Pulsar Flink Connector

The Pulsar Flink connector implements elastic data processing using Apache Pulsar and Apache Flink.

For details about the Chinese document, see here.

Prerequisites

Java 8 or higher version
Flink 1.9.0 or higher version
Pulsar 2.4.0 or higher version

Basic information

This section describes basic information about the Pulsar Flink connector.

Client

Currently, the following Flink versions are supported.

Flink 1.9 - 1.10: they are maintained in the flink-1.9 branch.
Flink 1.11: it is maintained in the flink-1.11 branch.
Flink 1.12: it is maintained in the master branch.

Note
Since Flink's API has changed greatly, we mainly work on new features in the master branch and fix bugs in other branches.

The JAR package is located in the Bintray Maven repository of StreamNative.

For projects using SBT, Maven, or Gradle, you can set the following parameters for your project.

FLINK_VERSION: currently, versions 1.9, 1.11, and 1.12 are available.
SCALA_BINARY_VERSION: this parameter defines the Scala version used by Flink. Versions 2.11 and 2.12 are available.
PULSAR_FLINK_VERSION: it is the version of the Pulsar Flink connector. Usually, use a three-digit version (such as version 2.7.0) for a master release and a four-digit version for a branch release (such as version 2.7.0.1).

Here is an example about how to configure parameters for projects using SBT, Maven, or Gradle.

groupId = io.streamnative.connectors
artifactId = pulsar-flink-connector-{{SCALA_BINARY_VERSION}}-{{FLINK_VERSION}}
version = {{PULSAR_FLINK_VERSION}}

Maven projects

For Maven projects, you can add the repository configuration to your pom.xml, as shown below.

  <repositories>
    <repository>
      <id>central</id>
      <layout>default</layout>
      <url>https://repo1.maven.org/maven2</url>
    </repository>
    <repository>
      <id>bintray-streamnative-maven</id>
      <name>bintray</name>
      <url>https://dl.bintray.com/streamnative/maven</url>
    </repository>
  </repositories>

For Maven projects, you can use the following shade plugin definition template to build an application JAR package that contains all the dependencies required for the client library and Pulsar Flink connector.

<plugin>
  <!-- Shade all the dependencies to avoid conflicts -->
  <groupId>org.apache.maven.plugins</groupId>
  <artifactId>maven-shade-plugin</artifactId>
  <version>${maven-shade-plugin.version}</version>
  <executions>
    <execution>
      <phase>package</phase>
      <goals>
        <goal>shade</goal>
      </goals>
      <configuration>
        <createDependencyReducedPom>true</createDependencyReducedPom>
        <promoteTransitiveDependencies>true</promoteTransitiveDependencies>
        <minimizeJar>false</minimizeJar>

        <artifactSet>
          <includes>
            <include>io.streamnative.connectors:*</include>
            <!-- more libs to include here -->
          </includes>
        </artifactSet>
        <filters>
          <filter>
            <artifact>*:*</artifact>
            <excludes>
              <exclude>META-INF/*.SF</exclude>
              <exclude>META-INF/*.DSA</exclude>
              <exclude>META-INF/*.RSA</exclude>
            </excludes>
          </filter>
        </filters>
        <transformers>
          <transformer implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer" />
          <transformer implementation="org.apache.maven.plugins.shade.resource.PluginXmlResourceTransformer" />
        </transformers>
      </configuration>
    </execution>
  </executions>
</plugin>

Gradle projects

For Gradle projects, you can add the repository configuration to your build.gradle, as shown below.

repositories {
         maven {
             url 'https://dl.bintray.com/streamnative/maven'
         }
}

For gradle projects, you can use the following shade plugin definition template to build an application JAR package that contains all the dependencies required for the client library and Pulsar Flink connector.

buildscript {
     repositories {
         jcenter()
     }
     dependencies {
         classpath 'com.github.jengelman.gradle.plugins:shadow:6.0.0'
     }
}

apply plugin: 'com.github.johnrengelman.shadow'
apply plugin: 'java'

Build Pulsar Flink connector

To build the Pulsar Flink connector for reading data from Pulsar or writing the results to Pulsar, follow these steps.

Check out the source code.

git clone https://github.com/streamnative/pulsar-flink.git
cd pulsar-flink

Install the Docker.

