ActiveMQ Source Connector for Confluent Cloud
The fully-managed ActiveMQ Source connector for Confluent Cloud connector reads messages from an ActiveMQ broker and writes the messages to an Apache Kafka® topic.
Note
This Quick Start is for the fully-managed Confluent Cloud connector. If you are installing the connector locally for Confluent Platform, see ActiveMQ Source Connector for Confluent Platform.
If you require private networking for fully-managed connectors, make sure to set up the proper networking beforehand. For more information, see Manage Networking for Confluent Cloud Connectors.
Features
The ActiveMQ Source connector includes the following features:
At least once delivery: The connector guarantees that records are delivered at least once to the Kafka topic.
Supports multiple tasks: The connector supports running one or more tasks. More tasks may improve performance.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.
Limitations
Be sure to review the following information.
For connector limitations, see ActiveMQ Source Connector limitations.
If you plan to use one or more Single Message Transforms (SMTs), see SMT Limitations.
If you plan to use Confluent Cloud Schema Registry, see Schema Registry Enabled Environments.
Quick Start
Use this quick start to get up and running with the Confluent Cloud ActiveMQ source connector.
- Prerequisites
Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud.
Access to an ActiveMQ message broker.
The Confluent CLI installed and configured for the cluster. See Install the Confluent CLI.
Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). See Schema Registry Enabled Environments for additional information.
For networking considerations, see Networking and DNS. To use a set of public egress IP addresses, see Public Egress IP Addresses for Confluent Cloud Connectors.
Kafka cluster credentials. The following lists the different ways you can provide credentials.
Enter an existing service account resource ID.
Create a Confluent Cloud service account for the connector. Make sure to review the ACL entries required in the service account documentation. Some connectors have specific ACL requirements.
Create a Confluent Cloud API key and secret. To create a key and secret, you can use confluent api-key create or you can autogenerate the API key and secret directly in the Cloud Console when setting up the connector.
Using the Confluent Cloud Console
Step 1: Launch your Confluent Cloud cluster
To create and launch a Kafka cluster in Confluent Cloud, see Create a kafka cluster in Confluent Cloud.
Step 2: Add a connector
In the left navigation menu, click Connectors. If you already have connectors in your cluster, click + Add connector.
Step 3: Select your connector
Click the ActiveMQ Source connector card.

Step 4: Enter the connector details
Note
Make sure you have all your prerequisites completed.
An asterisk ( * ) designates a required entry.
At the Add ActiveMQ Source Connector screen, complete the following:
Select the topic you want to send data to from the Topics list. To create a new topic, click +Add new topic.
Select the way you want to provide Kafka Cluster credentials. You can choose one of the following options:
My account: This setting allows your connector to globally access everything that you have access to. With a user account, the connector uses an API key and secret to access the Kafka cluster. This option is not recommended for production.
Service account: This setting limits the access for your connector by using a service account. This option is recommended for production.
Use an existing API key: This setting allows you to specify an API key and a secret pair. You can use an existing pair or create a new one. This method is not recommended for production environments.
Note
Freight clusters support only service accounts for Kafka authentication.
Click Continue.
Enter the ActiveMQ connection ans session details:
ActiveMQ URL: The URL of the ActiveMQ broke. An ActiveMQ broker URL is similar to
tcp://<remotehost>:61616.ActiveMQ Username: The username to use when connecting to ActiveMQ.
ActiveMQ Password: The password to use when connecting to ActiveMQ.
Click Continue.
Select the output record value format (data going to the Kafka topic): AVRO, JSON, JSON_SR (JSON Schema), or PROTOBUF. Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON Schema, or Protobuf). See Schema Registry Enabled Environments for additional information.
Enter the Destination Name: The name of the JMS destination (queue or topic) to read from.
