Create a Knative-based Function to Interact with Middleware
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Create a Knative-based Function to Interact with Middleware

Learn how to create a Knative-based function to interact with middleware via Dapr components.

This document describes how to create a Knative-based function to interact with middleware via Dapr components.

Overview

Similar to asynchronous functions, the functions that are based on Knative runtime can interact with middleware through Dapr components. This document uses two functions, function-front and kafka-input, for demonstration.

The following diagram illustrates the relationship between these functions.

Prerequisites

You have installed OpenFunction.
You have created a secret.

Create a Kafka Server and Topic

Run the following commands to install strimzi-kafka-operator in the default namespace.

helm repo add strimzi https://strimzi.io/charts/
helm install kafka-operator -n default strimzi/strimzi-kafka-operator

Use the following content to create a file kafka.yaml.

apiVersion: kafka.strimzi.io/v1beta2
kind: Kafka
metadata:
  name: kafka-server
  namespace: default
spec:
  kafka:
    version: 3.1.0
    replicas: 1
    listeners:
      - name: plain
        port: 9092
        type: internal
        tls: false
      - name: tls
        port: 9093
        type: internal
        tls: true
    config:
      offsets.topic.replication.factor: 1
      transaction.state.log.replication.factor: 1
      transaction.state.log.min.isr: 1
      default.replication.factor: 1
      min.insync.replicas: 1
      inter.broker.protocol.version: "3.1"
    storage:
      type: ephemeral
  zookeeper:
    replicas: 1
    storage:
      type: ephemeral
  entityOperator:
    topicOperator: {}
    userOperator: {}
---
apiVersion: kafka.strimzi.io/v1beta2
kind: KafkaTopic
metadata:
  name: sample-topic
  namespace: default
  labels:
    strimzi.io/cluster: kafka-server
spec:
  partitions: 10
  replicas: 1
  config:
    retention.ms: 7200000
    segment.bytes: 1073741824

Run the following command to deploy a 1-replica Kafka server named kafka-server and 1-replica Kafka topic named sample-topic in the default namespace.
```
kubectl apply -f kafka.yaml
```

Run the following command to check pod status and wait for Kafka and Zookeeper to be up and running.

$ kubectl get po
NAME                                              READY   STATUS        RESTARTS   AGE
kafka-server-entity-operator-568957ff84-nmtlw     3/3     Running       0          8m42s
kafka-server-kafka-0                              1/1     Running       0          9m13s
kafka-server-zookeeper-0                          1/1     Running       0          9m46s
strimzi-cluster-operator-687fdd6f77-cwmgm         1/1     Running       0          11m

Run the following commands to view the metadata of the Kafka cluster.

# Starts a utility pod.
$ kubectl run utils --image=arunvelsriram/utils -i --tty --rm
# Checks metadata of the Kafka cluster.
$ kafkacat -L -b kafka-server-kafka-brokers:9092

Create Functions

Use the following example YAML file to create a manifest kafka-input.yaml and modify the value of spec.image to set your own image registry address. The field spec.serving.inputs defines an input source that points to a Dapr component of the Kafka server. It means that the kafka-input function will be driven by events in the topic sample-topic of the Kafka server.

apiVersion: core.openfunction.io/v1beta1
kind: Function
metadata:
  name: kafka-input
spec:
  version: "v1.0.0"
  image: <your registry name>/kafka-input:latest
  imageCredentials:
    name: push-secret
  build:
    builder: openfunction/builder-go:latest
    env:
      FUNC_NAME: "HandleKafkaInput"
      FUNC_CLEAR_SOURCE: "true"
    srcRepo:
      url: "https://github.com/OpenFunction/samples.git"
      sourceSubPath: "functions/async/bindings/kafka-input"
      revision: "main"
  serving:
    runtime: async
    scaleOptions:
      minReplicas: 0
      maxReplicas: 10 
      keda:
        scaledObject:
          pollingInterval: 15
          minReplicaCount: 0
          maxReplicaCount: 10
          cooldownPeriod: 60
          advanced:
            horizontalPodAutoscalerConfig:
              behavior:
                scaleDown:
                  stabilizationWindowSeconds: 45
                  policies:
                  - type: Percent
                    value: 50
                    periodSeconds: 15
                scaleUp:
                  stabilizationWindowSeconds: 0
    triggers:
      - type: kafka
        metadata:
          topic: sample-topic
          bootstrapServers: kafka-server-kafka-brokers.default.svc:9092
          consumerGroup: kafka-input
          lagThreshold: "20"
    inputs:
      - name: greeting
        component: target-topic
    bindings:
      target-topic:
        type: bindings.kafka
        version: v1
        metadata:
          - name: brokers
            value: "kafka-server-kafka-brokers:9092"
          - name: topics
            value: "sample-topic"
          - name: consumerGroup
            value: "kafka-input"
          - name: publishTopic
            value: "sample-topic"
          - name: authRequired
            value: "false"
    template:
      containers:
        - name: function
          imagePullPolicy: Always