The Pulsar Flink connector uses Testcontainers for integration test. To run the integration test, ensure to install the Docker. For details about how to install the Docker, see here.

Set the Java version.

Modify java.version and java.binary.version in pom.xml.

Note
Ensure that the Java version should be identical to the Java version for the Pulsar Flink connector.
Build the project.

mvn clean install -DskipTests

Run the test.

mvn clean install

After the Pulsar Flink connector is installed, a JAR package that contains all the dependencies is generated in both the local Maven repository and the target directory.

Note
If you use intellij IDEA to debug this project, you might encounter the org.apache.pulsar.shade.org.bookkeeper.ledger package error. To fix the error, use the mvn clean install -DskipTests command to install the JAR package to the local repository, ignore the managed-ledger-shaded Maven module on the project, and then click Refresh.

Deploy Pulsar Flink connector

This section describes how to deploy the Pulsar Flink connector.

Client library

For any Flink application, use the ./bin/flink run command to compile and start your application.

If you have already built a JAR package with dependencies using the above shade plugin, you can use the --classpath option to add your JAR package.

Note
The path must be in a protocol format (such as file://) and the path must be accessible on all nodes.

Example

./bin/flink run -c com.example.entry.point.ClassName file://path/to/jars/your_fat_jar.jar

Scala REPL

The Scala REPL is a tool (scala) for evaluating expressions in Scala. Use the bin/start-scala-shell.sh command to deploy Pulsar Flink connector on Scala client. You can use the --addclasspath to add pulsar-flink-connector_{{SCALA_BINARY_VERSION}}-{{ PULSAR_FLINK_VERSION}}.jar package.

Example

./bin/start-scala-shell.sh remote <hostname> <portnumber>
 --addclasspath pulsar-flink-connector-{{SCALA_BINARY_VERSION}}-{{PULSAR_FLINK_VERSION}}.jar

For more information on submitting applications through the CLI, see Command-Line Interface .

SQL client

The SQL Client is used to write SQL queries for manipulating data in Pulsar, you can use the -addclasspath option to add pulsar-flink-connector-{{SCALA_BINARY_VERSION}}-{{PULSAR_FLINK_VERSION}}.jar package.

Example

./bin/sql-client.sh embedded --jar pulsar-flink-connector-{{SCALA_BINARY_VERSION}}-{{PULSAR_FLINK_VERSION}}.jar

Note
If you put the JAR package of our connector under $FLINK_HOME/lib, do not use --jar again to specify the package of the connector.

By default, to use the Pulsar directory in the SQL client and register it automatically at startup, the SQL client reads its configuration from the ./conf/sql-client-defaults.yaml environment file. You need to add the Pulsar catalog to the catalogs section of this YAML file, as shown below.

catalogs:
- name: pulsarcatalog
    type: pulsar
    default-database: tn/ns
    service-url: "pulsar://localhost:6650"
    admin-url: "http://localhost:8080"
    format: json

Usage

This section describes how to use the Pulsar Flink connector in the stream environment and table environment.

Stream environment

This section describes how to use the Pulsar Flink connector in the stream environment.

Source

In Pulsar Flink, the Pulsar consumer is called FlinkPulsarSource<T>. It accesses to one or more Pulsar topics.

Its constructor method has the following parameters.

serviceUrl (service address) and adminUrl (administrative address): they are used to connect to the Pulsar instance.
PulsarDeserializationSchema<T>: when the FlinkPulsarSource is used, you need to set the PulsarDeserializationSchema<T> parameter.
Properties: it is used to configure the behavior of the Pulsar consumer, including the topic, topics, and topicsPattern options. The topic, topics, or topicsPattern option is used to configure information about the topic to be consumed. You must set a value for it. (The topics parameters refers to multiple topics separated by a comma (,), and the topicsPattern parameter is a Java regular expression that matches a number of topics.)
setStartFromLatest, setStartFromEarliest, setStartFromSpecificOffsets, or setStartFromSubscription: these parameters are used to configure the consumption mode. When the setStartFromSubscription consumption mode is configured, the checkpoint function must be enabled.

