Implementation:SeldonIO Seldon core Seldon Experiment Start
Appearance
| Field | Value |
|---|---|
| Type | External Tool Doc |
| Overview | Concrete CLI tool for starting A/B test and traffic mirroring experiments in Seldon Core 2. |
| Domains | MLOps, Experimentation |
| Related Principle | SeldonIO_Seldon_core_Experiment_Execution |
| Source | docs-gb/cli/seldon_experiment_start.md:L1-25, samples/local-experiments.md:L109-127
|
| Knowledge Sources | Repo, Doc |
| Last Updated | 2026-02-13 00:00 GMT |
Description
This implementation provides the concrete CLI commands for starting A/B test and traffic mirroring experiments in Seldon Core 2. The seldon experiment start command submits an Experiment CRD to the Seldon scheduler, which activates traffic routing according to the specified weights and mirror configuration. Alternatively, kubectl apply can be used to apply the experiment manifest directly to the Kubernetes API.
Code Reference
CLI Signature
seldon experiment start -f <experiment.yaml> [--scheduler-host string] [--force]
Alternative: kubectl
kubectl apply -f <experiment.yaml>
Full Example: Start an A/B Test
# Ensure candidates are loaded and ready
seldon model status iris -w ModelAvailable
seldon model status iris2 -w ModelAvailable
# Start the experiment
seldon experiment start -f samples/experiments/ab-default-model.yaml
# Verify experiment is active
seldon experiment status experiment-sample -w | head -1
Full Example: Start a Mirror Experiment
# Start mirroring experiment
seldon experiment start -f samples/experiments/sklearn-mirror.yaml
# Verify mirror experiment is active
seldon experiment status sklearn-mirror -w | head -1
I/O Contract
| Direction | Description |
|---|---|
| Inputs | Experiment CRD YAML file. All candidate models and/or pipelines referenced in the manifest must be deployed and ready before starting the experiment. |
| Outputs | Experiment active: traffic splitting or mirroring engaged on the default endpoint. The scheduler updates its routing table and begins probabilistically routing requests to candidates. |
Key Parameters
| Parameter | Description | Default | Required |
|---|---|---|---|
-f / --file-path |
Path to the experiment manifest YAML file | — | Yes |
--scheduler-host |
Address of the Seldon scheduler | 0.0.0.0:9004 |
No |
--force |
Force start even if experiment is already running | false |
No |
Usage Examples
Start A/B Test Between Two Models
# Define the experiment manifest (ab-test.yaml)
# Then start it
seldon experiment start -f ab-test.yaml
Start with Custom Scheduler Host
seldon experiment start -f ab-test.yaml --scheduler-host scheduler.seldon-mesh:9004
Start and Immediately Verify
# Start experiment and wait for active status
seldon experiment start -f ab-test.yaml
seldon experiment status experiment-sample -w | head -1
# Run a quick inference to verify routing
seldon model infer iris '{"inputs": [{"name": "predict", "shape": [1, 4], "datatype": "FP32", "data": [[1, 2, 3, 4]]}]}' --show-headers
Using kubectl
# Apply the experiment
kubectl apply -f samples/experiments/ab-default-model.yaml
# Check experiment status
kubectl get experiments experiment-sample -o yaml
External Dependencies
- seldon CLI — Command-line tool for interacting with Seldon Core 2 scheduler
- kubectl — Kubernetes CLI for applying CRD manifests (alternative method)
- Seldon scheduler — Orchestrates experiment routing; must be running and accessible
Related Pages
- SeldonIO_Seldon_core_Experiment_Execution — principle for this implementation — Activating an experiment to begin traffic splitting or mirroring between model candidates.
- SeldonIO_Seldon_core_Seldon_Experiment_CRD — prerequisite — The Experiment CRD manifest that defines the traffic routing rules.
- SeldonIO_Seldon_core_Seldon_Model_Infer_With_Headers — next step — Monitoring experiment traffic distribution using inference with response headers.
- SeldonIO_Seldon_core_Seldon_Experiment_Stop — lifecycle — Stopping the experiment when analysis is complete.
- Environment:SeldonIO_Seldon_core_Kubernetes_Cluster_Environment
Page Connections
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Principle
Implementation
Heuristic
Environment