# ActiveMQ Source Connector for Confluent Cloud The fully managed ActiveMQ Source connector for Confluent Cloud connector reads messages from an [ActiveMQ broker](https://activemq.apache.org/) 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](https://docs.confluent.io/kafka-connectors/activemq-source/current/). * 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](networking/internet-resource.md#clusters-connect-cloud). ## 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. * **Supports ActiveMQ Artemis**: The connector supports [ActiveMQ Artemis](https://activemq.apache.org/components/artemis/) over the default Artemis protocol. It has been tested against open source ActiveMQ Artemis (version 2.40.0) and Red Hat AMQ Broker (based on ActiveMQ Artemis, version 2.33.0). For more information and examples to use with the Confluent Cloud API for Connect, see the [Confluent Cloud API for Connect Usage Examples](connect-api-section.md#ccloud-connect-api) section. ## Limitations Be sure to review the following information. * For connector limitations, see [ActiveMQ Source Connector](limits.md#cc-activemq-source-limits) limitations. * If you plan to use one or more Single Message Transformations (SMTs), see [SMT Limitations](single-message-transforms.md#cc-single-message-transforms-limitations). ## 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](https://www.confluent.io/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](https://docs.confluent.io/confluent-cli/current/install.html). - [Schema Registry](../get-started/schema-registry.md#cloud-sr-config) must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). - For networking considerations, see [Networking and DNS](overview.md#connect-internet-access-resources). To use a set of public egress IP addresses, see [Public Egress IP Addresses for Confluent Cloud Connectors](static-egress-ip.md#cc-static-egress-ips).
- Kafka cluster credentials. The following lists the different ways you can provide credentials. - Enter an existing [service account](service-account.md#s3-cloud-service-account) resource ID. - Create a Confluent Cloud [service account](service-account.md#s3-cloud-service-account) for the connector. Make sure to review the ACL entries required in the [service account documentation](service-account.md#s3-cloud-service-account). 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](https://docs.confluent.io/confluent-cli/current/command-reference/api-key/confluent_api-key_create.html) *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](../get-started/index.md#cloud-create-kafka-cluster). #### 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](#cc-activemq-source-prereqs) completed. * An asterisk ( \* ) designates a required entry. At the **Add ActiveMQ Source Connector** screen, complete the following: ### Topic selection Select the topic you want to send data to from the **Topics** list. To create a new topic, click **+Add new topic**. ### Kafka access 1. 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](service-account.md#s3-cloud-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. 2. Click **Continue**. ### Authentication 1. Configure the authentication properties: **ActiveMQ Connection** - **ActiveMQ URL**: The URL of the ActiveMQ broker. An ActiveMQ broker URL is similar to `tcp://:61616`. - **ActiveMQ Username**: The username to use when connecting to ActiveMQ. - **ActiveMQ Password**: The password to use when connecting to ActiveMQ. 2. Click **Continue**. ### Configuration **Output messages** - **Select output record value format**: Select the output record value format (data going to the Kafka topic). Valid entries are AVRO, JSON, JSON_SR (JSON Schema), or PROTOBUF. [Schema Registry](../get-started/schema-registry.md#cloud-sr-config) must be enabled to use a Schema Registry-based format (for example, Avro, JSON Schema, or Protobuf). **ActiveMQ Session** - **Destination Name**: The name of the JMS destination (queue or topic) to read from. - **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?](../sr/faqs-cc.md#faq-schema-contexts). **Additional Configs** - **Value Converter Decimal Format**: Specifies the `JSON` or `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 `DECIMAL` logical type values in `JSON` or `JSON_SR` as a number representing the decimal value. - **Value Converter Replace Null With Default**: Specifies whether to replace fields that have a default value and that are null to the default value. When set to `true`, the connector uses the default value; otherwise, it uses `null`. Applies to the `JSON` converter. - **Key Converter Schema ID Serializer**: The class name of the schema ID serializer for keys. This is used to serialize schema IDs in the message headers. - **Value Converter Reference Subject Name Strategy**: Sets the subject reference name strategy for values. Valid entries are `DefaultReferenceSubjectNameStrategy` or `QualifiedReferenceSubjectNameStrategy`. You can use this strategy only with `PROTOBUF` format; the default strategy is `DefaultReferenceSubjectNameStrategy`. - **Value Converter Schemas Enable**: Includes schema within each of the serialized values. Input messages must contain `schema` and `payload` fields and must not contain additional fields. For plain `JSON` data, set this to `false`. Applies