Apache Kafka® comes with basic OAuth2 support in the form of SASL based authentication module which provides client-server retrieval, exchange and validation of access token used as credentials. For real world usage, extensions have to be provided in the form of JAAS callback handlers which is what Strimzi Kafka OAuth does.
Strimzi Kafka OAuth modules provide support for OAuth2 as authentication mechanism when establishing a session with Kafka broker.
- OAuth2 for Authentication
- OAuth2 for Authorization
- Building
- Installing
- Configuring the authorization server
- Configuring the Kafka Broker
- Configuring the Kafka client with SASL/OAUTHBEARER
- Configuring the Kafka client with SASL/PLAIN
- Configuring the TLS truststore
- Configuring the network timeouts for communication with authorization server
- Configuring the metrics
- Demo
One of the advantages of OAuth2 compared to direct client-server authentication is that client credentials are never shared with the server. Rather, there exists a separate OAuth2 authorization server that application clients and application servers communicate with. This way user management, authentication, and authorization is 'outsourced' to a third party - authorization server.
User authentication is then an outside step which user manually performs to obtain an access token or a refresh token, which grants a limited set of permissions to a specific client app.
In the simplest case, the client application can authenticate in its own name using client credentials - client id and secret. While the client secret is in this case packaged with application client, the benefit is still that it is not shared with application server (Kafka broker in our case) - the client first performs authentication against OAuth2 authorization server in exchange for an access token, which it then sends to the application server instead of its secret. Access tokens can be independently tracked and revoked at will, and represent limited access to resources on application server.
In a more advanced case, user authenticates and authorizes the application client in exchange for a token. The client application is then packaged with only a long-lived access token or a long-lived refresh token. User's username and password are never packaged with application client. If access token is configured it is sent directly to Kafka broker during session initialisation. But if refresh token is configured, it is first used to ask authorization server for a new access token, which is then sent to Kafka broker to start a new authenticated session.
When using refresh tokens for authentication the retrieved access tokens can be relatively short-lived which puts a time limit on potential abuse of a leaked access token. Repeated exchanges with authorization server also provide centralised tracking of authentication attempts which is something that can be desired.
A developer authorizing the client application with access to Kafka resources will access authorization server directly, using a web based or CLI based tool to sign in and generate access token or refresh token for application client.
As hinted above, OAuth2 allows for different implementations, multiple layers of security, and it is up to the developer, taking existing security policies into account, on how exactly they would implement it in their applications.
Authentication is the procedure of establishing if the user is who they claim they are. Authorization is the procedure of deciding if the user is allowed to perform some action using some resource. Kafka brokers by default allow all users full access - there is no specific authorization policy in place. Kafka comes with an implementation of ACL based authorization mechanism where access rules are saved in ZooKeeper and replicated across brokers.
Authorization in Kafka is implemented completely separately and independently of authentication. Thus, it is possible to configure Kafka brokers to use OAuth2 based authentication, and at the same time the default ACL authorization.
Since version 0.3.0 Strimzi Kafka OAuth provides token-based authorization using Keycloak as authorization server, and taking advantage of Keycloak Authorization Services. See examples authorization README for a demonstration on how to install, and use KeycloakAuthorizer which implements this functionality.
mvn clean install
Copy the following jars into your Kafka libs directory:
oauth-common/target/kafka-oauth-common-*.jar
oauth-server/target/kafka-oauth-server-*.jar
oauth-server-plain/target/kafka-oauth-server-plain-*.jar
oauth-keycloak-authorizer/target/kafka-oauth-keycloak-authorizer-*.jar
oauth-client/target/kafka-oauth-client-*.jar
oauth-common/target/lib/nimbus-jose-jwt-*.jar
If you want to use custom claim checking, or json-path based principal extraction from JWT tokens, also copy the following:
oauth-server/target/lib/json-path-*.jar
oauth-server/target/lib/json-smart-*.jar
oauth-server/target/lib/accessors-smart-*.jar
At your authorization server, you need to configure a client for Kafka broker, and a client for each of your client applications.
Also, you may want each developer to have a user account in order to configure user based access controls.
Configuring users, clients, and authorizing clients, obtaining access tokens, and refresh tokens are steps that are specific to the authorization server that you use. Consult your authorization server's documentation.
If you use the KeycloakAuthorizer for authorization, then you have to use Keycloak or Keycloak based authorization server to configure security policies and permissions for users and service accounts.
Kafka uses JAAS to bootstrap custom authentication mechanisms. Strimzi Kafka OAuth therefore needs to use JAAS configuration to activate SASL/OAUTHBEARER, and install its own implementations of the callback classes. This is true for configuring the server side of the Kafka Broker, as well as for the Kafka client side - when using OAuth 2 for inter-broker communication.
The authentication configuration specific to the Strimzi Kafka OAuth can be specified as part of JAAS configuration in the form of JAAS parameter values.
The authorization configuration for KeycloakAuthorizer is specified as server.properties key-value pairs.
Both authentication and authorization configuration specific to Strimzi Kafka OAuth can also be set as ENV vars, or as Java system properties.
The limitation here is that authentication configuration specified in this manner can not be listener-scoped.
Note: Strimzi Kafka OAuth can not be used for Kafka Broker to Zookeeper authentication. It only supports Kafka Client to Kafka Broker authentication (including inter-broker communication).
There are several steps to configuring the Kafka Broker:
In order to configure Strimzi Kafka OAuth for the listener, you first need to enable SASL security for the listener, and enable SASL/OAUTHBEARER mechanism.
For example, let's have two listeners, one for inter-broker communication (REPLICATION), and one for Kafka clients to connect (CLIENT):
listeners=REPLICATION://kafka:9991,CLIENT://kafka:9092
listener.security.protocol.map=REPLICATION:PLAINTEXT,CLIENT:SASL_PLAINTEXT
Here we have configured the REPLICATION listener to not use any authentication, and we have configured the CLIENT listener to use SASL authentication over insecure connection.
Note that these are examples, for production you should almost certainly not use PLAINTEXT, or SASL_PLAINTEXT.
Having these two listeners, the one called CLIENT fulfils the precondition for Strimzi Kafka OAuth in that it is configured to use SASL based authentication.
The next thing to do is to enable SASL/OAUTHBEARER mechanism:
sasl.enabled.mechanisms=OAUTHBEARER
Since version 0.7.0 there is also support for so called OAuth over PLAIN which allows using the SASL/PLAIN mechanism to authenticate with an OAuth access token or with a client ID and a secret.
In order to use OAuth over PLAIN you have to enable the SASL/PLAIN mechanism as well (you can enable one or the other or both):
sasl.enabled.mechanisms=OAUTHBEARER,PLAIN
In JAAS configuration we do four things:
- Activate a specific JAAS login module - for Strimzi Kafka OAuth that is either:
- the
org.apache.kafka.common.security.oauthbearer.OAuthBearerLoginModuleclass which implements Kafka's SASL/OAUTHBEARER authentication mechanism, or - the
org.apache.kafka.common.security.plain.PlainLoginModuleclass which implements Kafka's SASL/PLAIN authentication mechanism.
- the
- Activate the custom principal builder -
io.strimzi.kafka.oauth.server.OAuthKafkaPrincipalBuilder. - Activate the custom server callback that will provide server-side token validation:
- For
SASL/OAUTHBEARERthe callback class should beio.strimzi.kafka.oauth.server.JaasServerOauthValidatorCallbackHandler. - For
SASL/PLAINthe callback class should beio.strimzi.kafka.oauth.server.plain.JaasServerOauthOverPlainValidatorCallbackHandler.
- For
- Specify the configurations used by the login module, and by our custom extensions - the server callback handler and / or the login callback handler (which we will do in the next step).
JAAS configuration can be specified inside server.properties file using the listener-scoped sasl.jaas.config key.
Assuming there is the CLIENT listener configured as shown above, we can specify configuration specifically for that listener:
listener.name.client.oauthbearer.sasl.jaas.config=org.apache.kafka.common.security.oauthbearer.OAuthBearerLoginModule required \
oauth.jwks.endpoint.uri="https://server/keys" ;
Note the listener.name.client.oauthbearer. prefix for the key. The word client in the key refers to the CLIENT listener.
In this case we are configuring the validator with fast local signature check that uses the JWKS endpoint provided by authorization server.
The oauthbearer part refers to the sasl mechanism SASL/OAUTHBEARER on the CLIENT listener. In order to configure the SASL/PLAIN mechanism you have to use plain instead:
listener.name.client.plain.sasl.jaas.config=org.apache.kafka.common.security.plain.PlainLoginModule required \
oauth.jwks.endpoint.uri="https://server/keys" oauth.token.endpoint.uri="https://server/token";
Here we specified the oauth.token.endpoint.uri configuration key which is the additional option for SASL/PLAIN, and is not used by SASL/OAUTHBEARER. The other options are the same as for SASL/OAUTHBEARER.
Any Strimzi Kafka OAuth keys that begin with oauth. can be specified this way - scoped to the individual listener.
A value of the scoped sasl.jaas.config always starts with the JAAS login module name, followed by required, and then followed by zero or more configuration parameters, separated by a whitespace, and ended with a semicolon - ;
Inside server.properties this has to be a single line, or if multi-line, each non-final line has to be ended with a backslash \.
The custom callbacks are enabled per listener in server.properties using the listener-scoped configuration.
On the Kafka Broker we typically only install the custom server callback - the so called validator callback handler.