Run the following command to create the function kafka-input.
```
kubectl apply -f kafka-input.yaml
```

Use the following example YAML file to create a manifest function-front.yaml and modify the value of spec.image to set your own image registry address.

apiVersion: core.openfunction.io/v1beta1
kind: Function
metadata:
  name: function-front
  annotations:
    plugins: |
      pre:
      - plugin-custom
      - plugin-example
      post:
      - plugin-custom
      - plugin-example      
spec:
  version: "v1.0.0"
  image: "<your registry name>/sample-knative-dapr:latest"
  imageCredentials:
    name: push-secret
  port: 8080 # Default to 8080
  build:
    builder: openfunction/builder-go:latest
    env:
      FUNC_NAME: "ForwardToKafka"
      FUNC_CLEAR_SOURCE: "true"
    srcRepo:
      url: "https://github.com/OpenFunction/samples.git"
      sourceSubPath: "functions/knative/with-output-binding"
      revision: "main"
  serving:
    scaleOptions:
      minReplicas: 0
      maxReplicas: 5
    runtime: knative
    outputs:
      - name: target
        component: kafka-server
        operation: "create"
    bindings:
      kafka-server:
        type: bindings.kafka
        version: v1
        metadata:
          - name: brokers
            value: "kafka-server-kafka-brokers:9092"
          - name: authRequired
            value: "false"
          - name: publishTopic
            value: "sample-topic"
          - name: topics
            value: "sample-topic"
          - name: consumerGroup
            value: "function-front"
    template:
      containers:
        - name: function
          imagePullPolicy: Always

Note

metadata.plugins.pre defines the order of plugins that need to be called before the user function is executed. metadata.plugins.post defines the order of plugins that need to be called after the user function is executed. For more information about the logic of these two plugins and the effect of the plugins after they are executed, see Plugin mechanism.

In the manifest, spec.serving.outputs defines an output that points to a Dapr component of the Kafka server. That allows you to send custom content to the output target in the function function-front.
```
func Sender(ctx ofctx.Context, in []byte) (ofctx.Out, error) {
  ...
    _, err := ctx.Send("target", greeting)
    ...
}
```
Run the following command to create the function function-front.
```
kubectl apply -f function-front.yaml
```

Check Results

Run the following command to view the status of the functions.

$ kubectl get functions.core.openfunction.io
NAME             BUILDSTATE   SERVINGSTATE   BUILDER         SERVING         URL                                             AGE
function-front   Succeeded    Running        builder-bhbtk   serving-vc6jw   http://openfunction.io/default/function-front   2m41s
kafka-input      Succeeded    Running        builder-dprfd   serving-75vrt                                                   2m21s

Note

The URL, provided by the OpenFunction Domain, is the address that can be accessed. To access the function through this URL address, you need to make sure that DNS can resolve this address.

Run the following command to create a pod in the cluster for accessing the function.
```
kubectl run curl --image=radial/busyboxplus:curl -i --tty --rm
```

Run the following command to access the function through URL.

[ root@curl:/ ]$ curl -d '{"message":"Awesome OpenFunction!"}' -H "Content-Type: application/json" -X POST http://openfunction.io.svc.cluster.local/default/function-front

Run the following command to view the log of function-front.

kubectl logs -f \
  $(kubectl get po -l \
  openfunction.io/serving=$(kubectl get functions function-front -o jsonpath='{.status.serving.resourceRef}') \
  -o jsonpath='{.items[0].metadata.name}') \
  function

The output looks as follows.

dapr client initializing for: 127.0.0.1:50001
I0125 06:51:55.584973       1 framework.go:107] Plugins for pre-hook stage:
I0125 06:51:55.585044       1 framework.go:110] - plugin-custom
I0125 06:51:55.585052       1 framework.go:110] - plugin-example
I0125 06:51:55.585057       1 framework.go:115] Plugins for post-hook stage:
I0125 06:51:55.585062       1 framework.go:118] - plugin-custom
I0125 06:51:55.585067       1 framework.go:118] - plugin-example
I0125 06:51:55.585179       1 knative.go:46] Knative Function serving http: listening on port 8080
2022/01/25 06:52:02 http - Data: {"message":"Awesome OpenFunction!"}
I0125 06:52:02.246450       1 plugin-example.go:83] the sum is: 2

Run the following command to view the log of kafka-input.

kubectl logs -f \
  $(kubectl get po -l \
  openfunction.io/serving=$(kubectl get functions kafka-input -o jsonpath='{.status.serving.resourceRef}') \
  -o jsonpath='{.items[0].metadata.name}') \
  function

The output looks as follows.

dapr client initializing for: 127.0.0.1:50001
I0125 06:35:28.332381       1 framework.go:107] Plugins for pre-hook stage:
I0125 06:35:28.332863       1 framework.go:115] Plugins for post-hook stage:
I0125 06:35:28.333749       1 async.go:39] Async Function serving grpc: listening on port 8080
message from Kafka '{Awesome OpenFunction!}'

Last modified April 13, 2022: Update EN Documents (#56) (c6c10f0)