitoring pipeline component models in Seldon Core 2 |
| Domains | MLOps, Kubernetes |
| Implements Principle | SeldonIO_Seldon_core_Monitoring_Component_Deployment |
| Source | samples/models/income.yaml:L1-8, samples/models/income-preprocess.yaml:L1-8, samples/models/income-drift.yaml:L1-9, samples/models/income-outlier.yaml:L1-9 |
| External Dependencies | seldon CLI, kubectl, MLServer, alibi-detect runtime |
| Knowledge Sources | Repo (https://github.com/SeldonIO/seldon-core) |
| Last Updated | 2026-02-13 00:00 GMT |
Code Reference
Classifier Model (income.yaml)
apiVersion: mlops.seldon.io/v1alpha1
kind: Model
metadata:
name: income
spec:
storageUri: "gs://seldon-models/scv2/samples/mlserver_1.6.0/income-sklearn/classifier"
requirements:
- sklearn
Preprocessor Model (income-preprocess.yaml)
apiVersion: mlops.seldon.io/v1alpha1
kind: Model
metadata:
name: income-preprocess
spec:
storageUri: "gs://seldon-models/scv2/samples/mlserver_1.6.0/income-sklearn/preprocessor"
requirements:
- sklearn
Drift Detector Model (income-drift.yaml)
apiVersion: mlops.seldon.io/v1alpha1
kind: Model
metadata:
name: income-drift
spec:
storageUri: "gs://seldon-models/scv2/samples/mlserver_1.6.0/income-sklearn/drift-detector"
requirements:
- mlserver
- alibi-detect
Outlier Detector Model (income-outlier.yaml)
apiVersion: mlops.seldon.io/v1alpha1
kind: Model
metadata:
name: income-outlier
spec:
storageUri: "gs://seldon-models/scv2/samples/mlserver_1.6.0/income-sklearn/outlier-detector"
requirements:
- mlserver
- alibi-detect
Key Parameters
| Parameter | Description | Values |
|---|---|---|
| apiVersion | Seldon Core 2 API version | mlops.seldon.io/v1alpha1 |
| kind | Resource type | Model |
| metadata.name | Unique model identifier | income, income-preprocess, income-drift, income-outlier |
| spec.storageUri | Cloud storage path to model artifacts | gs://seldon-models/scv2/samples/... |
| spec.requirements | MLServer runtime requirements | sklearn (classifier/preprocessor), mlserver + alibi-detect (detectors) |
I/O Contract
Inputs
| Input | Type | Description |
|---|---|---|
| income.yaml | Model CRD YAML | Classifier model definition |
| income-preprocess.yaml | Model CRD YAML | Preprocessor model definition |
| income-drift.yaml | Model CRD YAML | Drift detector model definition |
| income-outlier.yaml | Model CRD YAML | Outlier detector model definition |
Outputs
| Output | Type | Description |
|---|---|---|
| income | Loaded Model | Classifier ready for inference (sklearn runtime) |
| income-preprocess | Loaded Model | Preprocessor ready for feature transformation (sklearn runtime) |
| income-drift | Loaded Model | Drift detector ready for batch drift testing (alibi-detect runtime) |
| income-outlier | Loaded Model | Outlier detector ready for per-request anomaly detection (alibi-detect runtime) |
Usage Examples
Loading All Four Monitoring Components
# Load all four models
seldon model load -f samples/models/income.yaml
seldon model load -f samples/models/income-preprocess.yaml
seldon model load -f samples/models/income-drift.yaml
seldon model load -f samples/models/income-outlier.yaml
Waiting for All Models to Be Ready
# Wait for each model to reach ModelAvailable state
seldon model status income -w ModelAvailable
seldon model status income-preprocess -w ModelAvailable
seldon model status income-drift -w ModelAvailable
seldon model status income-outlier -w ModelAvailable
Verifying Runtime Assignments
| Model | Runtime | Description |
|---|---|---|
| income | sklearn | RandomForestClassifier via joblib |
| income-preprocess | sklearn | ColumnTransformer via joblib |
| income-drift | alibi-detect | TabularDrift detector |
| income-outlier | alibi-detect | OutlierVAE detector |
Related Pages
- SeldonIO_Seldon_core_Monitoring_Component_Deployment (principle) - Principles of deploying monitoring components as independent services
- SeldonIO_Seldon_core_Alibi_Detect_Training (prerequisite) - Training code that produces the detector artifacts
- SeldonIO_Seldon_core_Seldon_Pipeline_CRD_Monitoring (next step) - Composing loaded models into a monitoring pipeline
- SeldonIO_Seldon_core_Seldon_Model_Load (related) - General model loading tool documentation
- SeldonIO_Seldon_core_Seldon_Model_CRD (related) - General Model CRD structure
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