Configure Confluent Role Based Access Control (RBAC) with Confluent for Kubernetes¶
Confluent for Kubernetes (CFK) supports Role-Based Access Control (RBAC). RBAC is powered by Confluent’s Metadata Service (MDS), which integrates with an LDAP server and acts as the central authority for authorization and authentication data. RBAC leverages role bindings to determine which users and groups can access specific resources and what actions the users can perform on those resources.
Confluent provides audit logs, that record the runtime decisions of the permission checks that occur as users/applications attempt to take actions that are protected by ACLs and RBAC.
There are a set of principals and role bindings required for the Confluent components to function, and those are automatically generated when CFK is deployed.
Note
RBAC with CFK can be enabled only for new installations. You cannot upgrade an existing cluster and enable it with RBAC.
When you deploy Confluent Platform with RBAC enabled, CFK automates the security setup. Here’s the end state architecture:
Based on the components and features you use, you need to configure the following additional role bindings:
- Grant role to Kafka user to access Schema Registry
- Grant roles to a Confluent Control Center user to administer Confluent Platform
Requirements¶
The following are the requirements for enabling and using RBAC with CFK:
You must have an LDAP server that Confluent Platform can use for authentication.
Currently, CFK only supports the
GROUPS
LDAP search mode. The search mode indicates if the user-to-group mapping is retrieved by searching for group or user entries. If you need to use theUSERS
search mode, specify using theconfigOverrides
setting in the Kafka CR as below:spec: configOverrides: server: - ldap.search.mode=USERS
See Sample Configuration for User-Based Search for more information.
Confluent REST service is automatically enabled for RBAC and cannot be disabled when RBAC is enabled.
Use the Kafka bootstrap endpoint (same as the MDS endpoint) to access Confluent REST API.
You must create the user principals in LDAP that will be used by Confluent Platform components. These are the default user principals:
- Kafka:
kafka
/kafka-secret
- Confluent REST API:
erp
/erp-secret
- Confluent Control Center:
c3
/c3-secret
- ksqlDB:
ksql
/ksql-secret
- Schema Registry:
sr
/sr-secret
- Replicator:
replicator
/replicator-secret
- Connect:
connect
/connect-secret
- Kafka:
Create the LDAP user/password for a user who has a minimum of LDAP read-only permissions to allow Metadata Service (MDS) to query LDAP about other users. For example, you’d create a user
mds
with passwordDeveloper!
Create a user for the Admin REST service in LDAP and provide the username and password.
Configure RBAC with CFK¶
The comprehensive security tutorial walks you through an end-to-end setup of role-based access control (RBAC) for Confluent with CFK. We recommend you take the CustomResource spec and the steps outlined in the scenario as a starting point and customize for your environment.
Enable RBAC for Kafka¶
To configure and deploy Kafka with the Confluent RBAC:
Specify the settings in your Kafka Custom Resource (CR):
kind: Kafka spec: authorization: type: rbac --- [1] superUsers: --- [2] services: mds: --- [3] tokenKeyPair: --- [4] secretRef: directoryPathInContainer: provider: type: ldap --- [5] ldap: --- [6] address: ldap://ldap.confluent.svc.cluster.local:389 authentication: type: simple simple: secretRef: credential configurations: groupNameAttribute: cn groupObjectClass: group groupMemberAttribute: member groupMemberAttributePattern: CN=(.*),DC=test,DC=com groupSearchBase: dc=test,dc=com userNameAttribute: cn userMemberOfAttributePattern: CN=(.*),DC=test,DC=com userObjectClass: organizationalRole userSearchBase: dc=test,dc=com dependencies: kafkaRest: --- [7] authentication: type: bearer --- [8] bearer: secretRef: --- [9] directoryPathInContainer: --- [10]
[1] Required.
[2] Required. The super users to be given the admin privilege on the Kafka cluster.
These users have no access to resources in other Confluent Platform clusters unless they also configured with specific role bindings on the clusters.
This list is in the
User:<user-name>
format. For example:superUsers: - "User:kafka" - "User:testadmin"
[3] Required.
[4] Required. The token key pair to authenticate to the MDS. Use
secretRef
ordirectoryPathInContainer
to specify.You need to add the public key and the token key pair to the secret or directoryPathInContainer. For details, see Create a PEM key pair for MDS.
An example command to create a secret is:
kubectl create secret generic mds-token \ --from-file=mdsPublicKey.pem=mds-publickey.txt \ --from-file=mdsTokenKeyPair.pem=mds-tokenkeypair.txt \ --namespace confluent
[5] Required.
[6] Required. A few examples properties are given under [6].
[7] Required. The REST client configuration for the MDS when RBAC is enabled.
[8] Required.
[9] or [10] Required.
When RBAC is enabled (
spec.authorization.type: rbac
), CFK always uses the Bearer authentication for Confluent components, ignoring thespec.authentication
setting. It is not possible to set the component authentication type to mTLS when RBAC is enabled.[9] The username and password are loaded through secretRef.
The expected key is
bearer.txt
.The value for the key is:
username=<username> password=<password>
[10] Provide the path where required credentials are injected by Vault. See [9] for the expected key and the value.
Configure the Admin REST Class CR.
You need to use the
bearer
authentication for the Admin Rest Class as shown below.For the rest of the configuration details for the Admin REST Class, see Manage Confluent Admin REST Class.
kind: KafkaRestClass metadata: name: --- [1] namespace: spec: kafkaRest: authentication: type: bearer --- [2] bearer: secretRef: --- [3] directoryPathInContainer: --- [4]
[1] Optional. If not specified,
default
is used as the name of this REST class.[2] Required for RBAC.
[3] or [4] Required.
[3] The username and password are loaded through secretRef.
