apiVersion: serving.kserve.io/v1beta1
kind: InferenceService
metadata:
  name: iris-classifier
  namespace: kserve
  annotations:
    serving.kserve.io/secretName: kserve-s3-credentials
spec:
  predictor:
    model:
      modelFormat:
        name: mlflow
        version: "2"
      storageUri: s3://mlflow/EXPERIMENT_ID/models/MODEL_ID/artifacts
      resources:
        requests:
          cpu: "100m"
          memory: "512Mi"
        limits:
          cpu: "1000m"
          memory: "1Gi"
---
# Alternative: Using SKLearn Server (does not install requirements.txt)
# apiVersion: serving.kserve.io/v1beta1
# kind: InferenceService
# metadata:
#   name: iris-classifier
#   namespace: kserve
#   annotations:
#     serving.kserve.io/secretName: kserve-s3-credentials
# spec:
#   predictor:
#     model:
#       modelFormat:
#         name: sklearn
#         version: "1"
#       storageUri: s3://mlflow/EXPERIMENT_ID/models/MODEL_ID/artifacts
#       resources:
#         requests:
#           cpu: "100m"
#           memory: "256Mi"
#         limits:
#           cpu: "500m"
#           memory: "512Mi"