You can use the Helm charts to deploy services on Kubernetes for development, test, and proof of concept environments.

Open Source Helm charts are not supported by Confluent.

If you want to use Confluent Platform on Kubernetes in a test or production environment, follow these instructions to install Confluent Operator.

The Confluent Platform Helm Charts enable you to deploy Confluent Platform components on Kubernetes for development, test, and proof of concept environments.

Installation

Installing helm chart
helm repo add confluentinc https://confluentinc.github.io/cp-helm-charts/   (1)
helm repo update    (2)
helm install confluentinc/cp-helm-charts --name my-confluent --version 0.6.0    (3)
1 Add confluentinc helm charts repo
2 Update repo information
3 Install Confluent Platform with release name «my-confluent» and version 0.6.0

Contributing

We welcome any contributions:

It’s not officially supported repo, hence support is on "best effort" basis.

  • Report all enhancements, bugs, and tasks as GitHub issues

  • Provide fixes or enhancements by opening pull requests in GitHub

Documentation

Helm is an open-source packaging tool that helps you install applications and services on Kubernetes. Helm uses a packaging format called charts. Charts are a collection of YAML templates that describe a related set of Kubernetes resources.

This repository provides Helm charts for the following Confluent Platform services:

  • ZooKeeper

  • Kafka brokers

  • Kafka Connect

  • Confluent Schema Registry

  • Confluent REST Proxy

  • ksqlDB

  • Confluent Control Center

Environment Preparation

You must have a Kubernetes cluster that has Helm configured.

Tested Software

These Helm charts have been tested with the following software versions:

This guide assumes that you’re Helm 2 (tested with Helm 2.16). You can follow up on Helm 3 issues in https://github.com/confluentinc/cp-helm-charts/issues/480

For local Kubernetes installation with Minikube, see Install Minikube and Drivers.

Install Helm on Kubernetes

Follow the directions to install and deploy Helm to the Kubernetes cluster.

View a list of all deployed releases in the local installation.

helm init
helm repo update
helm list
For Helm versions prior to 2.9.1, you may see "connect: connection refused", and will need to fix up the deployment before proceeding. 
kubectl delete --namespace kube-system svc tiller-deploy
kubectl delete --namespace kube-system deploy tiller-deploy
kubectl create serviceaccount --namespace kube-system tiller
kubectl create clusterrolebinding tiller-cluster-rule --clusterrole=cluster-admin --serviceaccount=kube-system:tiller
kubectl patch deploy --namespace kube-system tiller-deploy -p '{"spec":{"template":{"spec":{"serviceAccount":"tiller"}}}}'
helm init --service-account tiller --upgrade

Persistence

The ZooKeeper and Kafka cluster deployed with StatefulSets that have a volumeClaimTemplate which provides the persistent volume for each replica. You can define the size of the volumes by changing dataDirSize and dataLogDirSize under cp-zookeeper and size under cp-kafka in values.yaml.

You also could use the cloud provider’s volumes by specifying StorageClass. For example, if you are on AWS your storage class will look like this:

apiVersion: storage.k8s.io/v1beta1
kind: StorageClass
metadata:
  name: ssd
provisioner: kubernetes.io/aws-ebs
parameters:
  type: gp2
To adapt this example to your needs, read the Kubernetes StorageClass documentation.

The StorageClass that was created can be specified in dataLogDirStorageClass and dataDirStorageClass under cp-zookeeper and in storageClass+ under cp-kafka in values.yaml.

To deploy non-persistent Kafka and ZooKeeper clusters, you must change the value of persistence.enabled under cp-kafka and cp-zookeeper in values.yaml

These type of clusters are suitable for strictly development and testing purposes. The StatefulSets+ are going to use emptyDir volumes, this means that its content strictly related to the pod life cycle and is deleted when the pod goes down.

Install Confluent Platform Charts

Clone the Confluent Helm Chart repo

> helm repo add confluentinc https://confluentinc.github.io/cp-helm-charts/
"confluentinc" has been added to your repositories

> helm repo update
Hang tight while we grab the latest from your chart repositories...
...Skip local chart repository
...Successfully got an update from the "confluentinc" chart repository
...Successfully got an update from the "stable" chart repository
Update Complete. ⎈ Happy Helming!⎈

Install a 3 node Zookeeper ensemble, a Kafka cluster of 3 brokers, 1 Confluent Schema Registry instance, 1 REST Proxy instance, and 1 Kafka Connect worker, 1 ksqlDB server in your Kubernetes environment.

