IBM MQ Source Connector for Confluent Cloud¶
The fully-managed IBM MQ Source connector for Confluent Cloud reads messages from an IBM MQ cluster and then writes them 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 IBM MQ 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 IBM MQ Source connector provides the following features:
- This connector guarantees that records are delivered at-least-once to the Kafka topic.
- Client-side field level encryption (CSFLE) support: The connector supports CSFLE for sensitive data. For more information about CSFLE setup, see the connector configuration.
- Multiple tasks: The connector supports multiple tasks. More tasks may improve performance.
- JMS message types: The connector supports TextMessage and BytesMessage. It does not support ObjectMessage or StreamMesssage.
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 IBM MQ 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.
Errors and retry attempts¶
The IBM MQ Source connector uses the general retry policy implemented for most Kafka Connect connectors. Additionally, the IBM MQ Source connector uses exponential backoff after each retry attempt. The backoff time is the time between retries and a random value between zero and the exponentially increasing bound. The exponential bound is capped at one minute and the initial backoff time is set to 100
milliseconds (ms).
initialbackoffTime * 2 ^ (retry-1)
The following errors will trigger a retry. With the exception of
MQRC_GET_INHIBITED
, all of the listed errors first shut down the connection
and then reconnect before retrying.
MQRC_GET_INHIBITED
MQRC_BACKED_OUT
MQRC_CHANNEL_NOT_AVAILABLE
MQRC_CONNECTION_BROKEN
MQRC_HOST_NOT_AVAILABLE
MQRC_NOT_AUTHORIZED
MQRC_Q_MGR_NOT_AVAILABLE
MQRC_Q_MGR_QUIESCING
MQRC_Q_MGR_STOPPING
MQRC_UNEXPECTED_ERROR
Quick Start¶
Use this quick start to get up and running with the Confluent Cloud IBM MQ source connector. The quick start shows how to attach the connector to an IBM MQ broker, subscribe to the specified queue or topic, and stream data into Apache Kafka®.
- Prerequisites
- Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud.
- Access to an IBM MQ 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 IBM MQ 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 IBM MQ authentication details:
- Username: The username to use when connecting to IBM MQ.
- Password: The password to use when connecting to IBM MQ.
- IBM MQ broker host: The IBM MQ broker host.
- IBM MQ broker port: The IBM MQ broker port.
- TLS Keystore Type: The file format of the key store file. This is required only when using secure TLS communication with IBM MQ.
- TLS Keystore file: Upload your TLS key store file.
- TLS Keystore Password: The store password for the key store file. This is optional for client and only needed if TLS Keystore file is configured.
- TLS Key Password: The password of the private key used for secure TLS communication with IBM MQ.
- TLS Truststore Type: The file format of the trust store file. This is required when using TLS and secure communication with IBM MQ.
- TLS Truststore file: Upload your TLS trust store file.
- TLS Truststore Password: The password for the trust store file. If a password is not set access to the truststore is still available, but integrity checking is disabled. This is required only when using secure TLS communication with IBM MQ.
- TLS KeyManager Algorithm: The algorithm used by key manager factory for SSL connections. Default value is the key manager factory algorithm configured for the Java Virtual Machine. This is required only when using secure TLS communication with IBM MQ.
- TLS TrustManager Algorithm: The algorithm used by trust manager factory for SSL connections. Default value is the trust manager factory algorithm configured for the Java Virtual Machine. This is required only when using secure TLS communication with IBM MQ.
- TLS Secure Random Implementation: The SecureRandom PNG implementation to use for SSL cryptography operations.
- Click Continue.
Configure the following properties:
- (Optional) Enable Client-Side Field Level Encryption for data encryption. Specify a Service Account to access the Schema Registry and associated encryption rules or keys with that schema. For more information on CSFLE setup, see Manage CSFLE for connectors.
- 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.
- Destination Name: The name of the JMS destination (queue or topic) to read from.
- Queue Manager: The name of the queue manager.
- Destination Type: The type of JMS destination, which is either
queue
ortopic
. - Channel: The channel name for client connections.
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?.
Maximum time to wait…: The maximum amount of time in milliseconds (ms) for a task to build a batch.
Character Encoding: The character encoding to use while receiving the message. Defaults to
UTF-8
.SSL Cipher Suite: The CipherSuite for SSL connections.
SSL FIPS Required: Set whether SSL FIPS is required.
SSL Peer Name: Sets a distinguished name (DN) pattern. If
sslCipherSuite
is set, this pattern can ensure that the correct queue manager is used. The connection attempt fails if the distinguished name provided by the queue manager does not match this pattern.Durable Subscription: Whether the connector task subscription to the JMS topic is durable or not.
TLS Protocol: The TLS protocol version for secure connections to IBM MQ.
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 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 that 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": " IbmMQSource",
"name": "IbmMQSource",
"kafka.auth.mode": "KAFKA_API_KEY",
"kafka.api.key": "<my-kafka-api-key>",
"kafka.api.secret": "<my-kafka-api-secret>",
"kafka.topic" : "data_topic_0",
"output.data.format": "AVRO",
"jms.destination.name": "<destination-name>",
"mq.username": "<authorized-user>",
"mq.password": "<user-password>"
"mq.hostname": "<server-hostname>",
"mq.queue.manager": <queue-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"
: Supports AVRO, JSON, JSON_SR, and PROTOBUF. Schema Registry must be enabled to use a Schema Registry-based format."jms.destination.name"
: This is the name of the JMS destination (queue or topic) to read from."mq.username"
: Authorized user for the broker host.mq.password
is required if not using additional connection security."mq.queue.manager"
: The IBM MQ queue manager."tasks.max"
: Enter the number of tasks in use by the connector. The connector supports multiple tasks. More tasks may improve performance.