The expected key is
bearer.txt
.The value for the key is:
username=<username> password=<password>
[4] Provide the path where required credentials are injected by Vault. See [2] for the expected key and the value.
When RBAC is enabled (
spec.authorization.type: rbac
), CFK always uses the Bearer authentication for Confluent components, ignoring thespec.authentication
setting. It is not possible to set the component authentication type to mTLS when RBAC is enabled.
Enable RBAC for other Confluent Platform components¶
To configure and deploy other non-Kafka components with the Confluent RBAC:
Specify the settings in the component CR:
spec: authorization: type: rbac --- [1] kafkaRestClassRef: --- [2] name: default dependencies: mds: endpoint: --- [3] tokenKeyPair: --- [4] secretRef: directoryPathInContainer authentication: type: bearer --- [5] bearer: secretRef: --- [6] directoryPathInContainer: --- [7]
[1] Required for RBAC.
[2] If
kafkaRestClassRef
is not configured, the kafkaRestClass with the name,default
, in the current namespace is used.[3] Required. MDS endpoint.
[4] Required. The token key pair and the public key to authenticate to the MDS. Use
secretRef
ordirectoryPathInContainer
to specify.You need to add the public key and the token key pair to the secret or directoryPathInContainer. For details, see Create a PEM key pair for MDS.
An example command to create a secret is:
kubectl create secret generic mds-token \ --from-file=mdsPublicKey.pem=mds-publickey.txt \ --from-file=mdsTokenKeyPair.pem=mds-tokenkeypair.txt \ --namespace confluent
[5] Required.
[6] or [7] Required.
When RBAC is enabled (
spec.authorization.type: rbac
), CFK always uses the Bearer authentication for Confluent components, ignoring thespec.authentication
setting. It is not possible to set the component authentication type to mTLS when RBAC is enabled.[6] The username and password are loaded through secretRef.
The expected key is
bearer.txt
.The value for the key is:
username=<username> password=<password>
[7] Provide the path where required credentials are injected by Vault. See [2] for the expected key and the value.
Use an existing Admin REST Class or create a new Admin REST Class CR as described in the previous section.
Automated creation of role bindings for Confluent Platform component principals¶
CFK automatically creates all required role bindings for Confluent Platform components as ConfluentRoleBinding custom resources (CRs).
Review the role bindings created by CFK:
kubectl get confluentrolebinding
Grant role to Kafka user to access Schema Registry¶
Use the following ConfluentRolebinding CR to create the required role binding to access Schema Registry:
apiVersion: platform.confluent.io/v1beta1
kind: ConfluentRolebinding
metadata:
name: internal-schemaregistry-schema-validation
namespace: <namespace>
spec:
principal:
name: <user-id>
type: user
clustersScopeByIds:
schemaRegistryClusterId: <schema-registry-group-id>
kafkaClusterId: <kafka-cluster-id>
resourcePatterns:
name: "*"
patternType: LITERAL
resourceType: Subject
role: DeveloperRead
Grant roles to a Confluent Control Center user to administer Confluent Platform¶
Control Center users require separate roles for each Confluent Platform component and resource they wish to view and administer in the Control Center UI. Grant explicit permissions to the users as shown below.
In the following example, the testadmin
principal is used as a Control Center UI
user.
Grant permission to view and administer Confluent Platform components¶
The rolebinding CRs in the examples GitHub repo specifies the permissions needed in CFK. Create the rolebindings with the following command:
kubectl apply -f \
https://raw.githubusercontent.com/confluentinc/confluent-kubernetes-examples/master/security/production-secure-deploy/controlcenter-testadmin-rolebindings.yaml
Check the roles created:
kubectl get confluentrolebinding
Use custom authorizer¶
To use a custom authorizer, other than RBAC or ACL, use
Configuration overrides to set the authorizer.class.name
property.
For example, to configure Ranger authorization in the Kafka CR:
spec:
configOverrides:
server:
- authorizer.class.name=org.apache.ranger.authorization.kafka.authorizer.RangerKafkaAuthorizer
To configure the client-side security for the Kafka Admin REST API server when
using a custom authorizer, set kafka.spec.dependencies.kafkaRest
in the Kafka
CR.
For example, to configure Kafka REST client for Kafka mTLS authentication, set in the Kafka CR:
spec:
dependencies:
kafkaRest:
bootstrapEndpoint: <kafka_listener_dns>:<kafka_listener_port>
authentication:
type: mtls
tls:
enabled: true
Troubleshooting: Verify MDS configuration¶
Log into MDS to verify the correct configuration and to get the Kafka cluster ID. You need the Kafka cluster ID for component role bindings.
Replace https://<mds_endpoint>
in the below commands with the value you set
in the spec.dependencies.mds.endpoint
in the Kafka CR.
Log into MDS as the Kafka super user as below:
confluent login \ --url https://<mds_endpoint> \ --ca-cert-path <path-to-cacerts.pem>
You need to pass the
--ca-cert-path
flag if:- You have configured MDS to serve HTTPS traffic
(
kafka.spec.dependencies.mds.tls.enabled: true
). - The CA used to issue the MDS certificates is not trusted by system where you are running these commands.
Provide the Kafka username and password when prompted, in this example,
kafka
andkafka-secret
.You get a response to confirm a successful login.
- You have configured MDS to serve HTTPS traffic
(
Verify that the advertised listeners are correctly configured using the following command:
curl -ik \ -u '<kafka-user>:<kafka-user-password>' \ https://<mds_endpoint>/security/1.0/activenodes/https
Get the Kafka cluster ID using one of the following commands:
confluent cluster describe --url https://<mds_endpoint>
curl -ik \ https://<mds_endpoint>/v1/metadata/id