An example for SASL/OAUTHBEARER:
listener.name.client.oauthbearer.sasl.server.callback.handler.class=io.strimzi.kafka.oauth.server.JaasServerOauthValidatorCallbackHandler
An example for SASL/PLAIN:
listener.name.client.plain.sasl.server.callback.handler.class=io.strimzi.kafka.oauth.server.plain.JaasServerOauthOverPlainValidatorCallbackHandler
If the SASL/OAUTHBEARER listener is also used for inter-broker communication, then you also have to configure the client callback handler class.
listener.name.client.oauthbearer.sasl.login.callback.handler.class=io.strimzi.kafka.oauth.client.JaasClientOauthLoginCallbackHandler
If the listener is not used for inter-broker communication, then you don't have to configure the login callback, but in that case make sure to include the following parameter in listener's sasl.jaas.config:
unsecuredLoginStringClaim_sub="unused"
For example:
listener.name.client.oauthbearer.sasl.jaas.config=org.apache.kafka.common.security.oauthbearer.OAuthBearerLoginModule required \
oauth.jwks.endpoint.uri="https://server/keys" unsecuredLoginStringClaim_sub="unused";
This prevents an error during the execution of the default OAuthBearerLoginModule parameter validation logic.
OAuth authentication also requires a custom principal builder to be installed on the broker:
principal.builder.class=io.strimzi.kafka.oauth.server.OAuthKafkaPrincipalBuilder
Strimzi Kafka OAuth library uses properties that start with oauth.* to configure authentication, and properties that start with strimzi.* to configure authorization.
Authentication properties are best specified as JAAS config parameters as part of the value of listener-scoped sasl.jaas.config property in server.properties.
See Configuring the JAAS login module.
At this time the authentication properties (oauth.*) can't be specified as server.properties property keys - they will not have any effect.
They can be specified as ENV variables, or as Java system properties in which case they override any JAAS config parameter values.
For environment variables the oauth.* and strimzi.* property keys can be uppercased with . replaced by _.
For example, to specify oauth.client.id as the ENV var, you can use OAUTH_CLIENT_ID.
In terms of precedence the order of looking for a configuration is the following:
- System property
oauth.client.id - ENV var
OAUTH_CLIENT_ID - ENV var
oauth.client.id - JAAS config property
oauth.client.id
Whichever is found first is the one that is used.
Similarly, for authorization the strimzi.* properties follow a similar lookup mechanism except that they don't use JAAS config, but are specified as server.properties keys.
For example, the order of looking for configuration for strimzi.client.id would be the following:
- System property
strimzi.client.id - ENV var
STRIMZI_CLIENT_ID - ENV var
strimzi.client.id server.propertiespropertystrimzi.client.id
The most essential OAuth2 configuration on the Kafka broker is the configuration related to validation of the access tokens passed from Kafka clients to the Kafka broker during SASL based authentication mechanism.
There are two options for token validation:
- Using the JWKS endpoint in combination with signed JWT formatted access tokens
- Using the introspection endpoint
If your authorization server generates JWT tokens, and exposes the JWKS Endpoint then using JWKS endpoint is most efficient, since it does not require contacting the authorization server whenever a new Kafka client connects to the Kafka Broker.
Specify the following oauth.* properties:
oauth.jwks.endpoint.uri(e.g.: "https://localhost:8443/realms/demo/protocol/openid-connect/certs")oauth.valid.issuer.uri(e.g.: "https://localhost:8443/realms/demo" - only access tokens issued by this issuer will be accepted)
Some authorization servers don't provide the iss claim. In that case you would not set oauth.valid.issuer.uri, and you would explicitly turn off issuer checking by setting the following option to false:
oauth.check.issuer(e.g. "false")
You can enforce audience checking, which is an OAuth2 mechanism to prevent successful authentication with tokens unless they are explicitly issued for use by your resource server.
The authorization server adds the allowed resource servers' client IDs into the aud claim of such tokens.
Set the following option to true to enforce audience checking:
oauth.check.audience(e.g. "true")
When audience checking is enabled the oauth.client.id has to be configured:
oauth.client.id(e.g.: "kafka" - this is the OAuth2 client configuration id for the Kafka Broker)
If the configured oauth.client.id is kafka, the following are valid examples of aud attribute in the JWT token:
- "kafka"
- ["rest-api", "kafka"]
JWT tokens contain unique user identification in sub claim. However, this is often a long number or a UUID, but we usually prefer to use human-readable usernames, which may also be present in JWT token.
Use oauth.username.claim to map the claim (attribute) where the value you want to use as user id is stored:
oauth.username.claim(e.g.: "preferred_username", for nested attributes use[topAttrKey].[subAttrKey]. Claim names can also be single quoted:['topAttrKey'].['subAttrKey'])
If oauth.username.claim is specified the value of that claim is used instead, but if not set, the automatic fallback claim is the sub claim.
You can specify a prefix that is automatically prepended to the user id. This allows for the consistent mapping of user ids into the same name space and may be needed to prevent name collisions. One use case is to assign a different prefix for each server when using different authorization servers for different listeners:
oauth.username.prefix(e.g.: "internal_" - there is no prefix set by default)
You can specify the secondary claim to fall back to, which allows you to map multiple account types into the same principal namespace:
oauth.fallback.username.claim(e.g.: "client_id", for nested attributes use[topAttrKey].[subAttrKey]. Claim names can also be single quoted:['topAttrKey'].['subAttrKey'])oauth.fallback.username.prefix(e.g.: "client-account-")
If oauth.username.claim is specified but value does not exist in the token, then oauth.fallback.username.claim is used. If value for that doesn't exist either, the exception is thrown.
When oauth.fallback.username.prefix is specified and the claim specified by oauth.fallback.username.claim contains a non-null value the resulting user id will be equal to concatenation of the prefix, and the value.
For example, if the following configuration is set:
oauth.username.claim="username"
oauth.fallback.username.claim="client_id"
oauth.fallback.username.prefix="client-account-"
Then, if the token contains "username": "alice" claim then the principal will be User:alice.
Otherwise, if the token contains "client_id": "my-producer" claim then the principal will be User:client-account-my-producer.
If your authorization server uses ECDSA encryption you used to need to enable the BouncyCastle JCE crypto provider:
oauth.crypto.provider.bouncycastle(e.g.: "true")
Since version 0.8.0 this is no longer needed, and this configuration option is ignored, as well as the option:
oauth.crypto.provider.bouncycastle.position
Depending on your authorization server you may need to relax some checks:
oauth.check.access.token.type(e.g.: "false" - do not require"typ": "Bearer"in JWT token)
You can control how often the keys used for signature checks are refreshed and when they expire:
oauth.jwks.refresh.seconds(e.g.: "300" - that's the default value - keys are refreshed every 5 minutes)oauth.jwks.expiry.seconds(e.g.: "360" - that's the default value - keys expire 6 minutes after they are loaded)
If an access token signed with an unknown signing key is encountered, another refresh is scheduled immediately. You can control the minimum pause between two consecutive scheduled keys refreshes - the default is 1 second:
oauth.jwks.refresh.min.pause.seconds(e.g.: "0" - no minimum pause)
All access tokens can be invalidated by rotating the keys on authorization server and expiring old keys.
Some authorization servers don't specify the "use": "sig" attribute in validation keys in the JWKS endpoint response. By default, only the public keys with "use": "sig" are considered for signature validation. There is an option to ignore the use attribute, and consider all the keys for token signature validation:
oauth.jwks.ignore.key.use(e.g.: "true" - ignore theuseattribute on the keys in JWKS response)
During the Kafka broker startup, a request to the JWKS endpoint immediately tries to load the keys. If JWKS keys can not be loaded or can not be successfully parsed during startup, the Kafka broker will exit. That behaviour can be turned off:
oauth.fail.fast(e.g.: "false" - it is "true" by default)
When your authorization server is configured to use opaque tokens (not JWT) or if it does not expose JWKS endpoint, you have no other option but to use the introspection endpoint. This will result in Kafka Broker making a request to authorization server every time a new Kafka client connection is established.
Specify the following oauth.* properties:
oauth.introspection.endpoint.uri(e.g.: "https://localhost:8443/realms/demo/protocol/openid-connect/token/introspect")oauth.valid.issuer.uri(e.g.: "https://localhost:8443/realms/demo" - only access tokens issued by this issuer will be accepted)oauth.client.id(e.g.: "kafka" - this is the OAuth2 client configuration id for the Kafka broker)oauth.client.secret(e.g.: "kafka-secret")
Introspection endpoint should be protected. The oauth.client.id and oauth.client.secret specify Kafka Broker credentials for authenticating to access the introspection endpoint.
Some authorization servers don't provide the iss claim. In that case you would not set oauth.valid.issuer.uri, and you would explicitly turn off issuer checking by setting the following option to false:
oauth.check.issuer(e.g.: "false")
You can enforce audience checking, which is an OAuth2 mechanism to prevent successful authentication with tokens unless they are explicitly issued for use by your resource server.
The authorization server adds the allowed resource servers' client IDs into the aud claim of such tokens.
Set the following option to true to enforce audience checking:
oauth.check.audience(e.g. "true")
If the configured oauth.client.id is kafka, the following are valid examples of aud attribute in the JWT token:
- "kafka"
- ["rest-api", "kafka"]
By default, if the Introspection Endpoint response contains token_type claim, there is no checking performed on it.
Some authorization servers use a non-standard token_type value. To give the most flexibility, you can specify the valid token_type for your authorization server:
oauth.valid.token.type(e.g.: "access_token")
When this is specified the Introspection Endpoint response has to contain token_type, and its value has to be equal to the value specified by oauth.valid.token.type.
Introspection Endpoint may or may not return identifying information which we could use as user id to construct a principal for the user.
If the information is available we attempt to extract the user id from Introspection Endpoint response.
Use oauth.username.claim to map the attribute where the user id is stored:
oauth.username.claim(e.g.: "preferred_username", for nested attributes use[topAttrKey].[subAttrKey]. Claim names can also be single quoted:['topAttrKey'].['subAttrKey'])
You can fall back to a secondary attribute, which allows you to map multiple account types into the same user id namespace:
oauth.fallback.username.claim(e.g.: "client_id", for nested attributes use[topAttrKey].[subAttrKey]. Claim names can also be single quoted:['topAttrKey'].['subAttrKey'])oauth.fallback.username.prefix(e.g.: "client-account-")
If oauth.username.claim is specified but value does not exist in the Introspection Endpoint response, then oauth.fallback.username.claim is used. If value for that doesn't exist either, the exception is thrown.
