Deploy Confluent for Kubernetes¶
The Confluent for Kubernetes (CFK) bundle contains Helm charts, templates, and scripts for deploying Confluent Platform to your Kubernetes cluster.
You can deploy CFK using one of the following methods:
You can install the optional Confluent plugin for interacting with CFK using one of the following methods:
Deploy CFK from Confluent’s Helm repo¶
Add a Helm repo:
helm repo add confluentinc https://packages.confluent.io/helm
helm repo update
Install CFK using the default configuration:
helm upgrade --install confluent-operator \ confluentinc/confluent-for-kubernetes \ --namespace <namespace>
Deploy CFK using the download bundle¶
Download the CFK bundle using the following command, and unpack the downloaded bundle:
curl -O https://packages.confluent.io/bundle/cfk/confluent-for-kubernetes-2.7.5.tar.gz
From the
helm
sub-directory of where you downloaded the CFK bundle, install CFK:helm upgrade --install confluent-operator \ ./confluent-for-kubernetes \ --namespace <namespace>
Deploy customized CFK¶
You can customize the configuration of CFK when you install or update it. Using Helm, you can:
- Set configuration values in a YAML file which you pass to
helm
commands via the--values
or-f
flag. - Set configuration values as
key=value
pairs directly in yourhelm
commands via the--set
,--set-string
, and--set-file
flags. - Combine the above two approaches, where you may set some configuration in a
values file and others on the command line with the
--set
flags.
Refer to Helm documentation for more details on the Helm flags.
- To deploy customized Confluent for Kubernetes using the CFK
values.yaml
file: Find the default
values.yaml
file:If you are using Helm repo to deploy CFK, pull the CFK Chart:
mkdir -p <CFK-home> helm pull confluentinc/confluent-for-kubernetes \ --untar \ --untardir=<CFK-home> \ --namespace <namespace>
The
values.yaml
file is in the<CFK-home>/confluent-for-kubernetes
directory.If you are using a download bundle to deploy CFK, the
values.yaml
file is in thehelm/confluent-for-kubernetes
directory under where you downloaded the bundle.
Create a copy of the
values.yaml
file to customize CFK configuration. Do not edit the defaultvalues.yaml
file. Save your copy to any file location; we will refer to this location as<path-to-values-file>
.Install CFK using the customized configuration:
helm upgrade --install confluent-operator \ confluentinc/confluent-for-kubernetes \ --values <path-to-values-file> \ --namespace <namespace>
- To deploy customized Confluent for Kubernetes with the
helm upgrade
command: Specify the configuration options using the
--set
flag:helm upgrade --install confluent-operator \ confluentinc/confluent-for-kubernetes \ --set <setting1>=<value1> \ --set <setting2>=<value2> \ ... --namespace <namespace>
Configure CFK to manage Confluent Platform components across all namespaces¶
By default, CFK deploys Confluent Platform in the namespaced deployment, and it manages Confluent Platform
component clusters and resources in the same Kubernetes namespace where CFK
itself is deployed. To enable CFK to manage Confluent Platform resources across all
namespaces in the cluster mode, set the namespaced
configuration property to
false
in the install command:
helm upgrade --install confluent-operator \
confluentinc/confluent-for-kubernetes \
--set namespaced=false \
--namespace <namespace>
Alternatively, you can update the values.yaml
file as described above, and set the following property:
namespaced: false
Configure CFK to manage Confluent Platform components in different namespaces¶
In a namespaced deployment (namespaced: true
), CFK, by default, only
watches the same Kubernetes namespace that it is deployed in.
To enable CFK to manage Confluent Platform resources deployed in different namespaces, specify a list of namespaces for CFK to watch. The list must contain the namespaces of CFK as well as the Confluent Platform components.
You can specify the namespaces in the install command. For example:
helm upgrade --install confluent-operator \
confluentinc/confluent-for-kubernetes \
--set namespaceList="{confluent-namespace,cfk-namespace}" \
--namespace cfk-namespace \
--set namespaced=true
Alternatively, you can update the values.yaml
file as described above, and set the following property:
namespaceList: [confluent-namespace,cfk-namespace]
Deploy CFK after separately installing CRDs¶
By default, when you deploy CFK via helm
, the helm
command also installs the
Confluent Platform custom resource definitions (CRDs). However, as the user responsible for
deploying CFK, you may not have the permission to install those CRDs, so your
helm
installation would fail.
The responsibility for installing CRDs may only belong to your Kubernetes cluster administrator. In this situation, your Kubernetes cluster admin must have already installed the required Confluent CRDs in advance as described in Strict permissions and restricted namespace access.
To instruct helm
to skip trying to install the CRDs, add --skip-crds
to
the install command:
helm upgrade --install confluent-operator \
confluentinc/confluent-for-kubernetes \
--skip-crds \
--namespace <namespace>
Deploy CFK without creating roles and role bindings¶
By default, when you deploy CFK via helm
, the helm
command also creates the
Kubernetes role and role binding (or cluster role and cluster role binding)
needed for CFK to function at the same time. However, as the user responsible
for deploying CFK, you may not have the ability to manage Kubernetes RBAC
permissions, so your helm
installation would fail. The responsibility for
managing Kubernetes RBAC permissions may only belong to your Kubernetes cluster
administrator. In this situation, your Kubernetes cluster admin must have
already created the requisite RBAC resources in advance (see Prepare Kubernetes Cluster for Confluent Platform and Confluent for Kubernetes).
