= Confluent Platform Helm Charts [Deprecated] :icons: font :toc: auto :toc-placement: macro :toc-position: auto :toc-title: Table of content :toclevels: 3 :idprefix: :idseparator: - :sectanchors: :icons: font :source-highlighter: rouge :experimental:

Deprecated: The cp-helm-charts is deprecated in favor of Confluent For Kubernetes .

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

CAUTION: 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 https://docs.confluent.io/current/installation/operator/index.html#operator-about-intro[Confluent Operator].

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The https://github.com/confluentinc/cp-helm-charts[Confluent Platform Helm Charts] enable you to deploy Confluent Platform components on Kubernetes for development, test, and proof of concept environments.

== Installation

[source,bash] .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: NOTE: It's not officially supported repo, hence support is on __"best effort"__ basis. * Report all enhancements, bugs, and tasks as https://github.com/confluentinc/cp-helm-charts/issues[GitHub issues] * Provide fixes or enhancements by opening pull requests in GitHub == Documentation https://helm.sh/[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: * https://kubernetes.io/[Kubernetes] 1.9.2+ * https://helm.sh/[Helm] 2.8.2+ * https://hub.docker.com/u/confluentinc/[Confluent Platform Docker Images] WARNING: 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 Helm on Kubernetes Follow the directions to https://docs.helm.sh/using_helm/#quickstart-guide[install and deploy Helm] to the Kubernetes cluster. View a list of all deployed releases in the local installation. [source,sh] ---- helm init helm repo update helm list ---- IMPORTANT: For Helm versions prior to 2.9.1, you may see `"connect: connection refused"`, and will need to fix up the deployment before proceeding. [source,sh] ---- 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 https://github.com/confluentinc/cp-helm-charts/blob/master/values.yaml[values.yaml]. You also could use the cloud provider's volumes by specifying https://kubernetes.io/docs/concepts/storage/storage-classes/[StorageClass]. For example, if you are on AWS your storage class will look like this: [source,yaml] ---- apiVersion: storage.k8s.io/v1beta1 kind: StorageClass metadata: name: ssd provisioner: kubernetes.io/aws-ebs parameters: type: gp2 ---- NOTE: To adapt this example to your needs, read the Kubernetes https://kubernetes.io/docs/concepts/storage/storage-classes/#parameters[StorageClass] documentation. The `StorageClass` that was created can be specified in `dataLogDirStorageClass` and `dataDirStorageClass` under `cp-zookeeper` and in `storageClass+` under `cp-kafka` in https://github.com/confluentinc/cp-helm-charts/blob/master/values.yaml[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 https://github.com/confluentinc/cp-helm-charts/blob/master/values.yaml[values.yaml] WARNING: 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 [source,sh] ---- > 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. NOTE: 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. [source,sh] ---- 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: [source,sh] ---- 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: [source,sh] ---- 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 NOTE: _This step is optional_ [source,sh] .Run the embedded test pod in each sub-chart to verify installation ---- helm test my-confluent-oss ---- ==== Verify Kafka cluster NOTE: _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. [source,sh] .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. [source,sh] ---- 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 kbd:[Ctrl + C] to close the producer session. . Consume the messages from the same Kafka topic as above. [source,sh] ---- 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 kbd:[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 : ls /brokers/ids #<3> kubectl exec -it zookeeper-client -- /bin/bash zookeeper-shell : get /brokers/ids/0 kubectl exec -it zookeeper-client -- /bin/bash zookeeper-shell : 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 [source,bash] .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 [source,bash] .From within the kafka-client pod, explore with kafka commands: ---- ## Setup export 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 https://github.com/confluentinc/cp-helm-charts/blob/master/examples/ksql-demo.yaml[ksqlDB example]. === Operations ==== Scaling Zookeeper TIP: 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 cp-helm-charts ---- Scale nodes down to 3, change `servers` under `cp-zookeeper` to 3 in `values.yaml` ---- helm upgrade cp-helm-charts ---- ==== Scaling Kafka IMPORTANT: Scaling Kafka brokers without doing Partition Reassignment will cause data loss. You must reassign partitions correctly before https://kafka.apache.org/documentation/#basic_ops_cluster_expansion[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 cp-helm-charts ---- Scale kafka brokers down to 3, change `+brokers+` under `+cp-kafka+` to 3 in values.yaml ---- helm upgrade 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. . Install Prometheus and Grafana in same Kubernetes cluster using helm + [source,bash] ---- helm install stable/prometheus helm install stable/grafana ---- . Add Prometheus as Data Source in Grafana, url should be something like: `+http://illmannered-marmot-prometheus-server:9090+` . Import dashboard under https://github.com/confluentinc/cp-helm-charts/blob/master/grafana-dashboard/confluent-open-source-grafana-dashboard.json[grafana-dashboard] into Grafana image:screenshots/kafka.png[Kafka Dashboard] image:screenshots/zookeeper.png[ZooKeeper Dashboard] === Teardown To remove the pods, list the pods with `kubectl get pods` and then delete the pods by name. [source,sh] ---- kubectl get pods kubectl delete pod ---- 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. [source,sh] ---- helm list helm delete kubectl delete statefulset -cp-kafka -cp-zookeeper kubectl delete pvc --selector=release= ---- == 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 https://kubernetes.io/docs/setup/minikube/[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 https://cloud.google.com/kubernetes-engine/docs/quickstart[Google Kubernetes Engine (GKE)]. [[create-local-minikube]] === 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 https://github.com/kubernetes/minikube[Minikube installation instructions]. Then install the https://github.com/kubernetes/minikube/blob/master/docs/drivers.md[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`. [IMPORTANT] If you are running on macOS, in particular make sure to install the `hyperkit` drivers for the native OS X hypervisor: ==== [source,sh] ---- brew install hyperkit minikube config set driver hyperkit #<1> ---- <1> Use hyperkit drivel by default ==== === Start Minikube TIP: The following command increases the memory to 6096 MB and uses the `hyperkit` driver for the native macOS Hypervisor. . Start Minikube. The following command increases the memory to 6096 MB and uses the `+xhyve+` driver for the native macOS Hypervisor. + [source,sh] ---- minikube start --kubernetes-version v1.9.4 --cpus 4 --memory 6096 --vm-driver=xhyve --v=8 ---- . Continue to check status of your local Kubernetes cluster until both minikube and cluster are in Running state + [source,sh] ---- ❯ minikube status m01 host: Running kubelet: Running apiserver: Running kubeconfig: Configured ---- . Work around Minikube https://github.com/kubernetes/minikube/issues/1568[issue #1568]. + [source,sh] ---- minikube ssh -- sudo ip link set docker0 promisc on ---- . Set the context. + [source,sh] ---- 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: * https://github.com/kubernetes/charts/tree/master/incubator/kafka[Kafka helm chart] * https://github.com/kubernetes/charts/tree/master/incubator/zookeeper[ZooKeeper helm chart] * https://github.com/kubernetes/charts/tree/master/incubator/schema-registry[Schema Registry helm chart] * https://github.com/Yolean/kubernetes-kafka[kubernetes-kafka] * https://github.com/solsson/dockerfiles[docker-kafka]