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 is a Quick Start for the fully-managed connector. If you are installing the connector locally for Confluent Platform, see ActiveMQ Source Connector for Confluent Platform.

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 Managed and Custom Connectors 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 (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, DNS, and service endpoints. 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¶

See the Quick Start for Confluent Cloud for installation instructions.

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.

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 queue or topic.
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?.
- 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 1 to 2048.
- 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 60000 ms (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 and Predicates: See the Single Message Transforms (SMT) documentation for details.
See Configuration Properties for all property values and definitions.
Click Continue.

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 Managed and Custom Connectors 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_ACCOUNT or KAFKA_API_KEY (the default). To use an API key and secret, specify the configuration properties kafka.api.key and kafka.api.secret, as shown in the example configuration (above). To use a service account, specify the Resource ID in the property kafka.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 to tcp://<remotehost>:61616.
"jms.destination.name": The name of the JMS destination queue or topic name 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 Managed and Custom Connectors 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?¶

name

Sets a name for your connector.

Type: string
Valid Values: A string at most 64 characters long
Importance: high

Kafka Cluster credentials¶

kafka.auth.mode

Kafka 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.key

Kafka API Key. Required when kafka.auth.mode==KAFKA_API_KEY.

Type: password
Importance: high

kafka.service.account.id

The Service Account that will be used to generate the API keys to communicate with Kafka Cluster.

Type: string
Importance: high

kafka.api.secret

Secret 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.topic

Identifies the topic name to write the data to.

Type: string
Importance: high

Schema Config¶

schema.context.name

Add 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.format

Sets 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
Importance: high

ActiveMQ Connection¶

activemq.url

The URL of the ActiveMQ broker.

Type: string
Importance: high

activemq.username

The username to use when connecting to ActiveMQ.

Type: string
Importance: high

activemq.password

The password to use when connecting to ActiveMQ.

Type: password
Importance: high

ActiveMQ Session¶

jms.destination.name

The name of the JMS destination (queue or topic) to read from.

Type: string
Importance: high

jms.destination.type

The type of JMS destination, which is either queue or topic.

Type: string
Default: queue
Importance: high

batch.size

The 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.messages

The 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 than batch.size limits the size of the batches.

Type: int
Importance: medium

max.poll.duration

The 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.encoding

The character encoding to use while receiving the message.

Type: string
Default: UTF-8
Importance: medium

jms.subscription.durable

Whether 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.name

The 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.selector

The message selector that should be applied to messages in the destination.

Type: string
Importance: medium

Number of tasks for this connector¶

tasks.max

Maximum number of tasks for the connector.

Type: int
Valid Values: [1,…]
Importance: high

Next Steps¶

For an example that shows fully-managed Confluent Cloud connectors in action with Confluent Cloud ksqlDB, see the Cloud ETL Demo. This example also shows how to use Confluent CLI to manage your resources in Confluent Cloud.