Example

StreamExecutionEnvironment see = StreamExecutionEnvironment.getExecutionEnvironment();
Properties props = new Properties();
props.setProperty("topic", "test-source-topic");
props.setProperty("partition.discovery.interval-millis", "5000");

FlinkPulsarSource<String> source = new FlinkPulsarSource<>(serviceUrl, adminUrl, new PulsarDeserializationSchemaWrapper(new SimpleStringSchema(),DataTypes.STRING()), props);

// or setStartFromLatest、setStartFromSpecificOffsets、setStartFromSubscription
source.setStartFromEarliest(); 

DataStream<String> stream = see.addSource(source);

// chain operations on dataStream of String and sink the output
// end method chaining

see.execute();

Sink

The Pulsar producer uses the FlinkPulsarSink instance. It allows to write record streams to one or more Pulsar topics.

Example

PulsarSerializationSchema<Person> pulsarSerialization = new PulsarSerializationSchemaWrapper.Builder<>(JsonSer.of(Person.class))
.usePojoMode(Person. class, RecordSchemaType.JSON)
.setTopicExtractor(person -> null)
.build();
FlinkPulsarSink<Person> sink = new FlinkPulsarSink(
  serviceUrl,
  adminUrl,
  Optional.of(topic),      // mandatory target topic or use `Optional.empty()` if sink to different topics for each record
  props,
  pulsarSerialization,
  PulsarSinkSemantic.AT_LEAST_ONCE);

stream.addSink(sink);

PulsarDeserializationSchema

PulsarDeserializationSchema is a connector-defined Flink DeserializationSchema wrapper that allows flexible manipulation of Pulsar messages.

PulsarDeserializationSchemaWrapper is a simple implementation of PulsarDeserializationSchema with two parameters: Flink DeserializationSchema and information about the decoded message type.

PulsarDeserializationSchemaWrapper(new SimpleStringSchema(),DataTypes.STRING())

Note
The DataTypes type comes from Flink's table-common module.

PulsarSerializationSchema

PulsarSerializationSchema is a wrapper for Flink SerializationSchema that provides more functionality. In most cases, users do not need to implement PulsarSerializationSchema by themselves. PulsarSerializationSchemaWrapper is provided to wrap a Flink SerializationSchema as PulsarSerializationSchema.

PulsarSerializationSchema uses the builder pattern and you can call setKeyExtractor or setTopicExtractor to extract the key and customize the target topic from each message.

In particular, since Pulsar maintains its own Schema information internally, our messages must be able to export SchemaInfo when they are written to Pulsar. The useSpecialMode, useAtomicMode, usePojoMode, and useRowMode methods help you quickly build the Schema information required for Pulsar. You must choose one of these four modes.

SpecialMode: specify the Schema<?> mode directly. Ensure that this Schema is compatible with the Flink SerializationSchema setting.
AtomicMode: For some atomic types, pass the type of AtomicDataType, such as DataTypes.INT(), which corresponds to Schema<Integer> in Pulsar.
PojoMode: you need to pass a custom class object and either JSON or Arvo Schema to specify how to build a composite type Schema, such as usePojoMode(Person.class, RecordSchemaType.JSON).
RowMode: in general, it is used for our internal Table&SQL API implementation.

Fault tolerance

With Flink's checkpoints being enabled, FlinkPulsarSink can provide at-least-once and exactly-once delivery guarantees.

In addition to enabling checkpoints for Flink, you should also configure setLogFailuresOnly(boolean) and setFlushOnCheckpoint(boolean) parameters.

Note
setFlushOnCheckpoint(boolean): by default, it is set to true. When it is enabled, writing to Pulsar records is performed at this checkpoint snapshotState. This ensures that all records before the checkpoint are written to Pulsar. And, at-least-once setting must also be enabled.

Table environment

The Pulsar Flink connector supports all the Table features, as listed below.

SQL and DDL
Catalog

SQL and DDL

The following section describes SQL configurations and DDL configurations.