Note
(Optional) To enable CSFLE for data encryption, specify the following properties:
csfle.enabled
: Flag to indicate whether the connector honors CSFLE rules.sr.service.account.id
: A Service Account to access the Schema Registry and associated encryption rules or keys with that schema.
For more information on CSFLE setup, see Manage CSFLE for connectors.
Single Message Transforms: See the Single Message Transforms (SMT) documentation for details about adding SMTs. See Unsupported transformations for a list of SMTs that are not supported with this connector.
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 ibmmq-source.json
Example output:
Created connector IbmMQSource_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 | IbmMQSource_0 | RUNNING | source
Step 6: Check the results on the broker.¶
After the connector is running, verify that 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?¶
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
- Default: JSON
- Importance: high
IBM MQ Secure Connection¶
mq.tls.protocol
The TLS protocol version for secure connections to IBM MQ. The default is
TLSv1.2
, which should be fine for most cases, though the actual set of allowed values will depend on the JVM. Recent JVMs supportTLSv1.3
andTLSv1.2
,TLSv1.1
andTLS
. Older JVMs may supportSSL
,SSLv2
andSSLv3
, but these versions are disabled due to known security vulnerabilities.- Type: string
- Default: TLSv1.2
- Importance: medium
mq.tls.keystore.type
The file format of the key store file. This is required only when using secure TLS communication with IBM MQ. For MQ on Cloud queue managers of version 9.2.1 revision 2 and above, TLS is enabled by default
- Type: string
- Default: JKS
- Importance: medium
mq.tls.keystore.location
The key store file. This is required only when using secure TLS communication with IBM MQ.
- Type: password
- Importance: high
mq.tls.keystore.password
The store password for the key store file. This is optional for client and only needed if
TLS Keystore file
is configured.- Type: password
- Importance: high
mq.tls.key.password
The password of the private key used for secure TLS communication with IBM MQ.
- Type: password
- Importance: high
mq.tls.truststore.type
The file format of the trust store file. This is required when using TLS and secure communication with IBM MQ.
- Type: string
- Default: JKS
- Importance: medium
mq.tls.truststore.location
The trust store file. This is required only when using secure TLS communication with IBM MQ.
- Type: password
- Importance: high
mq.tls.truststore.password
The password for the trust store file. If a password is not set access to the truststore is still available, but integrity checking is disabled. This is required only when using secure TLS communication with IBM MQ.
- Type: password
- Importance: high
mq.tls.keymanager.algorithm
The algorithm used by key manager factory for SSL connections. Default value is the key manager factory algorithm configured for the Java Virtual Machine. This is required only when using secure TLS communication with IBM MQ.
- Type: string
- Default: SunX509
- Importance: low
mq.tls.trustmanager.algorithm
The algorithm used by trust manager factory for SSL connections. Default value is the trust manager factory algorithm configured for the Java Virtual Machine. This is required only when using secure TLS communication with IBM MQ.
- Type: string
- Default: PKIX
- Importance: low
mq.tls.secure.random.implementation
The SecureRandom PRNG implementation to use for SSL cryptography operations. By default, tries PKCS11 implementation first. If PKCS11 is not supported, iterates through the provider and returns the first working implementation. This is required only when using secure TLS communication with IBM MQ.
- Type: string
- Importance: low
IBM MQ 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
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.
- Type: int
- Default: 2000
- Valid Values: [0,…,20000]
- Importance: high
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
- Importance: low
character.encoding
The character encoding to use while receiving the message.
- Type: string
- Default: UTF-8
- Importance: low
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
- 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 JMS message selector that should be applied to messages in the destination.
- Type: string
- Importance: high
IBM MQ Connection¶
mq.username
The username to use when connecting to IBM MQ.
- Type: string
- Importance: high
mq.password
The password to use when connecting to IBM MQ.
- Type: password
- Importance: high
mq.configuration.mode
The mode in connector is to configure single mq instance or multiple for HA/DR support
- Type: string
- Default: single
- Importance: high
mq.hostname
IBM MQ broker host
- Type: string
- Importance: high
mq.port
IBM MQ broker port
- Type: int
- Default: 1414
- Importance: high
mq.connection.list
For IBM’s HA/DR support with multiple MQ instances, enter hosts as comma-separated values, e.g., host1:port1, host2:port2.
- Type: string
- Importance: high
mq.queue.manager
The name of the queue manager.
- Type: string
- Importance: high
mq.channel
The channel for client connections.
- Type: string
- Default: “”
- Importance: high
mq.ssl.cipher.suite
The CipherSuite for SSL connections.
- Type: string
- Default: “”
- Importance: high
mq.ssl.fips.required
Whether SSL FIPS is required.
- Type: boolean
- Importance: high
mq.ssl.peer.name
Sets a distinguished name (DN) pattern. If sslCipherSuite is set, this pattern can ensure that the correct queue manager is used. The connection attempt fails if the distinguished name provided by the queue manager does not match this pattern.
- Type: string
- Default: “”
- Importance: high
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.