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Zeebe on Kubernetes Getting Started Guide
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Zeebe on Kubernetes

This repository contains the links to get an example application with Zeebe running inside a Kubernetes Cluster. This example also includes an example Workflow Definition and links to a Zeebe Worker based on Spring Boot. This example also includes the use of the Zeebe Modeler and the zbctl command line tool.

Zeebe on K8s

Pre Requisites

  • Git / Java / Maven
  • Kubernetes Cluster + kubectl
  • HELM cli
  • (Optional) Zeebe Modeler
  • (Optional) Zeebe CTL
  • (Optional) Spring Boot Zeebe Worker

You can run this example against any Kubernetes Cluster.

You can also find a Spring Boot Worker which implements the classify, hospital and firefighters workers for the BPMN Service Tasks included in the example process here Zeebe Spring Boot Example Worker

Install Zeebe Helm Charts into your Kubernetes Cluster

Follow the official documentation on how to install the official Zeebe Helm Charts into Kubernetes.

Zeebe Modeler

If you are in Mac OSX you can install it with homebrew:

> brew cask install zeebe-modeler

Or download from here: Zeebe Modeler Releases

You can open and modify the emergency-process.bpmn file with it now.

Checking Zeebe Installation

> kubectl get pods

Should return something like:

NAME                                                   READY   STATUS    RESTARTS   AGE
elasticsearch-master-0                                 1/1     Running   0          10m
elasticsearch-master-1                                 1/1     Running   0          10m
elasticsearch-master-2                                 1/1     Running   0          10m
<RELEASE NAME>-nginx-ingress-controller-5cf6dd7894-s9xkr      1/1     Running   0          10m
<RELEASE NAME>-nginx-ingress-default-backend-f5454db5-8jgpq   1/1     Running   0          10m
<RELEASE NAME>-operate-5d4867d6d-qxqq5                        1/1     Running   2          10m
<RELEASE NAME>-zeebe-0                                        1/1     Running   0          10m
<RELEASE NAME>-zeebe-1                                        1/1     Running   0          10m
<RELEASE NAME>-zeebe-2                                        1/1     Running   0          10m

Interact with the services inside the Cluster

In order to interact with the services inside the cluster you need to use port-forward to route traffic from your environment to the cluster.

> kubectl port-forward svc/<RELEASE NAME>-zeebe 26500:26500

Now you can connect and execute operations against your newly created Zeebe cluster. Notice that you need to keep running the port-forward command to be able to communicate with the remote cluster.

Using the Zeebe CLI - Command Line Interface (zbctl)

You can get the zbctl tool from the official Zeebe Release Page

zbctl by default is configured to point to localhost:26500 to interact with a cluster, and because we are running port-forward from our environment to the cluster, our 26500 port is redirected to the cluster service.

Download and add zbctl to your PATH, and now you can check the connection with your cluster:

> zbctl status --insecure

This should return something like this:

Cluster size: 3
Partitions count: 3
Replication factor: 3
  Broker 0 - salaboy-zeebe-0.salaboy-zeebe.default.svc.cluster.local:26501
    Partition 1 : Follower
    Partition 2 : Leader
    Partition 3 : Follower
  Broker 1 - salaboy-zeebe-1.salaboy-zeebe.default.svc.cluster.local:26501
    Partition 1 : Leader
    Partition 2 : Follower
    Partition 3 : Leader
  Broker 2 - salaboy-zeebe-2.salaboy-zeebe.default.svc.cluster.local:26501
    Partition 1 : Follower
    Partition 2 : Follower
    Partition 3 : Follower

Once you have your connection to your cluster you can deploy our process defintion by running:

> zbctl deploy emergency-process.bpmn --insecure

Next step is to create Workflow Instances. Notice that you can send variables:

> zbctl create instance EMERGENCY_PROCESS --variables "{\"emergencyReason\" : \"person\"}" --insecure


> zbctl create instance EMERGENCY_PROCESS --variables "{\"emergencyReason\" : \"building on fire\"}" --insecure

Accessing Operate from outside the cluster

The Zeebe Full HELM Charts install an Ingress Controller. If this is deployed in a cloud provider, it should provision a LoadBalancer which will expose an External IP that can be used as the main entry point to access all the services/applications that are configured to have Ingress Routes.

You can find the External IP by running:

> kubectl get svc

You should see something like:

NAME                                    TYPE           CLUSTER-IP       EXTERNAL-IP   PORT(S)                                  AGE
<RELEASE NAME>-nginx-ingress-controller        LoadBalancer     <pending>     80:30497/TCP,443:32232/TCP               63m

Where the <pending> under the EXTERNAL-IP column should change to a public IP that you (and other users) should be able to access from outside the Cluster. You might need to check your Cloud Provider specific configuration if that doesn't work.

If you are running in Kubernetes KIND, you will need to port-forward to the Ingress Controller main entry point due KIND doesn't support LoadBalancers. You can do that by running in a different terminal:

> kubectl port-forward svc/<RELEASE NAME>-nginx-ingress-controller 8080:80

Then you should be able to access Operate at http://localhost:8080

Using demo/demo for credentials.

At this point, if you create two process instances you will see that they are both stuck at the Classify Emergency task. This is because you don't have workers for such tasks, so the process will wait in that state until we provide one of these workers.

Starting a simple Spring Boot Zeebe Worker

Clone and run the Simple Zeebe Spring Boot Worker:

> git clone
> cd  zeebe-worker-spring-boot-example/
> mvn spring-boot:run

Once again, the worker is configured by default to connect to localhost:26500 to fetch Jobs. If everything is up and running the worker will start and connect, automatically completing the pending tasks in our Workflow Instances. If you refresh Operate (http://localhost:8080) you will find both Instances completed:

Completed Instances

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