When oauth.fallback.username.prefix is specified and the attribute specified by oauth.fallback.username.claim contains a non-null value the resulting user id will be equal to concatenation of the prefix, and the value.
If none of the oauth.*.username.* attributes is specified, sub claim will be used automatically.
For example, if the following configuration is set:
oauth.username.claim="username"
oauth.fallback.username.claim="client_id"
oauth.fallback.username.prefix="client-account-"
It means that if the response contains "username": "alice" then the principal will be User:alice.
Otherwise, if the response contains "client_id": "my-producer" then the principal will be User:client-account-my-producer.
Sometimes the Introspection Endpoint does not provide any useful identifying information that we can use for the user id. In that case you can configure User Info Endpoint:
oauth.userinfo.endpoint.uri(e.g.: "https://localhost:8443/realms/demo/protocol/openid-connect/userinfo")
If the user id could not be extracted from Introspection Endpoint response, then the same rules (oauth.username.claim, oauth.fallback.username.claim, oauth.fallback.username.prefix) will be used to try extract the user id from User Info Endpoint response.
When you have a DEBUG logging configured for the io.strimzi category you may need to specify the following to prevent warnings about access token not being JWT:
oauth.access.token.is.jwt(e.g.: "false")
Sometimes the network of the deployment environment may be glitchy resulting in intermittent connection problems. By default, a failed request to the Introspection Endpoint or the User Info Endpoint
will result in immediate failed validation and AuthenticationException returned to the Kafka client application. The following option enables reattempting the request to either endpoint.
The default value is '0', meaning 'no retries'. Provide the value greater than '0' to set the number of repeated attempts:
oauth.http.retries(e.g.: "1" - if initial request fails, retry one more time)
You may also specify a pause time between requests in order not to flood the authorization server. Keep in mind though that this is holding up a request processing thread in the Kafka broker, which may result in the pool of worker threads to become exhausted, and broker possibly unavailable even to the clients connecting to the listeners not configured with OAuth. The default value is '0', meaning 'no pause'. Provide the value greater than '0' to set the pause time between attempts in milliseconds:
oauth.http.retry.pause.millis(e.g.: "500" - if a retry is attempted, there will first be a half-a-second pause)
When using oauth.http.retries and oauth.http.retry.pause.millis options also keep in mind that the worker thread can
get blocked on unresponsive connection, and you will want to set oauth.connect.timeout.seconds and oauth.read.timeout.seconds
to smaller values as well, as explained in the chapter on timeouts.
You may want to place additional constraints on who can authenticate to your Kafka broker based on the content of JWT access token. There is a mechanism available that allows the use of JSONPath filter query which is the JWT access token or the introspection endpoint response is matched against. If the match fails, the authentication is denied.
oauth.custom.claim.check(e.g.: "'kafka-user' in @.roles")
For example, if the access token looks like the following:
{
"aud": ["uma_authorization", "kafka"],
"iss": "https://auth-server/token/",
"iat": 0,
"exp": 600,
"sub": "username",
"custom": "custom-value",
"roles": {
"client-roles": {
"kafka": ["kafka-user"]
}
},
"custom-level": 9,
"orgId": "org-001"
}
Here are some examples of valid queries that will pass the check:
@.orgId == 'org-001' && 'kafka-user' in @.roles.client-roles.kafka
@.custom-level > 7 && @.custom =~ /custom-.*/
@.orgId && !@.clientId
Note, that you should not use null in your queries, instead you should check if the attribute is non-empty.
For example:
- '@.orgId' is
trueif 'orgId' attribute is set to some non-empty value - '!@.clientId' is
trueif clientId attribute is missing or is set tonullor an empty string
See JsonPathFilterQuery JavaDoc for more information about the syntax.
When using custom authorization (by installing a custom authorizer) you may want to take user's group membership into account when making the authorization decisions.
One way is to obtain and inspect a parsed JWT token from io.strimzi.kafka.oauth.server.OAuthKafkaPrincipal object available through AuthorizableRequestContext passed to your authorize() method.
This gives you full access to token claims.
Another way is to configure group extraction at authentication time, and get groups as a set of group names from OAuthKafkaPrincipal object. If your custom authorizer only needs group information from the token, and that information is present in the token in the form where you can use a JSONPath query to extract it, then you may prefer to avoid extracting this information from the token yourself as part of each call to authorize() method, and rather use the one already extracted during authentication.
There are two configuration parameters for configuring group extraction:
oauth.groups.claim(e.g.:$.roles.client-roles.kafka)oauth.groups.claim.delimiter(a delimiter to parse the value of the groups claim when it's a single delimited string. E.g.:,- that's the default value)
Use oauth.groups.claim to specify a JSONPath query pointing to the claim containing an array of strings, or a delimited single string.
Use oauth.groups.claim.delimiter to specify a delimiter to use for parsing groups when they are specified as a delimited string.
By default, no group extraction is performed. When you configure oauth.groups.claim the group extraction is enabled and occurs during authentication.
The extracted groups are stored into OAuthKafkaPrincipal object. Here is an example how you can extract them in your custom authorizer:
public List<AuthorizationResult> authorize(AuthorizableRequestContext requestContext, List<Action> actions) {
KafkaPrincipal principal = requestContext.principal();
if (principal instanceof OAuthKafkaPrincipal) {
OAuthKafkaPrincipal p = (OAuthKafkaPrincipal) principal;
for (String group: p.getGroups()) {
System.out.println("Group: " + group);
}
}
}
See JsonPathQuery JavaDoc for more information about the syntax.
When configuring the listener for SASL/PLAIN using org.apache.kafka.common.security.plain.PlainLoginModule in its jaas.sasl.config (as explained previously), the oauth.* options are the same as when configuring the listener for SASL/OAUTHBEARER.
There is an additional oauth.* option you can specify (it's optional):
oauth.token.endpoint.uri(e.g.: "https://localhost:8443/realms/demo/protocol/openid-connect/token")
If this option is not specified the listener treats the username parameter of the SASL/PLAIN authentication as the account name, and the password parameter as the raw access token which is passed to the validation as if SASL/OAUTHBEARER was used.
However, if this option is specified, the listener, by default, performs client_credentials authentication to obtain the access token in the name of the connecting client. It treats the username and password parameters of SASL/PLAIN authentication as clientId and secret for client_credentials authentication, which the server performs against the authorization server to obtain an access token in client's name. In this mode the client can still authenticate with an access token directly, by specifying the account name as a username and specifying the raw access token prepended by a prefix $accessToken: as a password parameter of SASL/PLAIN authentication. In this case the raw access token will be extracted from the password parameter by removing the prefix, and passed directly for validation.
We can also say that by not configuring the oauth.token.endpoint.uri we disable client_credentials authentication over PLAIN.
When connecting to the token endpoint the listener's configuration options oauth.http.retries and oauth.http.retry.pause.millis will be used to control what to do if the request to the endpoint fails due to a network issue, a timeout, or unexpected response status.
It means that you can set these options on the listener that uses oauth.jwks.endpoint.uri as well as on one that uses oauth.introspection.endpoint.uri.
It is best to use mutual TLS for inter-broker communication. But if you really want to use oauth, there are a few details to get right.
In order to use OAuth for inter-broker connections you have to specify the following two settings:
sasl.mechanism.inter.broker.protocolinter.broker.listener.name
You need to configure the listener with SASL_PLAINTEXT (rather than PLAINTEXT) or SASL_SSL (rather than SSL). For proper security you should use SASL_SSL.
Then, you need to configure the sasl.jaas.config with client configuration options, not just the server configuration options.
All the Kafka brokers in the cluster should be configured with the same client ID and secret, and the corresponding user should be added to super.users since inter-broker client requires super-user permissions.
When you configure your listener to support OAuth, you can configure it to support OAUTHBEARER, but you can also configure it to support the OAuth over PLAIN as explained previously. PLAIN does not make much sense on the broker for inter-broker communication since OAUTHBEARER is supported. Therefore, it is best to only use OAUTHBEARER mechanism for inter-broker communication.
Specify the following oauth.* properties in sasl.jaas.config configuration:
oauth.token.endpoint.uri(e.g.: "https://localhost:8443/realms/demo/protocol/openid-connect/token")oauth.client.id(e.g.: "kafka" - this is the client configuration id for Kafka Broker)oauth.client.secret(e.g.: "kafka-secret")oauth.username.claim(e.g.: "preferred_username")
Also specify the principal corresponding to the client account identified by oauth.client.id in super.users property in server.properties file:
super.users(e.g.: "User:service-account-kafka")
This is not a full set of available oauth.* properties. All the oauth.* properties described in the next chapter about configuring the Kafka clients also apply to configuring the client side of inter-broker communication.
