Use Hazelcast with OpenFaaS

Use Hazelcast clients in OpenFaaS functions to connect to Hazelcast clusters on Kubernetes.

What You Will Learn

With the popularity of Function as a Service (FaaS) rising, Kubernetes was also brought into it. OpenFaaS is one of the projects that allows you to deploy serverless functions onto Kubernetes.

Serverless functions are designed to be stateless, however this slows down the functions for some use cases, generally connection set-up time holds a considerable portion of the response time. OpenFaaS with the use of of-watchdog, partially solves this problem by allowing functions to be able to hold their states between calls. This approach helps Hazelcast because now the clients in the functions can persist their connection with the cluster between function calls, thus allowing faster response times.

In the tutorial, we will deploy OpenFaaS on Kubernetes. We will also create a Hazelcast cluster and deploy OpenFaaS functions with Hazelcast clients in them. We will use Java, Python and Nodejs clients and we will compare the response times of functions created with of-watchdog and Classical Watchdog.

Before you Begin

Step 1. Install and Configure OpenFaaS on Kubernetes

In this tutorial, we are going to use Minikube as the Kubernetes environment.

We are going to install OpenFaaS on Minikube using Helm CLI. We start by adding two namespaces openfaas and openfaas-fn. If you want to use different namespaces edit the following file used in the command below.

kubectl apply -f https://raw.githubusercontent.com/openfaas/faas-netes/master/namespaces.yml

Now, add OpenFaaS to the Helm chart.

helm repo add openfaas https://openfaas.github.io/faas-netes/

You can expose the OpenFaaS gateway with different resources. Update the helm upgrade command with your choice .

  • NodePort, (default) pass no additional flags

  • LoadBalancer, add --set serviceType=LoadBalancer

  • IngressController, add --set ingress.enabled=true

When NodePort is used you can access the gateway by using kubectl port-forward. In this tutorial, we are going to use NodePort.

Now deploy OpenFaaS onto Kubernetes.

helm repo update \
&& helm upgrade openfaas --install openfaas/openfaas \
--namespace openfaas  \
--set functionNamespace=openfaas-fn \
--set generateBasicAuth=true

Run the following command to see OpenFaaS is deployed.

$ kubectl get pods -n openfaas
NAME                                READY   STATUS    RESTARTS   AGE
alertmanager-6b5857bbd4-fbkrk       1/1     Running   0          17m
basic-auth-plugin-b9cd7fb66-whmbh   1/1     Running   0          17m
gateway-78cbb75d4c-hkqch            2/2     Running   0          17m
nats-6b6564d858-j7l8w               1/1     Running   0          17m
prometheus-6f699b4d87-jshv8         1/1     Running   0          17m
queue-worker-5f6cb648db-hgwgq       1/1     Running   0          17m

Log into OpenFaaS

Wait for gateway to be ready.

kubectl rollout status -n openfaas deploy/gateway

Run the following command to create a tunnel between Kubernetes cluster and your local computer. You may run this in a seperate terminal.

kubectl port-forward svc/gateway -n openfaas 8080:8080

Now, we can access the gateway from http://127.0.0.1:8080.

If you’re using a managed cloud Kubernetes service then get the LoadBalancer’s IP address or DNS entry from the EXTERNAL-IP field from the command below.

kubectl get svc -o wide gateway-external -n openfaas

Your URL will be the IP or DNS entry above on port 8080.

You can log in to Gateway with following commands.

export OPENFAAS_URL="http://127.0.0.1:8080" # Change if you are using a managed cloud Kubernetes service.

# This command retrieves your password
PASSWORD=$(kubectl get secret -n openfaas basic-auth -o jsonpath="{.data.basic-auth-password}" | base64 --decode; echo)

# This command logs in and saves a file to ~/.openfaas/config.yml
echo -n $PASSWORD | faas-cli login --username admin --password-stdin

You can also see and call your functions from a browser. Go to your $OPENFAAS_URL and provide username and password as admin and $PASSWORD.

Deploy Hazelcast Cluster on Kubernetes

The functions we deploy with OpenFaaS will have Hazelcast clients in them. So we will need a Hazelcast cluster on the same Kubernetes cluster. We will deploy the Hazelcast cluster using Helm. The following code snippet will deploy the Hazelcast Helm chart on whatever namespace you run it.

helm repo add hazelcast https://hazelcast-charts.s3.amazonaws.com/
helm repo update
helm install hz-hazelcast hazelcast/hazelcast

Step 2. Create a Function with the Hazelcast Client

OpenFaaS CLI provides function templates for different runtime environments and watchdogs. We are going to implement the functions in Java, Python and NodeJs. We will be using both of-watchdog and Classic Watchdog. By using of-watchdog we will preserve the database connections, so our clients will not need to connect to the cluster after each function call. You can find more information on watchdogs here.

Clone the repository from templates:ROOT:page$/[here] and cd into the repository

  • Java

  • Python

  • Nodejs

We will use the function under hz-client-java/of-watchdog. cd into hz-client-java/of-watchdog. You need to change image part in hz-client-java-ofwatchdog.yml to your Docker Hub username.