Enter the Destination Type: The type of JMS destination, which is either
queueortopic.Show advanced configurations
Schema context: Select a schema context to use for this connector, if using a schema-based data format. This property defaults to the Default context, which configures the connector to use the default schema set up for Schema Registry in your Confluent Cloud environment. A schema context allows you to use separate schemas (like schema sub-registries) tied to topics in different Kafka clusters that share the same Schema Registry environment. For example, if you select a non-default context, a Source connector uses only that schema context to register a schema and a Sink connector uses only that schema context to read from. For more information about setting up a schema context, see What are schema contexts and when should you use them?.
Auto-restart policy
Enable Connector Auto-restart: Control the auto-restart behavior of the connector and its task in the event of user-actionable errors. Defaults to
true, enabling the connector to automatically restart in case of user-actionable errors. Set this property tofalseto disable auto-restart for failed connectors. In such cases, you would need to manually restart the connector.
Batch Size: The maximum number of records that the connector can read from the broker before it writes to Kafka. The connector task holds these records until they are acknowledged in Kafka which may affect memory usage. Acceptable values are
1to2048.Unacknowledged Messages Limit: The maximum number of messages (per connector task) that can be received from a broker and written to Kafka before Kafka acknowledges that the messages have been received. This is the maximum number of JMS messages the task may duplicate in Kafka, if the connector task fails and is restarted. This value is typically set larger than Batch Size. If you enter a smaller value than the Batch Size value, the batch size is limited to the value used here.
Maximum time to wait…: The maximum amount of time in milliseconds (ms) for a task to build a batch. The batch is closed and sent to Kafka at the end of this time. The batch is sent to Kafka even if less messages are present than the specified batch size. This can help limit connector lag when the JMS queue or topic has a lower throughput. Defaults to
60000ms (60 seconds).Character Encoding: The character encoding to use while receiving the message. Defaults to
UTF-8.Durable Subscription: Whether the connector task subscription to the JMS topic is durable or not.
Subscription Name: The name of the JMS subscription. Required for durable subscriptions. This option is applicable only for JMS topics.
Message Selector: The JMS message selector that should be applied to messages in the destination.
Transforms
Single Message Transforms: To add a new SMT, see Add transforms. For more information about unsupported SMTs, see Unsupported transformations.
See Configuration Properties for all property values and definitions.
Click Continue.
Based on the number of topic partitions you select, you will be provided with a recommended number of tasks.
To change the number of tasks, use the Range Slider to select the desired number of tasks.
Click Continue.
Verify the connection details by previewing the running configuration.
Tip
For information about previewing your connector output, see Data Previews for Confluent Cloud Connectors.
Once you’ve validated that the properties are configured to your satisfaction, click Launch.
The status for the connector should go from Provisioning to Running.
Step 5: Check the Kafka topic
After the connector is running, verify messages are populating your Kafka topic.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.
Using the Confluent CLI
Complete the following steps to set up and run the connector using the Confluent CLI.
Note
Make sure you have all your prerequisites completed.
Step 1: List the available connectors
Enter the following command to list available connectors:
confluent connect plugin list
Step 2: List the connector configuration properties
Enter the following command to show the connector configuration properties:
confluent connect plugin describe <connector-plugin-name>
The command output shows the required and optional configuration properties.
Step 3: Create the connector configuration file
Create a JSON file that contains the connector configuration properties. The following example shows the required connector properties.
{
"connector.class": "ActiveMQSource",
"name": "ActiveMQSource_0",
"kafka.auth.mode": "KAFKA_API_KEY",
"kafka.api.key": "<my-kafka-api-key>",
"kafka.api.secret": "<my-kafka-api-secret>",
"kafka.topic" : "topic_0",
"output.data.format" : "AVRO",
"activemq.url" : "tcp://<remotehost>:61616",
"activemq.username" : "<username>",
"activemq.password" : "<password>",
"jms.destination.name" : "<JMS-queue-or-topic-name>",
"tasks.max" : "1"
}
Note the following property definitions:
"name": Sets a name for your new connector."connector.class": Identifies the connector plugin name.