Here is an example of the configuration that uses OAUTHBEARER for inter-broker authentication:
# We could use only one listener, but it's customary to use a separate listener
# for interbroker communication
listener.security.protocol.map=REPLICATION:SASL_PLAINTEXT,EXTERNAL:SASL_PLAINTEXT
sasl.enabled.mechanisms=OAUTHBEARER,PLAIN
sasl.mechanism.inter.broker.protocol=OAUTHBEARER
inter.broker.listener.name=REPLICATION
# Because REPLICATION listener is used for inter-broker communication it also requires the 'client-side' login callback handler and corresponding configuration:
listener.name.replication.oauthbearer.sasl.jaas.config=org.apache.kafka.common.security.oauthbearer.OAuthBearerLoginModule required \
oauth.client.id="kafka" \
oauth.client.secret="kafka-secret" \
oauth.token.endpoint.uri="http://sso:8080/realms/demo/protocol/openid-connect/token" \
oauth.valid.issuer.uri="http://sso:8080/realms/demo" \
oauth.jwks.endpoint.uri="http://sso:8080/realms/demo/protocol/openid-connect/certs" \
oauth.username.claim="preferred_username" ;
# Server-side-authentication handler
listener.name.replication.oauthbearer.sasl.server.callback.handler.class=io.strimzi.kafka.oauth.server.JaasServerOauthValidatorCallbackHandler
# Login-as-a-client handler
listener.name.replication.oauthbearer.sasl.login.callback.handler.class=io.strimzi.kafka.oauth.client.JaasClientOauthLoginCallbackHandler
# The EXTERNAL listener only needs server-side-authentication support because we don't use it for inter-broker communication:
listener.name.external.oauthbearer.sasl.jaas.config=org.apache.kafka.common.security.oauthbearer.OAuthBearerLoginModule required \
oauth.valid.issuer.uri="http://sso:8080/realms/demo" \
oauth.jwks.endpoint.uri="http://sso:8080/realms/demo/protocol/openid-connect/certs" \
oauth.username.claim="preferred_username" \
unsecuredLoginStringClaim_sub="unused" ;
# The last parameter is needed for configuration to pass OAuthBearerLoginModule validation when we don't specify a custom sasl.login.callback.handler.class
# Server-side-authentication handler
listener.name.external.oauthbearer.sasl.server.callback.handler.class=io.strimzi.kafka.oauth.server.JaasServerOauthValidatorCallbackHandler
# On EXTERNAL listener we may also want to support OAuth over PLAIN
listener.name.external.plain.sasl.jaas.config=org.apache.kafka.common.security.plain.PlainLoginModule required \
oauth.token.endpoint.uri="http://sso:8080/realms/demo/protocol/openid-connect/token" \
oauth.valid.issuer.uri="http://sso:8080/realms/demo" \
oauth.jwks.endpoint.uri="http://sso:8080/realms/demo/protocol/openid-connect/certs" \
oauth.username.claim="preferred_username" \
unsecuredLoginStringClaim_sub="unused" ;
# Server-side-authentication handler
listener.name.external.plain.sasl.server.callback.handler.class=io.strimzi.kafka.oauth.server.plain.JaasServerOauthOverPlainValidatorCallbackHandler
This is without authorizer configuration.
Access tokens expire after some time. The token validation for the purpose of session authentication is only performed immediately after the new connection from the client is established. If using SimpleACLAuthorizer or no authorizer at all, then there is no further need for the access token after the authentication, and by default the expiry of the token will not result in session closure or denial of access within the existing session.
Since Kafka version 2.2 the Kafka brokers support a re-authentication mechanism allowing clients to update the token mid-session, without having to drop and re-establish the connection. When a client sends the new access token, validation is performed on the broker as if a new connection was established.
The re-authentication mechanism only makes sense for token based authentication mechanisms. Also, because it introduces additional message type to Kafka protocol it has to be explicitly enabled in order to not potentially break the older Kafka clients.
In order to enable the re-authentication on the Kafka broker, use the connections.max.reauth.ms property in server.properties:
connections.max.reauth.ms=3600000
In this example the maximum time until next re-authentication is set to one hour. If the access token expires sooner than that, the re-authentication will be triggered sooner.
The option can be specified per-listener. For example if you have a listener called CLIENTS, you can specify:
listener.name.clients.oauthbearer.connections.max.reauth.ms=3600000
If re-authentication is enabled, the session timeout is enforced as the expiry time of the access token. By using re-authentication the multiple 'lightweight' sessions can follow one another over the same network connection for as long as the connection isn't closed or interrupted due to processes restarting or due to network issues.
If for some reason you can't enable re-authentication or don't want to use it, and if you want to invalidate the session when access token expires, but aren't using KeycloakAuthorizer, which does this automatically (since version 0.6.0 of this library), you can use the OAuthSessionAuthorizer to enforce token expiry mid-session.
OAuthSessionAuthorizer works by checking the access token expiry on every operation performed, and denies all access after the token has expired.
As long as the token has not yet expired (it may have been recently invalidated at authorization server but the Kafka broker may not yet know about it) the authorization is delegated to the delegate authorizer.
If you want to install OAuthSessionAuthorizer wrapped around Simple ACL Authorizer install it as follows in server.properties:
authorizer.class.name=io.strimzi.kafka.oauth.server.OAuthSessionAuthorizer
strimzi.authorizer.delegate.class.name=kafka.security.auth.SimpleAclAuthorizer
You configure the SimpleAclAuthorizer by specifying the same properties as if it was installed under authorizer.class.name.
It's the same for any other authorizer you may use - instead of using authorizer.class.name you install it by using strimzi.authorizer.delegate.class.name.
Do not use OAuthSessionAuthorizer together with KeycloakAuthorizer as that would be redundant.
If you don't use any authorizer at all, and don't use re-authentication, but still want to enforce access token expiry mid-session, don't specify the strimzi.authorizer.delegate.class.name at all.
Instead, specify the following configuration:
strimzi.authorizer.grant.when.no.delegate=true
In this case, unless the access token has expired, all the actions will be granted. The broker will behave as if no authorizer was installed, effectively turning every user into a 'superuser'. The unauthenticated users, or users authenticated with a mechanism other than OAuth will also automatically have all the actions granted.
Note: When using SASL/PLAIN authentication in combination with KeycloakAuthorizer or OAuthSessionAuthorizer the Kafka client session will expire when the access token expires.
This will result in sudden appearance of the authorization failures.
Since there is no way to pass a new access token mid-session (re-authenticate), the client will have to start a new session by establishing a new connection.
Strimzi Kafka OAuth provides support to centrally manage not only users and clients, but also permissions to Kafka broker resources - topics, consumer groups, configurations ...
Support for this works specifically with Keycloak Authorization Services.
By default, authorization is not enabled on Kafka Broker. There is kafka.security.authorizer.AclAuthorizer that comes with Kafka out-of-the-box and works with Zookeeper, and org.apache.kafka.metadata.authorizer.StandardAuthorizer that works in KRaft mode.
They behave the same and handle the standard Kafka ACL based permissions as documented in Kafka Documentation.
Strimzi Kafka OAuth provides an alternative authorizer - io.strimzi.kafka.oauth.server.authorizer.KeycloakAuthorizer.
KeycloakAuthorizer uses the access token and the Token Endpoint of the same Keycloak realm used for OAuth2 authentication as a source of permission grants for the authenticated session.
Note: In Kafka versions prior to 3.3.x io.strimzi.kafka.oauth.server.authorizer.KeycloakRBACAuthorizer class should be used for the authorizer. For latest versions of Kafka the KeycloakAuthorizer which supports both KRaft mode and Zookeeper mode should be used.
The KeycloakAuthorizer detects the runtime environment, and delegates to ACLAuthorizer when in Zookeeper mode, and to StandardAuthorizer when in KRaft mode (as detected based on the presence of process.roles config property).
Add the following to server.properties file:
authorizer.class.name=io.strimzi.kafka.oauth.server.authorizer.KeycloakAuthorizer
You also need a properly configured OAuth authentication support, as described in Configuring the Kafka broker authentication.
All the configuration properties for KeycloakAuthorizer begin with a strimzi.authorization. prefix.
The token endpoint used by KeycloakAuthorizer has to be the same as the one used for OAuth authentication:
strimzi.authorization.token.endpoint.uri(e.g.: "https://localhost:8443/realms/demo/protocol/openid-connect/token" - the endpoint used to exchange the access token for a list of grants)strimzi.authorization.client.id(e.g.: "kafka" - the client representing a Kafka Broker which has Authorization Services enabled)
The authorizer will regularly reload the list of grants for active sessions. By default, it will do this once every minute. You can change this period or turn it off for debugging reasons (by setting it to "0"):
strimzi.authorization.grants.refresh.period.seconds(e.g.: "120" - the refresh job period in seconds)
The refresh job works by enumerating the active tokens and requesting the latest grants for each. It does that by using a thread pool. You can control the size of the thread pool (how much parallelism you want), the default value is 5:
strimzi.authorization.grants.refresh.pool.size(e.g.: "10" - the maximum of 10 parallel fetches of grants at a time)
Sometimes the deployment environment is such that there is a reverse proxy in front of the Keycloak, or some service like a network traffic analyzer, or flood protection server.
Or, the network may be glitchy resulting in intermittent connection problems. By default, any error while getting the initial grants for the new session,
will result in AuthorizationException returned to the Kafka client application. When the client retries some operation, the grants will be fetched again,
since they are not yet available. The following option enables reattempting the fetching of grants immediately so that if subsequent fetch is successful the client doesn't
receive the AuthorizationException. The default value is '0', meaning 'no retries'. Provide the value greater than '0' to set the number of repeated attempts:
strimzi.authorization.http.retries(e.g.: "1" - if initial fetching of grants for the session fails, immediately retry one more time)
Keep in mind that the worker thread of the request can get blocked on unresponsive connection, and you will want to set strimzi.authorization.connect.timeout.seconds
and strimzi.authorization.read.timeout.seconds to smaller values as well, as explained in the chapter on timeouts.
A single client typically uses a single unique access token for the concurrent sessions to the Kafka broker. As a result, the number of active tokens on the broker is generally less than the number of active sessions (connections). However, keep in mind that this is replicated across all Kafka brokers in the cluster, as clients maintain active sessions to multiple brokers.
Keycloak Authorization Services requires an access token to provide the grants for the user session. In the context of Kafka authorization the permissions are tied to a specific user id / principal name.
Multiple sessions and multiple access tokens for the same user will receive the same set of grants. For that reason the grants are cached in Keycloak authorizer 'per user', rather than 'per access token'.
The authorizer by default checks if the grants for the current user are available in grants cache. If grants are available, the existing grants are used. If not, they are fetched from Keycloak using the current session's access token and the current thread.
Once the grants are cached they will stay in the cache for the duration of the session or until the access token used to fetch them expires or idles out due to inactivity. There is a background job that periodically refreshes the cached grants (see: strimzi.authorization.grants.refresh.period.seconds).
The consequence of such a behavior is that the grants used for a new session may be out of sync with the state on the Keycloak server for up to the configured grants refresh period.
Sometimes you may want (e.g. for the debug purposes, for any changes in permissions to be reflected immediately) to fetch fresh grants for each newly established session, rather than use the already cached ones.
