https://ops.docs.72602.space/kubernetes/serverless/knative/eventing/async_prediction_flow/index.html Flow flowchart LR A[User Curl] -->|HTTP| B{ISVC-Broker:Kafka} B -->|Subscribe| D[Trigger1] B -->|Subscribe| E[Kserve-Triiger] B -->|Subscribe| F[Trigger3] E --> G[Mnist Service] G --> |Kafka-Sink| B Setps 1. Create Broker Setting kubectl apply -f - <<EOF apiVersion: v1 kind: ConfigMap metadata: name: kafka-broker-config namespace: knative-eventing data: default.topic.partitions: "10" default.topic.replication.factor: "1" bootstrap.servers: "kafka.database.svc.cluster.local:9092" #kafka service address default.topic.config.retention.ms: "3600" EOF 2. Create Broker kubectl apply -f - <<EOF apiVersion: eventing.knative.dev/v1 kind: Broker metadata: annotations: eventing.knative.dev/broker.class: Kafka name: isvc-broker namespace: kserve-test spec: config: apiVersion: v1 kind: ConfigMap name: kafka-broker-config namespace: knative-eventing EOF 3. Create Trigger kubectl apply -f - << EOF apiVersion: eventing.knative.dev/v1 kind: Trigger metadata: name: kserve-trigger namespace: kserve-test spec: broker: isvc-broker filter: attributes: type: prediction-request-udf-attr # you can change this subscriber: uri: http://prediction-and-sink.kserve-test.svc.cluster.local/v1/models/mnist:predict EOF 4. Create InferenceService 1kubectl apply -f - <<EOF 2apiVersion: serving.kserve.io/v1beta1 3kind: InferenceService 4metadata: 5 name: prediction-and-sink 6 namespace: kserve-test 7spec: 8 predictor: 9 model: 10 modelFormat: 11 name: pytorch 12 storageUri: gs://kfserving-examples/models/torchserve/image_classifier/v1 13 transformer: 14 containers: 15 - image: docker-registry.lab.zverse.space/data-and-computing/ay-dev/msg-transformer:dev9 16 name: kserve-container 17 env: 18 - name: KAFKA_BOOTSTRAP_SERVERS 19 value: kafka.database.svc.cluster.local 20 - name: KAFKA_TOPIC 21 value: test-topic # result will be saved in this topic 22 - name: REQUEST_TRACE_KEY 23 value: test-trace-id # using this key to retrieve preidtion result 24 command: 25 - "python" 26 - "-m" 27 - "model" 28 args: 29 - --model_name 30 - mnist 31EOF Expectd Output root@ay-k3s01:~# kubectl -n kserve-test get pod NAME READY STATUS RESTARTS AGE prediction-and-sink-predictor-00001-deployment-f64bb76f-jqv4m 2/2 Running 0 3m46s prediction-and-sink-transformer-00001-deployment-76cccd867lksg9 2/2 Running 0 4m3s Expectd Output Source code of the docker-registry.lab.zverse.space/data-and-computing/ay-dev/msg-transformer:dev9 could be found 🔗here Hugo en