add KEDA (#123)

howto/autoscale-with-keda/README.md

@@ -0,0 +1,85 @@
+# Autoscaling a Dapr app with KEDA
+
+Dapr is a programming model that's being installed and operated using a sidecar, and thus leaves autoscaling to the hosting layer, for example Kubernetes.
+Many of Dapr's [bindings](../../concepts/bindings#supported-bindings-and-specs) overlap with those of [KEDA](https://github.com/kedacore/keda), an Event Driven Autoscaler for Kubernetes.
+
+For apps that use these bindings, its easy to configure a KEDA autoscaler.
+
+## Install KEDA
+
+To install KEDA, follow [these instructions](https://github.com/dapr/docs/tree/master/concepts/bindings#supported-bindings-and-specs) on the KEDA Github page.
+
+## Create KEDA enabled Dapr binding
+
+For this example, we'll be using Kafka.<br>
+You can install Kafka in your cluster by using Helm:
+
+```
+# helm repo add incubator http://storage.googleapis.com/kubernetes-charts-incubator
+$ helm install --name my-kafka incubator/kafka
+```
+
+Next, we'll create the Dapr Kafka binding for Kubernetes.<br>
+Paste the following in a file named kafka.yaml:
+
+```yaml
+apiVersion: dapr.io/v1alpha1
+kind: Component
+metadata:
+  name: kafkaevent
+spec:
+  type: bindings.kafka
+  metadata:
+  - name: brokers
+    value: "my-kafka:9092"
+  - name: topics
+    value: "myTopic"
+  - name: consumerGroup
+    value: "group1"
+```
+
+The following YAML defines a Kafka component that listens for the topic `myTopic`, with consumer group `group1` and that connects to a broker at `my-kafka:9092`.
+
+Deploy the binding to the cluster:
+
+```
+$ kubectl apply -f kafka.yaml
+```
+
+## Create the KEDA autoscaler for Kafka
+
+Paste the following to a file named kafka_scaler.yaml, and put the name of your Deployment in the required places:
+
+```yaml
+apiVersion: keda.k8s.io/v1alpha1
+kind: ScaledObject
+metadata:
+  name: kafka-scaler
+  namespace: default
+  labels:
+    deploymentName: <REPLACE-WITH-DEPLOYMENT-NAME>
+spec:
+  scaleTargetRef:
+    deploymentName: <REPLACE-WITH-DEPLOYMENT-NAME>
+  triggers:
+  - type: kafka
+    metadata:
+      type: kafkaTrigger
+      direction: in
+      name: event
+      topic: myTopic
+      brokers:  my-kafka:9092
+      consumerGroup: group2
+      dataType: binary
+      lagThreshold: '5'
+```
+
+Deploy the KEDA scaler to Kubernetes:
+
+```
+$ kubectl apply -f kafka_scaler.yaml
+```
+
+All done!
+
+You can now start publishing messages to your Kafka topic `myTopic` and watch the pods autoscale when the lag threshold is bigger than `5`, as defined in the KEDA scaler manifest.