1. select or create a Project in the Google Cloud console
  2. install the gcloud CLI and kubectl
  3. create a GKE cluster
  4. configure credentials to target the GKE cluster from kubectl
  5. install helm
  6. install riff on the GKE cluster using a helm chart
  7. install Docker and create a Docker ID
  8. build one of the sample functions
  9. apply the function and topic resource definitions to Kubernetes
  10. send an event to the topic to trigger the function

create a Google Cloud project

A project is required to consume any Google Cloud services, including GKE clusters. When you log into the console you can select or create a project from the dropdown at the top.

install gcloud

Follow the quickstart instructions to install the Google Cloud SDK which includes the gcloud CLI. You may need to add the google-cloud-sdk/bin directory to your path. Once installed, gcloud init will open a browser to start an oauth flow and configure gcloud to use your project. Afterwards your browser will end up on this helpful page.

gcloud init
gcloud container clusters list # will show all the clusters in your project

install kubectl

Kubectl is the Kubernetes CLI. It is used to manage minikube as well as hosted Kubernetes clusters like GKE. If you don’t already have kubectl on your machine, you can use gcloud to install it.

gcloud components install kubectl

create a GKE cluster

Look for Kubernetes Engine in the console, and create a new cluster. The minimum configuration for riff on GKE is single node cluster with 2 vCPUs and 7.5GB memory. Using the default 1.7x version of Kubernetes without RBAC will simplify the configuration.

small GKE cluster in console

configure credentials to target the GKE cluster

Once the cluster has been created, you will see a Connect button in the console. Run the first command gcloud container clusters get-credentials ... to fetch the credentials and add a new context for kubectl. Your kubectl context will be switched to the new cluster.

kubectl config current-context

remove CPU request limit

Remove the GKE default request of 0.1 CPU’s per container which limits how many containers your cluster is allowed to schedule (effectively 10 per vCPU).

kubectl delete limitrange limits

install helm

Helm is used to package and install resources for Kubernetes. Helm packages are called charts. After installing the helm CLI, point helm to the riff-charts repo.

helm repo add riffrepo
helm repo update

install riff on GKE

Use helm init to install the helm server (aka “tiller”) in your GKE cluster, then install riff.

helm init
helm install riffrepo/riff --name demo

monitor your cluster

At this point it is useful to monitor your cluster using a utility like watch to refresh a separate terminal window which is running kubectl get every one or two seconds.

brew install watch
watch -n 1 kubectl get functions,topics,pods,services,deploy

install Docker and create a Docker ID

Installing Docker Community Edition is the easiest way get started with docker. Visit to create a new Docker ID. You will push your function container to a repo under this ID, so use your Docker ID credentals to login.

docker login

new function using node.js

The steps below will create a JavaScript function from scratch. The same files are also available in the square sample on GitHub.

write the function

Create square.js in an empty directory.

module.exports = (x) => x ** 2


Create a new file called Dockerfile in the same directory. This container will be built on the node-function-invoker base image.

FROM projectriff/node-function-invoker:0.0.3
ENV FUNCTION_URI /functions/function.js
ADD square.js ${FUNCTION_URI}

Docker build

Use the docker CLI to build the function container image. Prefix the image name by replacing <your-Docker-ID> below with your own Docker ID. Note the . at the end of the docker build... command.

docker build -t <your-Docker-ID>/square:v0001 .

After performing the build push the image to your own Docker Hub repo.

docker push <your-Docker-ID>/square:v0001

function and topic resource definitions

Create a single square.yaml file for both resource definitions. Use the same image name and tag as the Docker build, replacing <your-Docker-ID> as before.

kind: Topic
  name: numbers

kind: Function
  name: square
  protocol: http
  input: numbers
    image: <your-Docker-ID>/square:v0001

apply the yaml to kubernetes

kubectl apply -f square.yaml

trigger the function

export GATEWAY=`kubectl get service -l component=http-gateway -o jsonpath='{.items[0].status.loadBalancer.ingress[0].ip}'`
export HEADER="Content-Type: text/plain"
curl $GATEWAY/requests/numbers -H "$HEADER" -w "\n" -d 10

If 10 is the input to the square function, the response should be 100.