SQL configurations

CREATE TABLE pulsar (
  `physical_1` STRING,
  `physical_2` INT,
  `eventTime` TIMESTAMP(3) METADATA,
  `properties` MAP<STRING, STRING> METADATA ,
  `topic` STRING METADATA VIRTUAL,
  `sequenceId` BIGINT METADATA VIRTUAL,
  `key` STRING ,
  `physical_3` BOOLEAN
) WITH (
  'connector' = 'pulsar',
  'topic' = 'persistent://public/default/topic82547611',
  'key.format' = 'raw',
  'key.fields' = 'key',
  'value.format' = 'avro',
  'service-url' = 'pulsar://localhost:6650',
  'admin-url' = 'http://localhost:8080',
  'scan.startup.mode' = 'earliest' 
)

INSERT INTO pulsar 
VALUES
 ('data 1', 1, TIMESTAMP '2020-03-08 13:12:11.123', MAP['k11', 'v11', 'k12', 'v12'], 'key1', TRUE),
 ('data 2', 2, TIMESTAMP '2020-03-09 13:12:11.123', MAP['k21', 'v21', 'k22', 'v22'], 'key2', FALSE),
 ('data 3', 3, TIMESTAMP '2020-03-10 13:12:11.123', MAP['k31', 'v31', 'k32', 'v32'], 'key3', TRUE)
 
SELECT * FROM pulsar

SQL supports configuring physical fields, calculated columns, watermark, METADATA and other features.

DDL configurations

Parameter	Default value	Description	Required or not
connector	null	Set the connector type. Available options are `pulsar` and `upsert-pulsar`.	Yes
topic	null	Set the input or output topic, use half comma for multiple and concatenate topics. Choose one with the topic-pattern.	No
topic-pattern	null	Use regular to get the matching topic.	No
service-url	null	Set the Pulsar broker service address.	Yes
admin-url	null	Set the Pulsar administration service address.	Yes
scan.startup.mode	latest	COnfigure the Source's startup mode,. Available options are `earliest`, `latest`, `external-subscription`, and `specific-offsets`.	No
scan.startup.specific-offsets	null	This parameter is required when the `specific-offsets` parameter is specified.	No
scan.startup.sub-name	null	This parameter is required for the External subscription mode .	No
discovery topic interval	null	Set the time interval for partition discovery, in unit of milliseconds.	No
sink.message-router	key-hash	Set the routing method for writing messages to the Pulsar partition. Available options are `key-hash`, `round-robin`, and `custom MessageRouter`.	No
sink.semantic	at-least-once	The Sink writes the assurance level of the message. Available options are `at-least-once`, `exactly-once`, and `none`.	No
properties	empty	Set Pulsar's optional configurations, in a format of `properties.key='value'`. For details, see Configuration parameters.	No
key.format	null	Set the key-based serialization format for Pulsar messages. Available options are `No format`, `optional raw`, `Avro`, `JSON`, etc.	No
key.fields	null	The SQL definition field to be used when serializing Key, multiple by half comma `,` concatenated.	No
key.fields-prefix	null	Define a custom prefix for all fields in the key format to avoid name conflicts with fields in the value format. By default, the prefix is empty. If a custom prefix is defined, the Table schema and `key.fields` are used.	No
format or value.format	null	Set the name with a prefix. When constructing data types in the key format, the prefix is removed and non-prefixed names are used within the key format. Pulsar message value serialization format, support JSON, Avro, etc. For more information, see the Flink format.	Yes
value.fields-include	ALL	The Pulsar message value contains the field policy, optionally ALL, and EXCEPT_KEY.	No

Metadata configurations

The METADATA flag is used to read and write metadata in Pulsar messages. The support list is as follows.

Note
The R/W column defines whether a metadata field is readable (R) and/or writable (W). Read-only columns must be declared VIRTUAL to exclude them during an INSERT INTO operation.

Key	Data Type	Description	R/W
topic	STRING NOT NULL	Topic name of the Pulsar message.	R
messageId	BYTES NOT NULL	Message ID of the Pulsar message.	R
sequenceId	BIGINT NOT NULL	sequence ID of the Pulsar message.	R
publishTime	TIMESTAMP(3) WITH LOCAL TIME ZONE NOT NULL	Publishing time of the Pulsar message.	R
eventTime	TIMESTAMP(3) WITH LOCAL TIME ZONE NOT NULL	Generation time of the Pulsar message.	R/W
properties	MAP<STRING, STRING> NOT NULL	Extensions information of the Pulsar message.	R/W

Catalog

Flink always searches for tables, views and UDFs in the current catalog and database. To use the Pulsar Catalog and treat the topic in Pulsar as a table in Flink, you should use the pulsarcatalog that has been defined in ./conf/sql-client-defaults.yaml in pulsarcatalog.

tableEnv.useCatalog("pulsarcatalog")
tableEnv.useDatabase("public/default")
tableEnv.scan("topic0")

Flink SQL> USE CATALOG pulsarcatalog;
Flink SQL> USE `public/default`;
Flink SQL> select * from topic0;

The following configuration is optional in the environment file, or it can be overridden in the SQL client session using the SET command.