to the `JSON` converter. - **Errors Tolerance**: Use this property to configure the connector’s error handling behavior. #### WARNING Use this property with caution for sink connectors, as it can lead to data loss. If you set this property to `all`, the connector does not fail on errant records, but logs them (and sends to DLQ for sink connectors) and continues processing. If you set this property to `none`, the connector task fails on errant records. - **Value Converter Connect Meta Data**: Enables the Connect converter to add its metadata to the output schema. Applies to Avro converters. - **Value Converter Value Subject Name Strategy**: Determines how to construct the subject name under which the value schema is registered with Schema Registry. - **Key Converter Key Subject Name Strategy**: Determines how to construct the subject name for key schema registration. - **Value Converter Ignore Default For Nullables**: When set to `true`, this property ensures that the corresponding record in Kafka is `null`, instead of showing the default column value. Applies to the `AVRO`, `PROTOBUF`, and `JSON_SR` converters. - **Value Converter Schema ID Serializer**: The class name of the schema ID serializer for values. This is used to serialize schema IDs in the message headers. **Auto-restart policy** - **Enable Connector Auto-restart**: Enables 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 to `false` to disable auto-restart for failed connectors. If disabled, you must manually restart the connector. **ActiveMQ Session** - **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 for a single poll in milliseconds.**: 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](https://activemq.apache.org/selectors) that should be applied to messages in the destination. **Transforms** - **Single Message Transformations**: To add a new SMT, see [Add transforms](single-message-transforms.md#cc-single-message-transforms-ui). For more information about unsupported SMTs, see [Unsupported transformations](single-message-transforms.md#cc-single-message-transforms-unsupported-transforms). See [Configuration Properties](#cc-activemq-source-config-properties) for all property values and definitions. - Click **Continue**. ### Sizing Based on the number of topic partitions you select, you will be provided with a recommended number of tasks. 1. To change the number of tasks, use the Range Slider to select the desired number of tasks. 2. Click **Continue**. ### Review and Launch 1. Verify the connection details by previewing the running configuration. 2. 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](connect-api-section.md#ccloud-connect-api) 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](cc-mqtt-source.md#cc-mqtt-source-prereqs) completed. #### Step 1: List the available connectors Enter the following command to list available connectors: ```none confluent connect plugin list ``` #### Step 2: List the connector configuration properties Enter the following command to show the connector configuration properties: ```none confluent connect plugin describe ``` 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. ```none { "connector.class": "ActiveMQSource", "name": "ActiveMQSource_0", "kafka.auth.mode": "KAFKA_API_KEY", "kafka.api.key": "", "kafka.api.secret": "", "kafka.topic" : "topic_0", "output.data.format" : "AVRO", "activemq.url" : "tcp://:61616", "activemq.username" : "", "activemq.password" : "", "jms.destination.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](service-account.md#s3-cloud-service-account), specify the **Resource ID** in the property `kafka.service.account.id=`. To list the available service account resource IDs, use the following command: ```bash confluent iam service-account list ``` For example: ```bash 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](../get-started/schema-registry.md#cloud-sr-config) must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). * `"activemq.url"`: The URL of the ActiveMQ broker. An ActiveMQ broker URL is similar to `tcp://:61616`. * `"jms.destination.name"`: The name of the JMS destination `queue` or `topic` name to read from. * `"tasks.max"`: Enter the number of [tasks](/platform/current/connect/concepts.html#tasks) in use by the connector. The connector supports multiple tasks. More tasks may improve performance. **SMTs**: For details about adding SMTs using the Confluent CLI, see the [Single Message Transformations](single-message-transforms.md#cc-single-message-transforms) documentation. See [Configuration Properties](#cc-activemq-source-config-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: ```none confluent connect cluster create --config-file .json ``` For example: ```none confluent connect cluster create --config-file activemq-source.json ``` Example output: ```none Created connector ActiveMQSource_0 lcc-ix4dl ``` #### Step 5: Check the connector status Enter the following command to check the connector status: ```none confluent connect plugin list ``` Example output: ```none 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](connect-api-section.md#ccloud-connect-api) 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](/platform/current/connect/kafka_connectors.html). ### 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, whenever possible.