Note that this can noticeably increase the load from brokers to the Keycloak and aggravate any 'glitchiness' issues in communication with the Keycloak.
To enable such behavior, set the following option to false.
strimzi.authorization.reuse.grants(e.g.: "false" - if set to false, then when a new session is established the grants will be fetched from Keycloak using that session's access token and cached to grants cache)
Note
This option used to be set to false by default in version 0.12.0.
In versions prior to 0.13.0 the grants were cached per access token, rather than per user id / principal name.
The grants in the grants cache are shared between sessions of the same user id. To facilitate the timely removal from cache, the maximum time in seconds that a grant is kept in grants cache without being accessed can be configured. It allows for reliable active releasing of memory rather than waiting for VM's gc() to kick in for the timed-out sessions. Normally, the open sessions should not just idly consume resources, rather they should perform some operations. The default value for the maximum idle time of cached grants is 300 seconds. After that the grant will be removed from cache. If it is needed again it will be reloaded from the Keycloak server. The following option can be used to set a custom value for the maximum idle time for a cached grant:
strimzi.authorization.grants.max.idle.time.seconds(e.g.: "600" - if authorization grants for user are not access for more than ten minutes, remove them from grants cache)
There is a background service that removes the idle grants and grants with expired access token from grants cache by periodically iterating over the cache. The default time between two consecutive runs is 300 seconds. The following option can be used to set a custom value for the job period:
strimzi.authorization.grants.gc.period.seconds(e.g.: "600" - idle grants and grants with expired access token will be removed from grants cache every ten minutes)
There are some other things you may also want to configure. You may want to set a logical cluster name so you can target it with authorization rules:
strimzi.authorization.kafka.cluster.name(e.g.: "dev-cluster" - a logical name of the cluster which can be targeted with authorization services resource definitions, and permission policies)
You can integrate KeycloakAuthorizer with AclAuthorizer (in Zookeeper mode) or StandardAuthorizer (in KRaft mode):
strimzi.authorization.delegate.to.kafka.acl(e.g.: "true" - if enabled, then when action is not granted based on Keycloak Authorization Services grant it is delegated to ACLAuthorizer / StandardAuthorizer which can still grant it.)
If you turn on authorization support in Kafka brokers, you need to properly set super.users property.
By default, access token's sub claim is used as user id.
You may want to use another claim provided in access token as an alternative user id (username, email ...).
For example, to add the account representing Kafka Broker in Keycloak to super.users add the following to your server.properties file:
super.users=User:service-account-kafka
This assumes that you configured alternative user id extraction from the token by adding to JAAS configuration the parameter:
oauth.username.claim="preferred_username"
When using TLS to connect to Keycloak (which you always should in the production environment) you may need to configure the truststore.
You can see how to configure that in Configuring the TLS truststore chapter.
Use analogous properties except that they should start with strimzi.authorization. rather than oauth.
For a more in-depth guide to using Keycloak Authorization Services see the tutorial.
In order to grant Kafka permissions to users or service accounts you have to use the Keycloak Authorization Services rules on the OAuth client that represents the Kafka Broker - typically this client has kafka as its client ID.
The rules exist within the scope of this client, which means that if you have different Kafka clusters configured with different OAuth client IDs they would each have a separate set of permissions even though using the same set of users, and client accounts.
When the Kafka client authenticates using SASL/OAUTHEARER or SASL/PLAIN configured as 'OAuth over PLAIN' the KeycloakAuthorizer retrieves the list of grants for the current session from the Keycloak server using the access token of the current session. This list of grants is the result of evaluating the Keycloak Authorization Services policies and permissions.
There are four concepts used to grant permissions: resources, authorization scopes, policies, and permissions.
Typically, the initial configuration involves uploading the authorization scopes which creates a list of all the possible actions that can be performed on all the types of a Kafka resources. This step is performed only once, before defining any permissions. Alternatively, the authorization scopes can be added manually, but make sure to not introduce typos.
The following authorization scopes can be used, mirroring the Kafka security model: Create, Write, Read, Delete, Describe, Alter, DescribeConfigs, AlterConfigs, ClusterAction, IdempotentWrite.
The next step is to create targetting resources. When creating a Keycloak Authorization Services resource a pattern matching syntax is used to target the permissions rule to Kafka topics, consumer groups, or clusters.
The general pattern is as follows: RESOURCE_TYPE:NAME_PATTERN
There are five resource types: Topic, Group, Cluster, TransactionalId, DelegationToken.
And there are two matching options: exact matching (when the pattern does not end with *), and prefix matching (when the pattern ends with *).
A few examples:
Topic:my-topic
Topic:orders-*
Group:orders-*
Cluster:*
In addition, the general pattern can be prefixed by another one of the format kafka-cluster:CLUSTER_NAME, followed by comma, where cluster name is the name configured to KeycloakAuthorizer using strimzi.authorization.kafka.cluster.name.
For example:
kafka-cluster:dev-cluster,Topic:*
kafka-cluster:*,Group:b_*
When the kafka-cluster prefix is not present it is assumed to be kafka-cluster:*.
When the resource is defined a list of possible authorization scopes relevant to the resource should be added to the list of scopes. Currently, this needs to be added for each resource definition based on whatever actions make sense for the targeted resource type.
The Kafka security model understands the following actions on different resource types.
Topic:
- Write
- Read
- Describe
- Create
- Delete
- DescribeConfigs
- AlterConfigs
- IdempotentWrite
Group:
- Read
- Describe
- Delete
Cluster:
- Create
- Describe
- Alter
- DescribeConfigs
- AlterConfigs
- IdempotentWrite
- ClusterAction
TransactionalId:
- Describe
- Write
DelegationToken:
- Describe
While you may add any authorization scope to any resource, only the supported actions will ever matter.
The 'policies' are used to target permissions to one or more user accounts. The targeting can refer to specific user or service accounts, it can refer to the realm roles or client roles, it can refer to user groups, and it can even use a JS rule and match client's IP address for example.
Each policy can be given a name, and can be reused to target multiple permissions to multiple resources.
The 'permissions' are the final step where you pull together the policies, resources, and authorization scopes to grant access to one or more users.
Scope permissions should be used to grant fine-grained permissions to users.
Each policy should be descriptively named in order to make it very clear what permissions it grants to which users.
See the authorization tutorial to get a hands-on understanding of how to configure the permissions through Keycloak Authorization Services.
Configuring the Kafka client is very similar to configuring the Kafka broker.
Clients don't have multiple listeners so there is one authentication configuration, which makes things slightly simpler.
It is more common on the client to compose configuration properties programmatically rather than reading in a properties file (like server.properties).
In order to use insecure connectivity set the following property:
security.protocol=SASL_PLAINTEXT
If you want to use secure connectivity (using TLS) set:
security.protocol=SASL_SSL
Then enable OAUTHBEARER mechanism:
sasl.mechanism=OAUTHBEARER
Set the sasl.jaas.config property with JAAS configuration value that provides OAUTHBEARER handling, and configures Strimzi Kafka OAuth:
sasl.jaas.config=org.apache.kafka.common.security.oauthbearer.OAuthBearerLoginModule required \
oauth.token.endpoint.uri="https://server/token-endpoint" ;
Here we specified the oauth.token.endpoint.uri configuration key and its value as a JAAS configuration parameter.
A value of the sasl.jaas.config property always starts with:
org.apache.kafka.common.security.oauthbearer.OAuthBearerLoginModule required
Followed by zero or more configuration parameters, separated by a whitespace, and ended with a semicolon - ;
Install the Strimzi Kafka OAuth login callback:
sasl.login.callback.handler.class=io.strimzi.kafka.oauth.client.JaasClientOauthLoginCallbackHandler
The oauth.token.endpoint.uri property has to be specified whenever the token endpoint of the authorization server has to be contacted to obtain an access token. In practice that is in all cases except when access token is directly configured.
Its value points to OAuth2 Token Endpoint provided by authorization server.
Strimzi Kafka OAuth supports four ways to configure authentication on the client.
The first is to specify Client Credentials. This requires that a client is configured on the authorization server specifically for the individual client deployment. This is also called client credentials grant.
This is achieved by specifying the following:
oauth.client.id(e.g.: "my-client")
together with one of authentication options below.
When client starts to establish the connection with the Kafka Broker it will first obtain an access token from the configured Token Endpoint, authenticating with the configured client ID and configured authentication option using client_credentials grant type.
Specify the client secret.
oauth.client.secret(e.g.: "my-client-secret")
Specify the client assertion (JWT token) either directly through
oauth.client.assertion
or pointing to a file on the filesystem
oauth.client.assertion.location
The file contains secrets in plain text and should have proper permissions set - not readable by others.
The exact type of the token must also be communicated to the token endpoint and defaults to urn:ietf:params:oauth:client-assertion-type:jwt-bearer (which is specified in RFC-7523).
This can be overridden using property
oauth.client.assertion.type(i.e. useurn:ietf:params:oauth:client-assertion-type:saml2-bearer, specified in RFC-7522, for SAML 2 tokens)
The second way is to manually obtain and set a refresh token either directly through
oauth.refresh.token
or pointing to a file on the filesystem
oauth.refresh.token.location
The file contains secrets in plain text and should have proper permissions set - not readable by others.
When using this approach you are not limited to OAuth2 client_credentials grant type for obtaining a token. You can use a password grant type and authenticate as an individual user, rather than a client application. There is a simple CLI tool you can use to obtain the refresh token or an access token.
When client starts to establish the connection with the Kafka Broker it will first obtain an access token from the configured Token Endpoint, using refresh_token grant type for authentication.
The third way is to manually obtain and set an access token either directly through:
oauth.access.token
or pointing to a file on the filesystem
oauth.access.token.location
The file contains secrets in plain text and should have proper permissions set - not readable by others.
Access tokens are supposed to be short-lived in order to prevent unauthorized access if the token leaks. It is up to you, your environment, and how you plan to run your Kafka client application to consider if using long-lived access tokens is appropriate.
The fourth way is to use the OAuth 2 Resource Owner Password Credentials, also called password grant.