To instruct helm
to skip trying to create RBAC resources again, add --set
rbac=false
to the install command:
helm upgrade --install confluent-operator \
confluentinc/confluent-for-kubernetes \
--set rbac=false \
--namespace <namespace>
Alternatively, you can update the values.yaml
file as described above, and
set the following property:
rbac: false
Deploy CFK with custom service account¶
To provide a custom service account to manange CFK, add --set
serviceAccount.create=false --set serviceAccount.name=<name>
to the install command:
helm upgrade --install confluent-operator \
confluentinc/confluent-for-kubernetes \
--set serviceAccount.create=false \
--set serviceAccount.name=<service-account-name> \
--namespace <namespace>
Alternatively, you can update the values.yaml
file as described above, and
set the following property:
serviceAccount:
create: false
name: <service-account-name>
Note that if you use a custom service account and set rbac=false
, meaning
that the roles and role bindings were pre-created by your Kubernetes cluster admin,
then you must ensure that your <service-account-name>>
matches the subject
name in the pre-created role binding.
Deploy CFK with KRaft¶
To install KRaft controller in a Confluent Platform cluster, you need additional Kubernetes
ClusterRoles. Deploy CFK with the –-set kRaftEnabled=true
flag in the
helm upgrade
command so that CFK can create the required ClusterRole and
ClusterRolebinding for KRaft controllers.
For example:
helm upgrade --install confluent-operator \
confluentinc/confluent-for-kubernetes \
--set kRaftEnabled=true \
--namespace <namespace>
If ClusterRole and ClusterRolebindings are created out-of-band, it should have the following rule to get, list, patch, and update PersistentVolumes to deploy KRaft controllers:
kind: ClusterRole
rules:
- apiGroups:
- ""
resources:
- persistentvolumes
verbs:
- get
- list
- watch
- create
- update
- patch
- delete
Deploy CFK with cluster object deletion protection¶
Confluent for Kubernetes (CFK) provides validating admission webhooks for deletion events of the Confluent Platform clusters.
CFK webhooks are disabled by default in this release of CFK.
CFK provides the following webhooks:
Webhook to prevent component deletion when its persistent volume (PV) reclaim policy is set to Delete
This webhook blocks deletion requests on CRs with PVs in
ReclaimPolicy: Delete
. Without this prevention, a CR deletion will result in the deletion of those PVs and data loss.This webhook only applies to the components that have persistent volumes, namely, ZooKeeper, Kafka, ksqlDB, and Control Center.
Webhook to prevent CFK StatefulSet deletion
The proper way to delete Confluent Platform resources is to delete the component custom resource (CR) as CFK watches those deletion events and properly cleans everything up. Deletion of StatefulSets can result in unintended PV deletion and data loss.
This webhook blocks delete requests on CFK StatefulSets.
Webhook to prevent unsafe Kafka pod deletion
This webhook blocks Kafka pod deletion when the removal of a broker will result in fewer in-sync replicas than configured in the
min.insync.replicas
Kafka property. Dropping below that value can result in data loss. Pod deletion can happen during Kubernetes maintenance without warning, such as during node replacement, and this webhook is an additional safeguard for your Kafka data.Review the following when using this webhook:
This webhook is only supported on clusters with fewer than 140,000 partitions.
This webhook does not take the Kafka setting, minimum in-sync replicas (
min.insync.replicas
), into consideration.The minimum in-sync replicas setting on all topics is assumed to be
2
for Kafka with 3 or more replicas. Do not create topics with minimum in-sync replicas set to 1.To avoid having an internal ksqlDB topic with min in-sync replicas set to 1, set the ksqlDB internal topic replicas setting to
3
usingconfigOverrides
in the ksqlDB CR:spec: configOverrides: server: - ksql.internal.topic.replicas=3
Requirements¶
TLS certificates¶
Before you deploy CFK with webhooks enabled, you must provide TLS certificates to be used for secure communication between the webhook server and the Kubernetes API server:
Create signed TLS keys and certificates in the format as described in Provide TLS keys and certificates in PEM format. Provide the TLS Group 1 (
ca.pem
,server.pem
,server-key.pem
) or Group 3 (tls.crt
,tls.key
,ca.crt
) certificates.The certificate must have the Subject Alternative Name (SAN) of the form,
confluent-operator.<namespace>.svc
, which is the cluster-internal DNS name for the service in the namespace the CFK pod is getting deployed into.Provide the above certificates to the CFK pod using one of the following:
- Add the certificates to a Kubernetes secret and put them in the namespace that the CFK pod is getting deployed in.
- Add the certificates in Vault. All certificates must be in the same directory.
Kubernetes metadata label¶
If on the Kubernetes version lower than 1.21, before you deploy CFK with
webhooks enabled, add the kubernetes.io/metadata.name
label on all
namespaces where the webhooks should validate requests on.