* Type: string * Valid Values: SERVICE_ACCOUNT, KAFKA_API_KEY * 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 * Default: JSON * 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 ### Additional Configs `header.converter` : The converter class for the headers. This is used to serialize and deserialize the headers of the messages.
* Type: string * Importance: low `producer.override.compression.type` : The 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.ms` : The 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](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.keys` : Allow optional string map key when converting from Connect Schema to Avro Schema. Applicable for Avro Converters.
* Type: boolean * Importance: low `value.converter.auto.register.schemas` : Specify if the Serializer should attempt to register the Schema.
* Type: boolean * Importance: low `value.converter.connect.meta.data` : Allow the Connect converter to add its metadata to the output schema. Applicable for Avro Converters.
* Type: boolean * Importance: low `value.converter.enhanced.avro.schema.support` : Enable enhanced schema support to preserve package information and Enums. Applicable for Avro Converters.
* Type: boolean * Importance: low `value.converter.enhanced.protobuf.schema.support` : Enable enhanced schema support to preserve package information. Applicable for Protobuf Converters.
* Type: boolean * Importance: low `value.converter.flatten.unions` : Whether to flatten unions (oneofs). Applicable for Protobuf Converters.
* Type: boolean * Importance: low `value.converter.generate.index.for.unions` : Whether to generate an index suffix for unions. Applicable for Protobuf Converters.
* Type: boolean * Importance: low `value.converter.generate.struct.for.nulls` : Whether to generate a struct variable for null values. Applicable for Protobuf Converters.
* Type: boolean * Importance: low `value.converter.int.for.enums` : Whether to represent enums as integers. Applicable for Protobuf Converters.
* Type: boolean * Importance: low `value.converter.latest.compatibility.strict` : Verify latest subject version is backward compatible when use.latest.version is true.
* Type: boolean * Importance: low `value.converter.object.additional.properties` : Whether to allow additional properties for object schemas. Applicable for JSON_SR Converters.
* Type: boolean * Importance: low `value.converter.optional.for.nullables` : Whether nullable fields should be specified with an optional label. Applicable for Protobuf Converters.
* Type: boolean * Importance: low `value.converter.optional.for.proto2` : Whether proto2 optionals are supported. Applicable for Protobuf Converters.
* Type: boolean * Importance: low `value.converter.scrub.invalid.names` : Whether 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.version` : Use latest version of schema in subject for serialization when auto.register.schemas is false.
* Type: boolean * Importance: low `value.converter.use.optional.for.nonrequired` : Whether to set non-required properties to be optional. Applicable for JSON_SR Converters.
* Type: boolean * Importance: low `value.converter.wrapper.for.nullables` : Whether nullable fields should use primitive wrapper messages. Applicable for Protobuf Converters.
* Type: boolean * Importance: low `value.converter.wrapper.for.raw.primitives` : Whether a wrapper message should be interpreted as a raw primitive at root level. Applicable for Protobuf Converters.
* Type: boolean * Importance: low `errors.tolerance` : Use 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.schema.id.serializer` : The class name of the schema ID serializer for keys. This is used to serialize schema IDs in the message headers.
* Type: string * Default: io.confluent.kafka.serializers.schema.id.PrefixSchemaIdSerializer * Importance: low `key.converter.key.subject.name.strategy` : How to construct the subject name for key schema registration.
* Type: string * Default: TopicNameStrategy * Importance: low `value.converter.decimal.format` : Specify 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.unions` : Whether to flatten singleton unions. Applicable for Avro and JSON_SR Converters.