Naming the chart --name my-confluent-oss is optional, but we assume this is the name in the remainder of the documentation. Otherwise, helm will generate release name. 
helm install confluentinc/cp-helm-charts --name my-confluent-oss

If you want to install without the Confluent Schema Registry instance, the REST Proxy instance, and the Kafka Connect worker:

helm install --set cp-schema-registry.enabled=false,cp-kafka-rest.enabled=false,cp-kafka-connect.enabled=false confluentinc/cp-helm-charts

View the installed Helm releases:

helm list
NAME                REVISION    UPDATED                     STATUS      CHART                   NAMESPACE
my-confluent-oss    1           Tue Jun 12 16:56:39 2018    DEPLOYED    cp-helm-charts-0.1.0    default

Verify Installation

Using Helm

This step is optional
Run the embedded test pod in each sub-chart to verify installation
helm test my-confluent-oss

Verify Kafka cluster

This step is optional - to verify that Kafka is working as expected, connect to one of the Kafka pods and produce some messages to a Kafka topic.
List your pods and wait until they are all in Running state.
kubectl get pods
Connect to the container cp-kafka-broker in a Kafka broker pod to produce messages to a Kafka topic.

If you specified a different release name, substitute my-confluent-oss with whatever you named your release.

kubectl exec -c cp-kafka-broker -it my-confluent-oss-cp-kafka-0 -- /bin/bash /usr/bin/kafka-console-producer --broker-list localhost:9092 --topic test

Wait for a > prompt, and enter some text.

m1
m2

Press Ctrl+C to close the producer session.

  1. Consume the messages from the same Kafka topic as above.

kubectl exec -c cp-kafka-broker -it my-confluent-oss-cp-kafka-0 -- /bin/bash  /usr/bin/kafka-console-consumer --bootstrap-server localhost:9092 --topic test --from-beginning

You should see the messages which were published from the console producer. Press Ctrl+C to stop consuming.

Manual Test

Zookeepers
git clone https://github.com/confluentinc/cp-helm-charts.git        (1)
kubectl apply -f cp-helm-charts/examples/zookeeper-client.yaml      (2)
...
kubectl exec -it zookeeper-client -- /bin/bash zookeeper-shell <zookeeper service>:<port> ls /brokers/ids       (3)
kubectl exec -it zookeeper-client -- /bin/bash zookeeper-shell <zookeeper service>:<port> get /brokers/ids/0
kubectl exec -it zookeeper-client -- /bin/bash zookeeper-shell <zookeeper service>:<port> ls /brokers/topics    (4)
1 Clone Helm Chars git repository
2 Deploy a client pod.
3 Connect to the client pod and use the zookeeper-shell command to explore brokers…​
4 topics, etc.
Kafka
Validate Kafka installation
kubectl apply -f cp-helm-charts/examples/kafka-client.yaml (1)
kubectl exec -it kafka-client -- /bin/bash      (2)
1 Deploy a Kafka client pod.
2 Log into the Pod
From within the kafka-client pod, explore with kafka commands:
## Setup
export RELEASE_NAME=<release name>
export ZOOKEEPERS=${RELEASE_NAME}-cp-zookeeper:2181
export KAFKAS=${RELEASE_NAME}-cp-kafka-headless:9092

## Create Topic
kafka-topics --zookeeper $ZOOKEEPERS --create --topic test-rep-one --partitions 6 --replication-factor 1

## Producer
kafka-run-class org.apache.kafka.tools.ProducerPerformance --print-metrics --topic test-rep-one --num-records 6000000 --throughput 100000 --record-size 100 --producer-props bootstrap.servers=$KAFKAS buffer.memory=67108864 batch.size=8196

## Consumer
kafka-consumer-perf-test --broker-list $KAFKAS --messages 6000000 --threads 1 --topic test-rep-one --print-metrics

Run A Streams Application

ksqlDB is the streaming SQL engine that enables real-time data processing against Apache Kafka. Now that you have running in your Kubernetes cluster, you may run a ksqlDB example.

Operations

Scaling Zookeeper

All scaling operations should be done offline with no producer or consumer connection. The number of nodes should always be odd number.