Support for that mechanism has been added for use in environments where client credentials for some reason can not be used for Kafka client applications and the use of refresh tokens is undesired. It is highly advised to create special user accounts with very limited permissions to represent the Kafka client applications. Before resorting to this mechanism, consider using refresh tokens instead.
oauth.password.grant.usernameoauth.password.grant.password
Note, that the password is configured in plain text. It is not supposed to represent a personal account nor any kind of account with broad permissions. It should use long, randomly generated passwords and for all the practical purposes it should behave as if it was a service account one would use with client credentials.
Consider using an external secrets management tool to securely store your configuration.
Some authorization servers require that scope is specified:
oauth.scope
Scope is sent to the Token Endpoint when obtaining the access token.
Similarly, sometimes the authorization server may require that audience is specified:
oauth.audience
Audience is sent to the Token Endpoint when obtaining the access token.
For debug purposes you may want to properly configure which JWT token attribute contains the user id of the account used to obtain the access token:
oauth.username.claim(e.g.: "preferred_username", for nested attributes use[topAttrKey].[subAttrKey]. Claim names can also be single quoted:['topAttrKey'].['subAttrKey'])
This does not affect how Kafka client is presented to the Kafka Broker. The broker performs user id extraction from the token once again or it uses the Introspection Endpoint or the User Info Endpoint to get the user id.
By default, the user id on the Kafka client is obtained from sub claim in the token - only if token is JWT.
Client side user id extraction is not possible when token is an opaque token - not JWT.
You may want to explicitly specify the period the access token is considered valid. This allows you to shorten the token's lifespan.
On the client the access token is reused for multiple connections with the Kafka Broker. Before it expires the token is refreshed in the background so that a valid token is always available for all the connections. You can make the token refresh more often than strictly necessary by shortening its lifespan:
oauth.max.token.expiry.seconds(e.g.: "600" - set token expiry to 10 minutes)
If expiry is set to more that actual token expiry, this setting will have no effect. Note that this does not make any change to the token itself - the original token is still passed to the server.
If you have DEBUG logging turned on for io.strimzi, and are using opaque (non JWT) tokens, you can avoid parsing error warnings in the logs by specifying:
oauth.access.token.is.jwt(e.g.: "false")
When setting this to false the client library will not attempt to parse and introspect the token as if it was JWT.
If your Kafka client applications are deployed in unreliable network environment, and the requests to your authorization server are failing intermittently, you can use the following options to control automatic retries to obtain the token.
By default, a failed request to the Token Endpoint will result in immediate failure and may result in AuthenticationException.
The following option enables retrying the request.
The default value is '0', meaning 'no retries'. Provide the value greater than '0' to set the number of repeated attempts:
oauth.http.retries(e.g.: "1" - if initial request fails, retry one more time)
You may also specify a pause time between requests in order not to flood the authorization server.
The default value is '0', meaning 'no pause'. Provide the value greater than '0' to set the pause time between attempts in milliseconds:
oauth.http.retry.pause.millis(e.g.: "500" - if a retry is attempted, there will first be a half-a-second pause)
If your Kafka Broker uses some other custom OAUTHBEARER implementation, you may need to pass it SASL extensions options.
These are key:value pairs representing a client context, that are sent to the Kafka Broker when the new session is started.
You can pass SASL extensions options by using oauth.sasl.extension. as a key prefix:
oauth.sasl.extension.KEY(e.g.: "VALUE" - replace KEY with the actual SASL extension key name, and VALUE with the actual value)
For example, you could add multiple sasl extensions options: oauth.sasl.extension.key1="value1" oauth.sasl.extension.key2="value2"
Java based clients using Kafka client library 2.2 or later will automatically perform re-authentication if the broker supports it.
There are several Kafka client properties that control how the client refreshes the access token on the client side, before re-authenticating, based on token's expiry:
- sasl.login.refresh.buffer.seconds
- sasl.login.refresh.min.period.seconds
- sasl.login.refresh.window.factor
- sasl.login.refresh.window.jitter
Also keep in mind that if configuring the client token by using oauth.access.token property (manually obtaining it first), there is no way to automatically refresh such a token, and thus the re-authentication will use the already expired token one more time, resulting in authentication failure, and closure of the connection.
Note, that client-side token refresh works independently of re-authentication in the sense that it refreshes the token as necessary based on token's expiry information. Once the token is obtained by the client, it is cached and re-used for multiple authentication attempts possibly across multiple connections. If AuthenticationException occurs, that does not trigger the token refresh on the client. The only way to force the Java client library to perform token refresh is to re-initialise the KafkaProducer / KafkaConsumer.
Here's an example of a complete my.properties file which you can load in your client as java.util.Properties object, and pass to KafkaProducer or KafkaConsumer.
security.protocol=SASL_PLAINTEXT
sasl.mechanism=OAUTHBEARER
sasl.jaas.config=org.apache.kafka.common.security.oauthbearer.OAuthBearerLoginModule required \
oauth.client.id="team-a-client" \
oauth.client.secret="team-a-client-secret" \
oauth.token.endpoint.uri="http://keycloak:8080/realms/kafka-authz/protocol/openid-connect/token" ;
sasl.login.callback.handler.class=io.strimzi.kafka.oauth.client.JaasClientOauthLoginCallbackHandler
When you have a Kafka Client connecting to a single Kafka cluster it only needs one set of credentials - in such a situation it is sometimes more convenient to just use ENV vars.
In that case you could simplify my.properties file:
security.protocol=SASL_PLAINTEXT
sasl.mechanism=OAUTHBEARER
sasl.jaas.config=org.apache.kafka.common.security.oauthbearer.OAuthBearerLoginModule required ;
sasl.login.callback.handler.class=io.strimzi.kafka.oauth.client.JaasClientOauthLoginCallbackHandler
And pass additional configuration as ENV vars:
export OAUTH_CLIENT_ID="team-a-client"
export OAUTH_CLIENT_SECRET="team-a-client-secret"
export OAUTH_TOKEN_ENDPOINT_URI="http://keycloak:8080/realms/kafka-authz/protocol/openid-connect/token"
Note that if you have JAAS config parameters with the same names (lowercase with dots) they would not take effect - ENV vars will override them.
When using the Apache Kafka Java client library, you can distinguish between exceptions that occur as a result of authentication or authorization issues, and other exceptions.
From the client's point of view there usually isn't much to do when the exception occurs but to either retry the operation or exit.
Inside the cloud deployment it is a valid reaction to simply exit the process and let the cloud infrastructure start a new instance of the client service. But more often than not, a more effective strategy is to repeat the last operation again which can take advantage of the current state of the program loaded in the memory.
If there is a problem during authentication the client will receive the org.apache.kafka.common.errors.AuthenticationException.
Once the session is authenticated, and if some authorizer is configured, the failed authorization will result in the org.apache.kafka.common.errors.AuthorizationException.
In order to retry the operation you'll want to close the current producer or consumer, and create a new one from scratch in order to force the client to obtain a new access token. You'll also maybe want to make a slight pause when this happens, to prevent flooding the authorization server with the token requests.
String topic = "my-topic";
KafkaConsumer<String, String> consumer = new KafkaConsumer<>(config);
try {
consumer.subscribe(Arrays.asList(topic));
while (true) {
ConsumerRecords<String, String> records = consumer.poll(Duration.ofSeconds(1));
for (ConsumerRecord<String, String> record : records) {
System.out.println("Consumed message: " + record.value());
}
}
} catch (AuthenticationException | AuthorizationException e) {
consumer.close();
consumer = new KafkaConsumer<>(config);
} catch (InterruptedException e) {
throw new RuntimeException("Interrupted while consuming a message!", e);
}
Similarly, for asynchronous API:
Producer<String, String> producer = new KafkaProducer<>(props);
for (int i = 0; ; i++) {
try {
producer.send(new ProducerRecord<>(topic, "Message " + i))
.get();
System.out.println("Produced Message " + i);
} catch (InterruptedException e) {
throw new RuntimeException("Interrupted while sending!");
} catch (ExecutionException e) {
final Throwable cause = e.getCause();
if (cause instanceof AuthenticationException
|| cause instanceof AuthorizationException) {
producer.close();
producer = new KafkaProducer<>(props);
} else {
throw new RuntimeException("Failed to send message: " + i, e);
}
}
}
There is no OAuth specific configuration that would be required on the client when authenticating to Kafka Broker with SASL/PLAIN mechanism.
The Kafka Broker has to have the SASL/PLAIN mechanism enabled and properly configured with JaasServerOauthOverPlainValidatorCallbackHandler validation callback handler.
Then, the standard SASL/PLAIN configuration is used on the client with the following two options:
- the client can authenticate using the service account client ID and secret. Setting the
usernameto the value of client ID, and setting thepasswordto the value of client secret. The Kafka broker will use these client credentials to obtain the access token from the authorization server. - the client can authenticate using a long-lived access token obtained through a browser sign-in or through using
curlor similar CLI tool to obtain the access token withclient credentialsor thepasswordauthentication, then setting theusernameto the same principal id that the broker will resolve from the provided access token, and settingpasswordto prefix$accessToken:followed by the access token string. It is the presence of the$accessToken:prefix that tells the broker that it should extract the access token from thepassword. Ifclient_credentialsauthentication over PLAIN is disabled on the listener, then the access token should be passed as-is, without prefixing it.
For example, when using the Kafka Client Java library the configuration might look like:
security.protocol=SASL_PLAINTEXT
sasl.mechanism=PLAIN
sasl.jaas.config=org.apache.kafka.common.security.plain.PlainLoginModule required \
username="team-a-client" \
password="team-a-client-secret" ;
Note that when using SASL/PLAIN the credentials are actually sent to the Kafka Broker, which is not the case when SASL/OAUTHBEARER is used, when the client library contacts the OAuth2 authorization service first, to obtain the access token, and then only sends to the Kafka Broker the access token. On the other hand, the client doesn't need to connect to OAuth2 authorization server first, and there is no need for additionally configuring truststore for TLS connectivity.