"kafka.auth.mode": Identifies the connector authentication mode you want to use. There are two options:SERVICE_ACCOUNTorKAFKA_API_KEY(the default). To use an API key and secret, specify the configuration propertieskafka.api.keyandkafka.api.secret, as shown in the example configuration (above). To use a service account, specify the Resource ID in the propertykafka.service.account.id=<service-account-resource-ID>. To list the available service account resource IDs, use the following command:confluent iam service-account list
For example:
confluent iam service-account list Id | Resource ID | Name | Description +---------+-------------+-------------------+------------------- 123456 | sa-l1r23m | sa-1 | Service account 1 789101 | sa-l4d56p | sa-2 | Service account 2
"kafka.topic": The Kafka topic name where you want data sent."output.data.format": Options are AVRO, JSON, JSON_SR, and PROTOBUF. Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). See Schema Registry Enabled Environments for additional information."activemq.url": The URL of the ActiveMQ broker. An ActiveMQ broker URL is similar totcp://<remotehost>:61616."jms.destination.name": The name of the JMS destinationqueueortopicname to read from."tasks.max": Enter the number of tasks in use by the connector. The connector supports multiple tasks. More tasks may improve performance.
Single Message Transforms: See the Single Message Transforms (SMT) documentation for details about adding SMTs using the CLI.
See Configuration Properties for all property values and definitions.
Step 4: Load the properties file and create the connector
Enter the following command to load the configuration and start the connector:
confluent connect cluster create --config-file <file-name>.json
For example:
confluent connect cluster create --config-file activemq-source.json
Example output:
Created connector ActiveMQSource_0 lcc-ix4dl
Step 5: Check the connector status
Enter the following command to check the connector status:
confluent connect plugin list
Example output:
ID | Name | Status | Type
+-----------+---------------------+---------+-------+
lcc-ix4dl | ActiveMQSource_0 | RUNNING | source
Step 6: Check the results on the broker.
After the connector is running, verify messages are populating your Kafka topic.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.
Configuration Properties
Use the following configuration properties with the fully-managed connector. For self-managed connector property definitions and other details, see the connector docs in Self-managed connectors for Confluent Platform.
How should we connect to your data?
nameSets a name for your connector.
Type: string
Valid Values: A string at most 64 characters long
Importance: high
Kafka Cluster credentials
kafka.auth.modeKafka Authentication mode. It can be one of KAFKA_API_KEY or SERVICE_ACCOUNT. It defaults to KAFKA_API_KEY mode.
Type: string
Default: KAFKA_API_KEY
Valid Values: KAFKA_API_KEY, SERVICE_ACCOUNT
Importance: high
kafka.api.keyKafka API Key. Required when kafka.auth.mode==KAFKA_API_KEY.
Type: password
Importance: high
kafka.service.account.idThe Service Account that will be used to generate the API keys to communicate with Kafka Cluster.
Type: string
Importance: high
kafka.api.secretSecret associated with Kafka API key. Required when kafka.auth.mode==KAFKA_API_KEY.
Type: password
Importance: high
Which topic do you want to send data to?
kafka.topicIdentifies the topic name to write the data to.
Type: string
Importance: high
Schema Config
schema.context.nameAdd a schema context name. A schema context represents an independent scope in Schema Registry. It is a separate sub-schema tied to topics in different Kafka clusters that share the same Schema Registry instance. If not used, the connector uses the default schema configured for Schema Registry in your Confluent Cloud environment.
Type: string
Default: default
Importance: medium
Output messages
output.data.formatSets the output Kafka record value format. Valid entries are AVRO, JSON_SR, PROTOBUF, or JSON. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF
Type: string
Default: JSON
Importance: high
ActiveMQ Connection
activemq.urlThe URL of the ActiveMQ broker.
Type: string
Importance: high
activemq.usernameThe username to use when connecting to ActiveMQ.
Type: string
Importance: high
activemq.passwordThe password to use when connecting to ActiveMQ.