This label is automatically set in Kubernetes 1.21 or later. For reference, see Automatic labeling.
Check labels on the namespace Confluent Platform is getting deployed in:
kubectl get namespace <namespace> --show-labels
An example output:
NAME STATUS AGE LABELS operator Active 48d <none>
Set the
kubernetes.io/metadata.name
label to the name of the namespace itself:kubectl label namespace <namespace> kubernetes.io/metadata.name=<namespace>
Validate.
kubectl get namespace <namespace> --show-labels
Following is an sample output:
NAME STATUS AGE LABELS operator Active 48d kubernetes.io/metadata.name=operator
Enable webhooks¶
Use the Helm value to enable or disable the validating webhooks.
Update the values.yaml
file as described above, and
set the following properties:
webhooks:
enabled: true --- [1]
tls: --- [2]
secretRef:
directoryPathInContainer:
- [1] Required to enable CFK webhooks.
- [2] Specify
secretRef
ordirectoryPathInContainer
value that you created in TLS certificates.
When enabling the webhook to prevent unsafe Kafka pod deletion for clusters with
100,000 or more partitions, increase the memory limit in values.,yaml
:
resources:
limits:
memory: 1024Mi
Enable the webhook for RBAC-enabled Kafka¶
After you deploy CFK with the Kafka deletion webhook enabled, if you are deploying an RBAC-enabled Kafka, you may need to give the RBAC user read access to all Kafka topics if that user is not a super user.
In the Kafka custom resource (CR), if the user configured in
spec.dependencies.kafkaRest.authentication.bearer.secretRef
is not included
in the spec.authorization.superUsers
list, create a rolebinding CR for that
user as in the below example:
apiVersion: platform.confluent.io/v1beta1
kind: ConfluentRolebinding
metadata:
name: clusterread
namespace: confluent
spec:
principal:
type: user
name: <principal>
role: DeveloperRead
resourcePatterns:
- resourceType: Topic
name: '*'
kafkaRestClassRef:
name: primary
Disable webhooks¶
After you deploy CFK with webhooks enabled, you can disable CFK webhooks at the namespace or component level by applying the following labels for a namespace or for a component CR.
Disable all CFK validation webhooks:
confluent-operator.webhooks.platform.confluent.io/disable: "true"
Disable the webhook that validates StatefulSet deletion:
confluent-operator.webhooks.platform.confluent.io/allow-statefulset-deletion: "true"
This label is only applied at the CR level.
Disable the webhook that validates CR deletion for PV reclaim policy:
confluent-operator.webhooks.platform.confluent.io/allow-pv-deletion: "true"
For example, to allow Kafka CR deletion when PVs are in the
Delete
mode, apply the following label:kubectl -n operator label kafka kafka \ confluent-operator.webhooks.platform.confluent.io/allow-pv-deletion="true"
Disable the webhook that validates Kafka pod deletion:
confluent-operator.webhooks.platform.confluent.io/allow-kafka-pod-deletion: "true"
Confluent plugin¶
The Confluent for Kubernetes (CFK) bundle contains a Confluent plugin for interacting with Confluent for Kubernetes. It is supported for three environments: Linux, Windows, and Darwin. See Confluent plugin for more information about the tool.
Install Confluent plugin¶
If you deployed CFK using the Helm repo, download and unpack the CFK bundle as described in the first step in Deploy CFK using the download bundle.
If you deployed CFK using the download bundle, skip this step.
If you are upgrading from an older version of the Confluent plugin, delete the old plugin from the directory where you previously installed it.
From the directory where you deployed CFK, unpack the
kubectl
plugin that matches your client environment, Linux, Windows or Mac OS (Darwin), into your client environment local executables directory. On Mac OS and Linux, this would be/usr/local/bin/
. This will allow the standard CLIkubectl
to find the plugin.tar -xvf kubectl-plugin/kubectl-confluent-<environment>-amd64.tar.gz \ -C <local directory for the plugin>
For example, on Mac OS:
tar -xvf kubectl-plugin/kubectl-confluent-darwin-amd64.tar.gz \ -C /usr/local/bin/
Install Confluent plugin using Krew¶
Krew is the plugin manager for kubectl
. Take the following steps if you want
to use Krew to install the Confluent plugin.
Install Krew as described in Krew User Guide.
If you deployed CFK using the Helm repo, download and unpack the CFK bundle as described in the first step in Deploy CFK using the download bundle.
If you used Deploy CFK using the download bundle, skip this step.
Go to the
kubectl-plugin
sub-directory under the directory where you unpacked the CFK bundle.If you are upgrading from an older version of the Confluent plugin, delete the old plugin:
kubectl krew uninstall confluent
Install the Confluent plugin using the following command:
kubectl krew install \ --manifest=confluent-platform.yaml \ --archive=kubectl-confluent-<environment>-amd64.tar.gz
For example, to install the plugin on MacOS:
kubectl krew install \ --manifest=confluent-platform.yaml \ --archive=kubectl-confluent-darwin-amd64.tar.gz