The great advantage of SASL/PLAIN is that it can be used by Kafka clients that have no ready-to-use SASL/OAUTHBEARER support - SASL/PLAIN can be used with any Kafka client tool.
For example, to connect with kafkacat you could run:
kafkacat -b my-cluster-kafka-bootstrap:9092 -X security.protocol=SASL_PLAINTEXT -X sasl.mechanism=PLAIN -X sasl.username=team-a-client -X sasl.password="team-a-client-secret" -t a_topic -P
When your application connects to your authorization server, it should always use a secure connection - https://.
That goes for the Kafka Brokers, as well as for the Kafka clients.
You may need to provide a custom truststore for connecting to your authorization server or may need to turn off certificate hostname verification.
Use the following configuration properties to configure a JKS or PKCS12 truststore:
oauth.ssl.truststore.location(e.g.: "/path/to/truststore.p12")oauth.ssl.truststore.password(e.g.: "changeit")oauth.ssl.truststore.type(e.g.: "pkcs12")
You can also use PEM certificates:
oauth.ssl.truststore.location(e.g.: "/path/to/ca.crt")oauth.ssl.truststore.certificates(e.g.: "-----BEGIN CERTIFICATE-----\n....")oauth.ssl.truststore.type(e.g.: "PEM")
(Use always only one of the oauth.ssl.truststore.location and oauth.ssl.truststore.certificates options).
You may want to explicitly set the random number implementation provider to use a non-default one:
oauth.ssl.secure.random.implementation(e.g.: "SHA1PRNG")
If you need to turn off certificate hostname verification set the following property to empty string:
oauth.ssl.endpoint.identification.algorithm(e.g. "")
These configuration properties can be used to configure truststore for KeycloakAuthorizer as well, but they should be prefixed with strimzi.authorization. instead of oauth. when specifically targeting this authorizer (e.g.: strimzi.authorization.ssl.truststore.location).
You may want to set these options globally as system properties or env vars to apply for all the listeners and the KeycloakAuthorizer in which case you would use oauth. prefix. But when configured specifically for KeycloakAuthorizer in server.properties you have to use strimzi.authorization. prefix.
When the Kafka Broker or the Kafka Client communicates with the authorization server, the default connect and read timeouts are applied to the request. By default, they are both set to 60 seconds. That prevents the indefinite stalling of the HTTP request which may occur sometimes with glitchy network components.
Use the following configuration options to customize the connect and read timeouts:
oauth.connect.timeout.seconds(e.g.: 60)oauth.read.timeout.seconds(e.g.: 60)
These options can be set as system properties, as env variables or as jaas properties as described in Configuring the OAuth2.
These configuration properties can be used to configure timeouts for KeycloakAuthorizer as well, but they should be prefixed with strimzi.authorization. instead of oauth. when specifically targeting this authorizer (e.g.: strimzi.authorization.connect.timeout.seconds).
You may want to set these options globally as system properties or env vars to apply for all the listeners and the KeycloakAuthorizer in which case you would use oauth. prefix. But when configured specifically for KeycloakAuthorizer in server.properties you have to use strimzi.authorization. prefix.
NOTE: These options are available since version 0.10.0. Before, one could only apply JDK network options sun.net.client.defaultConnectTimeout, and sun.net.client.defaultReadTimeout as described here, and the default was no timeout.
By default, the gathering and exporting of metrics is disabled. Metrics are available to get an insight into the performance and failures during token validation, authorization operations and client authentication to the authorization server. You can also monitor the authorization server requests by background services such as refreshing of JWKS keys and refreshing of grants when KeycloakAuthorizer is used.
You can enable metrics for token validation, and KeycloakAuthorizer on the Kafka broker or for client authentication on the client by setting the following JAAS option to true:
oauth.enable.metrics(e.g.: "true")
You can also enable metrics only for KeycloakAuthorizer by setting an analogous option in Kafka broker's server.properties file:
strimzi.authorization.enable.metrics(e.g.: "true")
If OAUTH_ENABLE_METRICS env variable is set or if oauth.enable.metrics system property is set, that will also enable the metrics for KeycloakAuthorizer (as well as for token validation, and client authentication).
The OAuth metrics ignores the Kafka metric.reporters option in order to prevent automatically instantiating double instances of reporters. Most reporters may expect that they are singleton object and may not function properly in multiple copies.
Instead, there is strimzi.oauth.metric.reporters option where the reporters that support multiple copies can be specified for the purpose of metrics integration:
strimzi.oauth.metric.reporters(e.g.: "org.apache.kafka.common.metrics.JmxReporter,org.some.package.SomeMetricReporter", use ',' as a separator to enable multiple reporters.)
If this configuration option is not set and OAuth metrics is enabled for some component, then a new instance of org.apache.kafka.common.metrics.JmxReporter will automatically be instantiated to provide JMX integration for OAuth metrics.
However, if strimzi.oauth.metric.reporters is set, then only the reporters specified in the list will be instantiated and integrated. Setting the option to an empty string will result in no reporters instantiated.
The configuration option strimzi.oauth.metric.reporters on the Kafka broker has to be configured as an env variable or a system property. Using it on the Kafka broker inside server.properties does not work reliably due to multiple pluggability mechanisms that can be used (authorizer, authentication callback handler, inter-broker client).
Some of these mechanisms get the server.properties filtered so only configuration recognised by Kafka makes it through. However, this is a global OAuth Metrics configuration, and it is initialized on first use by any of the components, using the configuration provided to that component.
Specifically, the inter-broker client using OAUTHBEARER might be the first to trigger OAuth Metrics initialisation on the broker, and does not see this config option.
In order to reliably configure strimzi.oauth.metric.reporters one of the following options should be used when starting a Kafka broker:
STRIMZI_OAUTH_METRIC_REPORTERSenv variablestrimzi.oauth.metric.reportersenv variable or system property
At the moment there is no way to integrate with the existing Kafka metrics / reporters objects already instantiated in different Kafka runtimes (producer, consumer, broker, ...). When OAuth metrics is enabled the OAuth layer has to create its own copies of metric reporters.
NOTE: In OAuth versions preceding 0.13.0 the configuration option metric.reporters was used to configure reporters which were consequently automatically instantiated twice.
The configuration option metric.reporters is no longer used.
The Kafka options that control sampling are honored: metrics.num.samples, metrics.recording.level and metrics.sample.window.ms.
# Enable OAuth metrics for all listeners, Keycloak authorizer, and inter-broker clients:
export OAUTH_ENABLE_METRICS=true
# Use a custom metric reporter rather than the default JmxReporter
export STRIMZI_OAUTH_METRIC_REPORTERS=org.some.package.SomeMetricReporter
bin/kafka-server-start.sh config/server.properties
# Show the content of client properties file
cat ~/client.properties
...
sasl.jaas.config=org.apache.kafka.common.security.oauthbearer.OAuthBearerLoginModule required \
oauth.token.endpoint.uri="https://server/token-endpoint" oauth.client.id="clientId" oauth.client.secret="client-secret" oauth.enable.metrics="true";
strimzi.oauth.metric.reporters=org.some.package.SomeMetricReporter
...
# Start the client
bin/kafka-console-producer.sh --broker-list kafka:9092 --topic my-topic --producer.config=$HOME/client.properties
# Enable OAuth metrics for all listeners, Keycloak authorizer, and inter-broker clients:
# With no 'strimzi.oauth.metric.reporters' specified 'org.apache.kafka.common.metrics.JmxReporter' will be used automatically
export OAUTH_ENABLE_METRICS=true
bin/kafka-server-start.sh config/server.properties
A common use-case is for metrics to be exposed through JMX managed beans. They can then also be exposed as Prometheus metrics by using the Prometheus JMX Exporter agent, and mapping the JMX metrics names to prometheus metrics names.
If oauth.config.id is specified in JAAS configuration of the listener or the client, it will be available in MBean / metric name as contextId attribute. If not specified, it will be calculated from JAAS configuration for the validator or default to client in client JAAS config, or keycloak-authorizer for KeycloakAuthorizer metrics.
When JmxReporter is enabled, managed beans are registered on demand, containing the attributes that are easily translated into Prometheus metrics.
Each registered MBean contains two counter variables - count, and totalTimeMs.
It also contains three gauge variables - minTimeMs, maxTimeMs and avgTimeMs. These are measured within the configured sample time window.
The count contains the number of requests of the specific context (as represented by attributes).
The totalTimeMs contains the cumulative time in milliseconds spent in the requests of the specific context.
The minTimeMs contains the minimum request time within the configured time window.
The maxTimeMs contains the maximum request time within the configured time window.
The avgTimeMs contains the average request time within the configured time window.
Two reads of count and totalTimeMs allow to calculate the average request time within the time interval as delta Time / delta Count.
The following MBeans are registered, depending on which parts of strimzi-kafka-oauth are in use.