* Type: boolean * Default: false * Importance: low `value.converter.ignore.default.for.nullables` : When 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.strategy` : Set 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.default` : Whether 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.enable` : Include 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.schema.id.serializer` : The class name of the schema ID serializer for values. This is used to serialize schema IDs in the message headers.
* Type: string * Default: io.confluent.kafka.serializers.schema.id.PrefixSchemaIdSerializer * Importance: low `value.converter.value.subject.name.strategy` : Determines 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.error` : Enable connector to automatically restart on user-actionable errors.
* Type: boolean * Default: true * Importance: medium ## Frequently asked questions Find answers to frequently asked questions about the ActiveMQ Source connector for Confluent Cloud. ### Why is the connector failing with the `Connection to the ActiveMQ broker failed` error? This error indicates the connector cannot establish a connection to your ActiveMQ broker. Verify the following common issues: * **Broker availability**: Verify the ActiveMQ broker is running and listening on the configured host and port. For example, `tcp://broker.example.com:61616` or `ssl://broker.example.com:61617`. * **Network connectivity**: Ensure firewall rules, security groups, or Network Access Control Lists (NACLs) allow traffic from Confluent Cloud to your broker. If you are using private networking, verify the configuration is correct. * **Broker URL configuration**: In the connector configuration, confirm `activemq.url` uses the correct protocol (`tcp://` or `ssl://`), hostname, and port number. * **Invalid credentials**: Verify `activemq.username` and `activemq.password` match the credentials configured on your ActiveMQ broker. ### How do I configure the JMS destination correctly? The connector requires accurate JMS destination configuration to read messages from your ActiveMQ broker. Verify the following properties are set correctly: * `jms.destination.name`: Set this to the exact name of the JMS queue or topic from which you want to read messages. * `jms.destination.type`: Set this to either `QUEUE` or `TOPIC` based on your source destination type. If the destination name or type is incorrect, the connector cannot read messages from ActiveMQ. ### Why is the connector failing with Schema Registry errors? If you configure `output.data.format` to use a schema-based format like AVRO, JSON_SR, or PROTOBUF, the connector requires access to Confluent Cloud Schema Registry. Verify the following common issues: * **Schema Registry not enabled**: Verify Confluent Cloud Schema Registry is enabled for your Confluent Cloud environment. See [Quick Start for Schema Management on Confluent Cloud](../get-started/schema-registry.md#cloud-sr-config) for details. * **Missing or incompatible schema**: Ensure a valid schema is registered in Confluent Cloud Schema Registry and is compatible with the messages from ActiveMQ. * **Incorrect credentials**: Verify your Confluent Cloud Schema Registry credentials are correctly configured in the connector. For JSON messages without a schema, set `output.data.format` to `JSON` instead of `JSON_SR`. ### What should I do if the connector stops receiving messages? If the connector stops streaming messages to your Kafka topic: 1. **Check connector status**: In the Confluent Cloud Console, navigate to your connector and verify its status. Look for error messages in the connector logs. 2. **Verify broker health**: Ensure your ActiveMQ broker is running and accessible. Check broker logs for errors or restarts. 3. **Review network connectivity**: Confirm network connectivity between Confluent Cloud and your ActiveMQ broker has not been disrupted. 4. **Check for broker failover**: During broker failover scenarios, the connector may experience temporary errors but often recovers automatically. Monitor the connector status to see if it recovers. 5. **Restart the connector**: If the connector does not recover automatically, restart it from the Confluent Cloud Console. ### Why am I seeing authentication errors even with correct credentials? Authentication errors can occur for several reasons. Verify the following: * **Incorrect username or password**: Verify that `activemq.username` and `activemq.password` exactly match the credentials configured on your ActiveMQ broker. * **Authentication required but not configured**: If your ActiveMQ broker requires authentication and you have not provided credentials, connection attempts will fail. * **Broker-side configuration**: Verify your ActiveMQ broker is configured to accept the provided credentials and that the user has appropriate permissions. ## 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](/platform/current/tutorials/examples/cloud-etl/docs/index.html). This example also shows how to use Confluent CLI to manage your resources in Confluent Cloud. [](https://docs.confluent.io/platform/current/tutorials/examples/cloud-etl/docs/index.html)