If you are not using a local Kubernetes cluster, you will also need to change the gateway section in hz-client-java-ofwatchdog.yml with the value of OPENFAAS_URL environment variable you created before.
If you deployed your Hazelcast cluster in a namespace other than default do not forget to change the default in config.getNetworkConfig().addAddress to your namespace in the file `hz-client-java-ofwatchdog/src/…​/Handler.java'.

After the change you can build, push and deploy your functions using the following command.

faas-cli up -f hz-client-java-ofwatchdog.yml

We will use the function under hz-client-python/of-watchdog. cd into hz-client-python/of-watchdog. You need to change image part in hz-client-python-ofwatchdog.yml to your Docker Hub username

If you are not using a local Kubernetes cluster, you will also need to change the gateway section in hz-client-python-ofwatchdog.yml with the value of OPENFAAS_URL environment variable you created before.
If you deployed your Hazelcast cluster in a namespace other than default do not forget to change the default in cluster_members to your namespace in the file 'hz-client-python-ofwatchdog/handler.py'.

After the change you can build, push and deploy your functions by the following command.

faas template pull https://github.com/openfaas-incubator/python-flask-template #Needed for building the image from template
faas-cli up -f  hz-client-python-ofwatchdog.yml  --build-arg "TEST_ENABLED=false"

We will use the function under hz-client-node/of-watchdog. cd into hz-client-node/of-watchdog. You need to change image part in hz-client-node-ofwatchdog.yml to your Docker Hub username.

If you are not using a local Kubernetes cluster, you will also need to change the gateway section in hz-client-node-ofwatchdog.yml with the value of OPENFAAS_URL environment variable you created before.
If you deployed your Hazelcast cluster in a namespace other than default do not forget to change the default in clusterMembers to your namespace in the file 'hz-client-node-ofwatchdog/handler.js'.

After the change you can build, push and deploy your functions by the following command.

faas-cli up -f hz-client-node-ofwatchdog.yml

Step 3. Trigger the Functions

Every deployed function will have http triggers at <gateway_address>/function/<function-name>.

After deploying the functions using faas-cli up or faas-cli deploy, you may choose invoke them by using curl, faas-cli invoke or the browser. We are going to use hey project to invoke the functions.

  • Java

  • Python

  • Nodejs

You can call the function with the following command.

hey -n 100 -c 4 ${OPENFAAS_URL}/function/hz-client-java-ofwatchdog

This will invoke the function 100 times using 4 concurrent workers.

You can call the function with the following command.

hey -n 100 -c 4 ${OPENFAAS_URL}/function/hz-client-python-ofwatchdog

This will invoke the function 100 times using 4 concurrent workers.

You can call the function with the following command.

hey -n 100 -c 4 ${OPENFAAS_URL}/function/hz-client-node-ofwatchdog

This will invoke the function 100 times using 4 concurrent workers.

The watchdogs used in these functions allowed us to use the same Hazelcast Client connecting to the cluster. We can also see the difference in time by deploying the same functions with the Classic Watchdog.

Java does not have templates with Classical Watchdog. So the next section will only available for Python and Nodejs.

  • Python

  • Nodejs

Change the image section in hz-client-python/classic-watchdog/hz-client-python-classic.yml.

If you are not using a local Kubernetes cluster, you will also need to change the gateway section in hz-client-python-classic.yml with the value of OPENFAAS_URL environment variable you created before.
If you deployed your Hazelcast cluster in a namespace other than default do not forget to change the default in cluster_members to your namespace in the file 'hz-client-python-classic/handler.py'.

Now, you can deploy the function with the following command.

faas-cli up -f hz-client-python-classic.yml

We are going to call the functions as follows:

hey -n 100 -c 4 ${OPENFAAS_URL}/function/hz-client-python-classic

This will invoke the function 100 times using 4 concurrent workers.

Change the image section in hz-client-node/classic-watchdog/hz-client-node-classic.yml.

If you are not using a local Kubernetes cluster, you will also need to change the gateway section in hz-client-node-ofwatchdog.yml with the value of OPENFAAS_URL environment variable you created before.
If you deployed your Hazelcast cluster in a namespace other than default do not forget to change the default in clusterMembers to your namespace in the file 'hz-client-node-classic/handler.js'.

Now, you can deploy the function with the following command.

faas-cli up -f hz-client-node-classic.yml

We are going to call the functions as follows:

hey -n 100 -c 4 ${OPENFAAS_URL}/function/hz-client-node-classic

This will invoke the function 100 times using 4 concurrent workers.

Comparing the two deployed versions for of-watchdog and Classic Watchdog, you should see dramatic results between response times.Because of-watchdog allows clients to persist their connection, it will be considerably faster.

Summary

In this tutorial we deployed OpenFaaS on Kubernetes then we created a Hazelcast cluster for our Hazelcast clients in functions. We first used of-watchdog as the watchdog for our functions. After seeing the results of of-watchdog, we deployed our functions with Classic Watchdog. Comparing these two we stated using of-watchdog with Hazelcast clients is by far the better option.

See Also