Option	Value	Default	Description
`default-database`	Default database name	public/default	When using the Pulsar catalog, the topic in Pulsar is treated as a table in Flink. Therefore, `database` is another name for `tenant/namespace`. The database is the base path for table lookups or creation.
`table-default-partitions`	Default topic partition	5	When using the Pulsar catalog, the topic in Pulsar is treated as a table in Flink. The size of the partition is set when creating the topic.

For more details, see DDL configurations.

Note
In Catalog, you cannot delete tenant/namespace or topic.

Advanced features

This section describes advanced features supported by Pulsar Flink connector.

Pulsar primitive types

Pulsar provides some basic native types. To use these native types, you can support them in the following ways.

Stream API environment

PulsarPrimitiveSchema is an implementation of the PulsarDeserializationSchema and PulsarSerializationSchema interfaces.

You can create the required instance in a similar way new PulsarSerializationSchema(String.class).

Table environment

We have created a new Flink format component called atomic that you can use in SQL format. In Source, it translates the Pulsar native type into only one column of RowData. In Sink, it translates the first column of RowData into the Pulsar native type and writes it to Pulsar.

Upsert Pulsar

There is an increasing demand for Upsert mode message queues for three main reasons.

Interpret the Pulsar topic as a changelog stream, which interprets records with keys as Upsert events.
As part of the real-time pipeline, multiple streams are connected for enrichment and the results are stored in the Pulsar topic for further computation. However, the results may contain updated events.
As part of the real-time pipeline, the data stream is aggregated and the results are stored in Pulsar Topic for further computation. However, the results may contain updated events.

Based on these requirements, we support Upsert Pulsar. With this feature, users can read data from and write data to Pulsar topics in an Upsert fashion.

In the SQL DDL definition, you can set the connector to upsert-pulsar to use the Upsert Pulsar connector.

In terms of configuration, the primary key of the Table must be specified, and key.fields cannot be used.

As a source, the Upsert Pulsar connector produces changelog streams, where each data record represents an update or deletion event. More precisely, the value in a data record is interpreted as a UPDATE of the last value of the same key, if this key exists (If the corresponding key does not exist, the UPDATE is considered as an INSERT.). Using the table analogy, data records in the changelog stream are interpreted as UPSERT, also known as INSERT/UPDATE, because any existing row with the same key is overwritten. Also, a message with a null value is treated as a DELETE message.

As a sink, the Upsert Pulsar connector can consume changelog streams. It writes INSERT/UPDATE_AFTER data as normal Pulsar messages and writes DELETE data as Pulsar messages with null value (It indicates that key of the message is deleted). Flink partitions the data based on the value of the primary key so that the messages on the primary key are ordered. And, UPDATE/DELETE messages with the same primary key fall in the same partition.

Key-Shared subscription mode

In some scenarios, users need messages to be strictly guaranteed message order to ensure correct business processing. Usually, in the case of strictly order-preserving messages, only one consumer can consume messages at the same time to guarantee the order. This results in a significant reduction in message throughput. Pulsar designs the Key-Shared subscription mode for such scenarios by adding keys to messages and routing messages with the same Key Hash to the same messenger, which ensures message order and improves throughput.

Pulsar Flink connector supports this feature the as well. This feature can be enabled by configuring the enable-key-hash-range=true parameter. When enabled, the range of Key Hash processed by each consumer is divided based on the parallelism of the task.

Configuration parameters

This parameter corresponds to the FlinkPulsarSource in StreamAPI, the Properties object in the FlinkPulsarSink construction parameter, and the configuration properties parameter in Table mode.

