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 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 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.
- 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¶
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 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 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.
- 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.
- ActiveMQ URL: The URL of the ActiveMQ broke. An ActiveMQ broker
URL is similar to
- 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
ortopic
.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
to2048
.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.
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 Confluent Cloud Connector Data Previews.
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 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
orKAFKA_API_KEY
(the default). To use an API key and secret, specify the configuration propertieskafka.api.key
andkafka.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 destinationqueue
ortopic
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 thanbatch.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.