Type: password
Importance: high
ActiveMQ Session
jms.destination.nameThe name of the JMS destination (queue or topic) to read from.
Type: string
Importance: high
jms.destination.typeThe type of JMS destination, which is either queue or topic.
Type: string
Default: queue
Importance: high
batch.sizeThe maximum number of records that a connector task may read from the JMS broker before writing to Kafka. The task holds these records until they are acknowledged in Kafka, so this may affect memory usage.
Type: int
Valid Values: [1,…,2048]
Importance: medium
max.pending.messagesThe maximum number of messages per task that can be received from JMS brokers and produced to Kafka before the task acknowledges the JMS session/messages. If the task fails and is restarted, this is the maximum number of JMS messages the task may duplicate in Kafka. This is typically set larger than
batch.size. A smaller value thanbatch.sizelimits the size of the batches.Type: int
Importance: medium
max.poll.durationThe maximum amount of time each task can build a batch. The batch is closed and sent to Kafka if not enough messages are read during the time allotted. This helps limit connector lag when the JMS queue/topic has a lower throughput.
Type: int
Default: 60000
Valid Values: [1,…,120000]
Importance: medium
character.encodingThe character encoding to use while receiving the message.
Type: string
Default: UTF-8
Importance: medium
jms.subscription.durableWhether the subscription of the connector tasks to a JMS topic is durable or not. Durable subscriptions require a subscription name to be set via
jms.subscription.name.Type: boolean
Default: false
Importance: medium
jms.subscription.nameThe name of the JMS subscription. Supported only in durable subscriptions (
jms.subscription.durable = true) and is applicable only to JMS topics.Type: string
Importance: medium
jms.message.selectorThe message selector that should be applied to messages in the destination.
Type: string
Importance: medium
Number of tasks for this connector
tasks.maxMaximum number of tasks for the connector.
Type: int
Valid Values: [1,…]
Importance: high
Additional Configs
header.converterThe converter class for the headers. This is used to serialize and deserialize the headers of the messages.
Type: string
Importance: low
producer.override.compression.typeThe compression type for all data generated by the producer. Valid values are none, gzip, snappy, lz4, and zstd.
Type: string
Importance: low
producer.override.linger.msThe producer groups together any records that arrive in between request transmissions into a single batched request. More details can be found in the documentation: https://docs.confluent.io/platform/current/installation/configuration/producer-configs.html#linger-ms.
Type: long
Valid Values: [100,…,1000]
Importance: low
value.converter.allow.optional.map.keysAllow optional string map key when converting from Connect Schema to Avro Schema. Applicable for Avro Converters.
Type: boolean
Importance: low
value.converter.auto.register.schemasSpecify if the Serializer should attempt to register the Schema.
Type: boolean
Importance: low
value.converter.connect.meta.dataAllow the Connect converter to add its metadata to the output schema. Applicable for Avro Converters.
Type: boolean
Importance: low
value.converter.enhanced.avro.schema.supportEnable enhanced schema support to preserve package information and Enums. Applicable for Avro Converters.
Type: boolean
Importance: low
value.converter.enhanced.protobuf.schema.supportEnable enhanced schema support to preserve package information. Applicable for Protobuf Converters.
Type: boolean
Importance: low
value.converter.flatten.unionsWhether to flatten unions (oneofs). Applicable for Protobuf Converters.
Type: boolean
Importance: low
value.converter.generate.index.for.unionsWhether to generate an index suffix for unions. Applicable for Protobuf Converters.
Type: boolean
Importance: low
value.converter.generate.struct.for.nullsWhether to generate a struct variable for null values. Applicable for Protobuf Converters.
Type: boolean
Importance: low
value.converter.int.for.enumsWhether to represent enums as integers. Applicable for Protobuf Converters.
Type: boolean
Importance: low
value.converter.latest.compatibility.strictVerify latest subject version is backward compatible when use.latest.version is true.
Type: boolean
Importance: low
value.converter.object.additional.propertiesWhether to allow additional properties for object schemas. Applicable for JSON_SR Converters.