For fast local JWT token based validation there are:
-
The metrics for validation requests which occur as part of the authentication:
strimzi.oauth:type=validation_requests,context=$CONFIG_ID,kind=jwks,host="$HOST:$PORT",path="$JWKS_ENDPOINT_PATH",mechanism=$MECHANISM,outcome=successstrimzi.oauth:type=validation_requests,context=$CONFIG_ID,kind=jwks,host="$HOST:$PORT",path="$JWKS_ENDPOINT_PATH",mechanism=$MECHANISM,outcome=error,error_type=$ERROR_TYPE
-
The metrics for http requests to JWKS endpoint of the authorization server that are periodically performed in the background:
strimzi.oauth:type=http_requests,context=$CONFIG_ID,kind=jwks,host="$HOST:$PORT",path="$JWKS_ENDPOINT_PATH",outcome=success,status=200strimzi.oauth:type=http_requests,context=$CONFIG_ID,kind=jwks,host="$HOST:$PORT",path="$JWKS_ENDPOINT_PATH",outcome=error,error_type=http,status=$STATUS
For introspection based validation there are:
-
The metrics for validation requests which occur as part of the authentication:
strimzi.oauth:type=validation_requests,context=$CONFIG_ID,kind=introspect,host="$HOST:$PORT",path="$INTROSPECTION_ENDPOINT_PATH",mechanism=$MECHANISM,outcome=successstrimzi.oauth:type=validation_requests,context=$CONFIG_ID,kind=introspect,host="$HOST:$PORT",path="$INTROSPECTION_ENDPOINT_PATH",mechanism=$MECHANISM,outcome=error,error_type=$ERROR_TYPE
-
The metrics for http requests to introspect endpoint during validation requests:
strimzi.oauth:type=http_requests,context=$CONFIG_ID,kind=introspect,host="$HOST:$PORT",path="$INTROSPECTION_ENDPOINT_PATH",outcome=success,status=200strimzi.oauth:type=http_requests,context=$CONFIG_ID,kind=introspect,host="$HOST:$PORT",path="$INTROSPECTION_ENDPOINT_PATH",outcome=error,error_type=http,status=$STATUS
-
The metrics for http requests to userinfo endpoint during validation requests (if configured):
strimzi.oauth:type=http_requests,context=$CONFIG_ID,kind=userinfo,host="$HOST:$PORT",path="$USERINFO_ENDPOINT_PATH",outcome=success,status=200strimzi.oauth:type=http_requests,context=$CONFIG_ID,kind=userinfo,host="$HOST:$PORT",path="$USERINFO_ENDPOINT_PATH",outcome=error,error_type=http,status=$STATUS
For validation performed using OAuth over PLAIN there are additionally:
- The metrics for http requests to obtain the access token in client's name:
strimzi.oauth:type=http_requests,context=$CONFIG_ID,kind=plain,host="$HOST:$PORT",path="$TOKEN_ENDPOINT_PATH",outcome=success,status=200strimzi.oauth:type=http_requests,context=$CONFIG_ID,kind=plain,host="$HOST:$PORT",path="$TOKEN_ENDPOINT_PATH",outcome=error,error_type=http,status=$STATUS
For Keycloak authorization there are:
-
The metrics for authorization requests:
strimzi.oauth:type=authorization_requests,context=$CONFIG_ID,kind=keycloak-authorization,host="$HOST:$PORT",path="$TOKEN_ENDPOINT_PATH",outcome=successstrimzi.oauth:type=authorization_requests,context=$CONFIG_ID,kind=keycloak-authorization,host="$HOST:$PORT",path="$TOKEN_ENDPOINT_PATH",outcome=error,error_type=$ERROR_TYPE
-
The metrics for http requests to retrieve or refresh grants for the authenticated user:
strimzi.oauth:type=http_requests,context=$CONFIG_ID,kind=grants,host="$HOST:$PORT",path="$TOKEN_ENDPOINT_PATH",outcome=success,status=200strimzi.oauth:type=http_requests,context=$CONFIG_ID,kind=grants,host="$HOST:$PORT",path="$TOKEN_ENDPOINT_PATH",outcome=error,error_type=http,status=$STATUS
For client-side authentication there are:
-
The metrics for client authentication requests:
strimzi.oauth:type=authentication_requests,context=$CONFIG_ID,kind=client-auth,host="$HOST:$PORT",path="$TOKEN_ENDPOINT_PATH",outcome=successstrimzi.oauth:type=authentication_requests,context=$CONFIG_ID,kind=client-auth,host="$HOST:$PORT",path="$TOKEN_ENDPOINT_PATH",outcome=error,error_type=$ERROR_TYPE
-
The metrics for http requests to obtain the access token:
strimzi.oauth:type=http_requests,context=$CONFIG_ID,kind=client-auth,host="$HOST:$PORT",path="$TOKEN_ENDPOINT_PATH",outcome=success,status=200strimzi.oauth:type=http_requests,context=$CONFIG_ID,kind=client-auth,host="$HOST:$PORT",path="$TOKEN_ENDPOINT_PATH",outcome=error,error_type=http,status=$STATUS
The meaning of the variables used in the above names is as follows.
$CONFIG_IDThe value specified asoauth.config.idconfiguration option. If not specified it is set toclientfor Kafka client,kafka-authorizerforKeycloakAuthorizer, or calculated from other configuration parameters for the validation on Kafka broker.$HOST:$PORTThe hostname and port used to connect to authorization server. Extracted from the configured value foroauth.token.endpoint.uri,oauth.introspect.endpoint.uri,oauth.userinfo.endpoint.uri,oauth.jwks.endpoint.uriorstrimzi.authorization.token.endpoint.uri(depending on the context). If the port is not part of the uri it is defaulted to80forhttp, and to443forhttps.$PATHThepathpart of the associated URI (starts with/);$ERROR_TYPEOnly set whenoutcome=error. The possible values are:connect,tls,http,other.$STATUSSet to200for successful http requests. Whenerror_type=httpthe value is the returned HTTP status code.
The metrics-config.yml file contains the definitions for mapping the metrics from MBeans to Prometheus metrics names.
The following metrics are exposed as the result of the mapping.
For each pattern there are five metrics exposed with $METRIC being count, totaltimems, mintimems, maxtimems and avgtimems.
For fast local JWT token based validation there are:
-
The metrics for validation requests which occur as part of the authentication:
strimzi_oauth_validation_requests_$METRIC{type="jwks"}
-
The metrics for http requests to JWKS endpoint of the authorization server that are periodically performed in the background:
strimzi_oauth_http_requests_$METRIC{type="jwks"}
For introspection based validation there are:
-
The metrics for validation requests which occur as part of the authentication:
strimzi_oauth_validation_requests_$METRIC{type="introspect"}
-
The metrics for http requests to introspect endpoint during validation requests:
strimzi_oauth_http_requests_$METRIC{type="introspect"}
-
The metrics for http requests to userinfo endpoint during validation requests (if configured):
strimzi_oauth_http_requests_$METRIC{type="userinfo"}
For validation performed using OAuth over PLAIN there are additionally:
- The metrics for http requests to obtain the access token in client's name:
strimzi_oauth_http_requests_$METRIC{type="plain"}
For Keycloak authorization there are:
-
The metrics for authorization requests:
strimzi_oauth_authorization_requests_$METRIC{type="keycloak-authorization"}
-
The metrics for http requests to retrieve or refresh grants for the authenticated user:
strimzi_oauth_http_requests_$METRIC{type="keycloak-authorization"}
For client-side authentication there are:
-
The metrics for client authentication requests:
strimzi_oauth_authentication_requests_$METRIC{type="client-auth"}
-
The metrics for http requests to obtain the access token:
strimzi_oauth_http_requests_$METRIC{type="client-auth"}
- Get the average request time in ms during the last minute across all http requests to a specific authorization server:
rate(strimzi_oauth_http_requests_totaltimems{host="sso:443"}[1m]) / rate(strimzi_oaouth_http_requests_count{host="sso:443"}[1m])
Note, that this gives reliable results if scrape period is 15 seconds. If scrape period is longer, you should use a multiple of 4 as a minimum time span to average across. For example, if scrape period is 30 seconds, use 2m span instead of 1m.
- Get the number of http requests in the last minute:
idelta(strimzi_oauth_http_requests_count[1m])
- Get the network error counts across all http requests in the last minute:
idelta(strimzi_oauth_http_requests_count{outcome="error",error_type="connect"}[1m])
- Get the TLS error counts across all http requests in the last minute:
idelta(strimzi_oauth_http_requests_count{outcome="error",error_type="tls"}[1m])
For a demo / tutorial covering OAuth2 authentication see examples README.
For another demo / tutorial covering token based authorization using Keycloak Authorization Services see authorization README
There are many reasons the token can be invalid, and rejected by Kafka broker during authentication.
Here is a checklist of most common problems:
-
The client should use the same HOST and PORT when connecting to the Authorization Server as the Kafka broker.
For example, if you specify
oauth.valid.issuer.uritohttps://sso/then the client should usehttps://sso/tokensas aoauth.token.endpoint.uri, rather thanhttp://sso/tokensorhttps://localhost:8443/tokensor similar that route to the same authorization server endpoint, but using a different HOST and PORT in the url due to going via different routes or tcp tunnels. -
The access token may have expired, and the client has to obtain a new one
-
The listener configuration on the Kafka broker may impose additional constraints on the token which the specific token doesn't comply with by using
oauth.custom.claim.checkoroauth.check.audiencefor example.
You can debug the issue by enabling DEBUG level on io.strimzi logger on the Kafka broker.
Make sure that the authorization server instance used by the Kafka client to obtain the access token is the same as the authorization server endpoints configured on the
Kafka broker listener your client is connecting to. That means that the Kafka client and the Kafka broker have to use the same 'user domain' - for example with Keycloak they have to use the same realm. Different listeners can be configured to use different authorization servers, so pay attention about the port your client connects to.
There are some other possibilities why this error can occur.
The JWT tokens are signed by the authorization server when they are issued. The signing keys may be rotated or an existing instance of authorization server may be removed and a fresh new instance started in its place. In that situation a mismatch may occur between keys used to sign the tokens the client sends to Kafka broker during authentication, and the list of valid signing keys on the Kafka broker.
The client may have obtained a new access token, but the Kafka broker has not yet refreshed the public keys from JWKS endpoint resulting in a mismatch. The Kafka Broker will automatically refresh JWT keys if it encounters an unknown kid, and the problem will self-correct in this case, you may just need to repeat your request a few times.
It can also happen the other way around. Your existing client may still use the refresh token or the access token issued by the previous authorization server instance while the Kafka broker has already refreshed the keys from JWKS endpoint - resulting in a mismatch between the private key used by authorization server to sign the token, and the published public keys (JWKS endpoint). Since the problem is on the client you may need to configure your client with a newly obtained refresh token, or access token. If you configure your client with clientId and secret, it should autocorrect by itself, you just need to restart it.
For certain servers setting the Accept header on outbound requests to application/json can cause the identity provider to reject the request. If that is an issue, you can set oauth.include.accept.header to false and remove the Accept header from outbound requests made by the Kafka server or client.
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