Install cp-helm-charts with default 3 node ensemble

helm install cp-helm-charts

Scale nodes up to 5, change servers under cp-zookeeper to 5 in values.yaml

helm upgrade <release name> cp-helm-charts

Scale nodes down to 3, change servers under cp-zookeeper to 3 in values.yaml

helm upgrade <release name> cp-helm-charts

Scaling Kafka

Scaling Kafka brokers without doing Partition Reassignment will cause data loss. You must reassign partitions correctly before scaling the Kafka cluster.
Install cp-helm-charts with default 3 brokers kafka cluster
helm install cp-helm-charts

Scale kafka brokers up to 5, change brokers+ under cp-kafka to 5 in values.yaml

helm upgrade <release name> cp-helm-charts

Scale kafka brokers down to 3, change brokers under cp-kafka to 3 in values.yaml

helm upgrade <release name> cp-helm-charts

Monitoring

JMX Metrics are enabled by default for all components, Prometheus JMX Exporter is installed as a sidecar container along with all Pods.

  1. Install Prometheus and Grafana in same Kubernetes cluster using helm

    helm install stable/prometheus
helm install stable/grafana

  2. Add Prometheus as Data Source in Grafana, url should be something like: http://illmannered-marmot-prometheus-server:9090

  3. Import dashboard under grafana-dashboard into Grafana Kafka Dashboard ZooKeeper Dashboard

Teardown

To remove the pods, list the pods with kubectl get pods and then delete the pods by name.

kubectl get pods
kubectl delete pod <podname>

To delete the Helm release, find the Helm release name with helm list and delete it with helm delete. You may also need to clean up leftover StatefulSets, since helm delete can leave them behind. Finally, clean up all persisted volume claims (pvc) created by this release.

helm list
helm delete <release name>
kubectl delete statefulset <release name>-cp-kafka <release name>-cp-zookeeper
kubectl delete pvc --selector=release=<release name>

Appendix: Create a Local Kubernetes Cluster

There are many deployment options to get set up with a Kubernetes cluster, and this document provides instructions for using Minikube to set up a local Kubernetes cluster. Minikube runs a single-node Kubernetes cluster inside a VM on your laptop.

You may alternatively set up a Kubernetes cluster in the cloud using other providers such as Google Kubernetes Engine (GKE).

Install Minikube and Drivers

Minikube version 0.23.0 or higher is required for docker server https://github.com/moby/moby/pull/31352%5B17.05], which adds support for using ARG in FROM in your Dockerfile.

First follow the basic Minikube installation instructions.

Then install the Minikube drivers. Minikube uses Docker Machine to manage the Kubernetes VM so it benefits from the driver plugin architecture that Docker Machine uses to provide a consistent way to manage various VM providers. Minikube embeds VirtualBox and VMware Fusion drivers so there are no additional steps to use them. However, other drivers require an extra binary to be present in the host PATH.

If you are running on macOS, in particular make sure to install the hyperkit drivers for the native OS X hypervisor: 
brew install hyperkit
minikube config set driver hyperkit     (1)
1 Use hyperkit drivel by default

Start Minikube

The following command increases the memory to 6096 MB and uses the hyperkit driver for the native macOS Hypervisor.

  1. Start Minikube. The following command increases the memory to 6096 MB and uses the xhyve driver for the native macOS Hypervisor.

    minikube start --kubernetes-version v1.9.4 --cpus 4 --memory 6096 --vm-driver=xhyve --v=8

  2. Continue to check status of your local Kubernetes cluster until both minikube and cluster are in Running state

    ❯ minikube status
m01
host: Running
kubelet: Running
apiserver: Running
kubeconfig: Configured

  3. Work around Minikube issue #1568.

    minikube ssh -- sudo ip link set docker0 promisc on

  4. Set the context.

    eval $(minikube docker-env)

kubectl config set-context minikube.internal --cluster=minikube --user=minikube
Context "minikube.internal" modified.

kubectl config use-context minikube.internal
Switched to context "minikube.internal".

Verify Minikube Local Kubernetes Environment

kubectl config current-context
minikube.internal

kubectl cluster-info
Kubernetes master is running at https://192.168.99.106:8443
KubeDNS is running at https://192.168.99.106:8443/api/v1/namespaces/kube-system/services/kube-dns:dns/proxy

Thanks

Huge thanks to: