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+# 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.
+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.
+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:
+spec:
+ scaleTargetRef:
+ deploymentName:
+ 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.
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