Parameter	Default value	Description	Effective range
topic	null	Pulsar topic	source
topics	null	Multiple Pulsar topics connected by half-width commas	source
topicspattern	null	Multiple Pulsar topics with more Java regular matching	source
partition.discovery.interval-millis	-1	Automatically discover added or removed topics, in unit of milliseconds. If the value is set to -1, it indicates that means not open.	source
clientcachesize	100	Set the number of cached Pulsar clients.	source, sink
auth-params	null	Set the authentication parameters for Pulsar clients.	source, sink
auth-plugin-classname	null	Set the authentication class name for Pulsar clients.	source, sink
flushoncheckpoint	true	Write a message to Pulsar topics.	sink
failonwrite	false	When sink error occurs, continue to confirm the message.	sink
polltimeoutms	120000	Set the timeout for waiting to get the next message, in unit of milliseconds.	source
failondataloss	true	When data is lost, the operation fails.	source
commitmaxretries	3	Set the maximum number of retries when an offset is set for Pulsar messages.	source
scan.startup.mode	null	Set the earliest, latest, and the position where subscribers consume news,. It is a required parameter.	source
enable-key-hash-range	false	Enable the Key-Shared subscription mode.	source
pulsar.reader.*		For details about Pulsar reader configurations, see Pulsar reader.	source
pulsar.reader.subscriptionRolePrefix	flink-pulsar-	When no subscriber is specified, the prefix of the subscriber name is automatically created.	source
pulsar.reader.receiverQueueSize	1000	Set the receive queue size.	source
pulsar.producer.*		For details about Pulsar producer configurations, see Pulsar producer.	Sink
pulsar.producer.sendTimeoutMs	30000	Set the timeout for sending a message, in unit of milliseconds.	Sink
pulsar.producer.blockIfQueueFull	false	The Pulsar producer writes messages. When the queue is full, the method is blocked instead of an exception is thrown.	Sink

pulsar.reader.* and pulsar.producer.* specify more detailed configuration of the Pulsar behavior. The asterisk sign (*) is replaced by the configuration name in Pulsar. For details, see Pulsar reader and Pulsar producer.

In the DDL statement, the sample which is similar to the following is used.

'properties.pulsar.reader.subscriptionRolePrefix' = 'pulsar-flink-',
'properties.pulsar.producer.sendTimeoutMs' = '30000',

Authentication configuration

For Pulsar instances configured with authentication, the Pulsar Flink connector can be configured in a similar as the regular Pulsar client.

For FlinkPulsarSource and FlinkPulsarSink, you can use one of the following ways to set up authentication.

Set the Properties parameter.

props.setProperty(PulsarOptions.AUTH_PLUGIN_CLASSNAME_KEY, "org.apache.pulsar.client.impl.auth.AuthenticationToken");
props.setProperty(PulsarOptions.AUTH_PARAMS_KEY, "token:abcdefghijklmn");

Set the ClientConfigurationData parameter, which has a higher priority than the Properties parameter.

ClientConfigurationData conf = new ClientConfigurationData();
conf.setServiceUrl(serviceUrl);
conf.setAuthPluginClassName(className);
conf.setAuthParams(params);

For details about authentication configuration, see Pulsar Security.

Name		Name	Last commit message	Last commit date
Latest commit History 217 Commits
.github		.github
doc		doc
managed-ledger-shaded		managed-ledger-shaded
pulsar-flink-connector		pulsar-flink-connector
tools		tools
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
build.sh		build.sh
get-version.sh		get-version.sh
pom.xml		pom.xml
set-pulsar-version.sh		set-pulsar-version.sh
set-version.sh		set-version.sh

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Pulsar Flink Connector

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Maven projects

Gradle projects

Build Pulsar Flink connector

Deploy Pulsar Flink connector

Client library

Scala REPL

SQL client

Usage

Stream environment

Source

Sink

PulsarDeserializationSchema

PulsarSerializationSchema

Fault tolerance

Table environment

SQL and DDL

SQL configurations

DDL configurations

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Stream API environment

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Configuration parameters

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Pulsar Flink Connector

Prerequisites

Basic information

Client

Maven projects

Gradle projects

Build Pulsar Flink connector

Deploy Pulsar Flink connector

Client library

Scala REPL

SQL client

Usage

Stream environment

Source

Sink

PulsarDeserializationSchema

PulsarSerializationSchema

Fault tolerance

Table environment

SQL and DDL

SQL configurations

DDL configurations

Metadata configurations

Catalog

Advanced features

Pulsar primitive types

Stream API environment

Table environment

Upsert Pulsar

Key-Shared subscription mode

Configuration parameters

Authentication configuration

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