Type: boolean
Importance: low
value.converter.optional.for.nullablesWhether nullable fields should be specified with an optional label. Applicable for Protobuf Converters.
Type: boolean
Importance: low
value.converter.optional.for.proto2Whether proto2 optionals are supported. Applicable for Protobuf Converters.
Type: boolean
Importance: low
value.converter.scrub.invalid.namesWhether to scrub invalid names by replacing invalid characters with valid characters. Applicable for Avro and Protobuf Converters.
Type: boolean
Importance: low
value.converter.use.latest.versionUse latest version of schema in subject for serialization when auto.register.schemas is false.
Type: boolean
Importance: low
value.converter.use.optional.for.nonrequiredWhether to set non-required properties to be optional. Applicable for JSON_SR Converters.
Type: boolean
Importance: low
value.converter.wrapper.for.nullablesWhether nullable fields should use primitive wrapper messages. Applicable for Protobuf Converters.
Type: boolean
Importance: low
value.converter.wrapper.for.raw.primitivesWhether a wrapper message should be interpreted as a raw primitive at root level. Applicable for Protobuf Converters.
Type: boolean
Importance: low
errors.toleranceUse this property if you would like to configure the connector’s error handling behavior. WARNING: This property should be used with CAUTION for SOURCE CONNECTORS as it may lead to dataloss. If you set this property to ‘all’, the connector will not fail on errant records, but will instead log them (and send to DLQ for Sink Connectors) and continue processing. If you set this property to ‘none’, the connector task will fail on errant records.
Type: string
Default: none
Importance: low
key.converter.key.subject.name.strategyHow to construct the subject name for key schema registration.
Type: string
Default: TopicNameStrategy
Importance: low
value.converter.decimal.formatSpecify the JSON/JSON_SR serialization format for Connect DECIMAL logical type values with two allowed literals:
BASE64 to serialize DECIMAL logical types as base64 encoded binary data and
NUMERIC to serialize Connect DECIMAL logical type values in JSON/JSON_SR as a number representing the decimal value.
Type: string
Default: BASE64
Importance: low
value.converter.flatten.singleton.unionsWhether to flatten singleton unions. Applicable for Avro and JSON_SR Converters.
Type: boolean
Default: false
Importance: low
value.converter.ignore.default.for.nullablesWhen set to true, this property ensures that the corresponding record in Kafka is NULL, instead of showing the default column value. Applicable for AVRO,PROTOBUF and JSON_SR Converters.
Type: boolean
Default: false
Importance: low
value.converter.reference.subject.name.strategySet the subject reference name strategy for value. Valid entries are DefaultReferenceSubjectNameStrategy or QualifiedReferenceSubjectNameStrategy. Note that the subject reference name strategy can be selected only for PROTOBUF format with the default strategy being DefaultReferenceSubjectNameStrategy.
Type: string
Default: DefaultReferenceSubjectNameStrategy
Importance: low
value.converter.replace.null.with.defaultWhether to replace fields that have a default value and that are null to the default value. When set to true, the default value is used, otherwise null is used. Applicable for JSON Converter.
Type: boolean
Default: true
Importance: low
value.converter.schemas.enableInclude schemas within each of the serialized values. Input messages must contain schema and payload fields and may not contain additional fields. For plain JSON data, set this to false. Applicable for JSON Converter.
Type: boolean
Default: false
Importance: low
value.converter.value.subject.name.strategyDetermines how to construct the subject name under which the value schema is registered with Schema Registry.
Type: string
Default: TopicNameStrategy
Importance: low
Auto-restart policy
auto.restart.on.user.errorEnable connector to automatically restart on user-actionable errors.
Type: boolean
Default: true
Importance: medium
Next Steps
For an example that shows fully-managed Confluent Cloud connectors in action with Confluent Cloud for Apache Flink, see the Cloud ETL Demo. This example also shows how to use Confluent CLI to manage your resources in Confluent Cloud.
