Azure Service Bus Source Connector for Confluent Cloud¶
Note
This is a Quick Start for the managed cloud connector. If you are installing the connector locally for Confluent Platform, see Azure Service Bus Source connector for Confluent Platform.
The Azure Service Bus is a multitenant cloud messaging service you can use to send information between applications and services. The Kafka Connect Azure Service Bus Source connector for Confluent Cloud reads data from an Azure Service Bus queue or topic, and persists the data in a Kafka topic.
Features¶
The Azure Service Bus Source connector supports the following features:
- Topics created automatically: The connector can automatically create Kafka topics.
- 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.
- Supported data formats: The connector supports Avro, JSON Schema (JSON-SR), Protobuf, and JSON (schemaless) output formats. 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.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect section.
Limitations¶
Be sure to review the following information.
- For connector limitations, see Azure Service Bus 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 Azure Service Bus Source connector. The quick start provides the basics of selecting the connector and configuring it to stream events.
- Prerequisites
- Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud Platform (GCP).
- 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.
- You must have the Azure Service Bus connection details. For additional information, see the Azure Service Bus docs.
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 Azure Service Bus Source Connector screen, complete the following:
- Select the way you want to provide Kafka Cluster credentials. You can
choose one of the following options:
- Global Access: Allows your connector to access everything you have access to. With global access, connector access will be linked to your account. This option is not recommended for production.
- Granular access: Limits the access for your connector. You will be able to manage connector access through a service account. This option is recommended for production.
- Use an existing API key: Allows you to enter an API key and secret part you have stored. You can enter an API key and secret (or generate these in the Cloud Console).
- Click Continue.
- Enter the required Azure Service Bus connection details:
- Azure Service Bus Namespace: Azure Service Bus namespace that the
messaging entity belongs to. Only enter the
namespace
section from<namespace>.servicebus.windows.net
. Do not use the fully-qualified domain name (FQDN). - Shared access policy name: Shared access policy name to use for access authentication.
- Shared access key: Shared access key to use for access authentication.
- Azure Service Bus Queue/Topic Name: Azure Service Bus messaging entity name. Should be either the name of the queue or topic from which messages have to be polled.
- Azure Service Bus Subscription Name: The Azure Service Bus subscription name for the configured topic from which messages have to be polled. This should only be configured when messaging entity is of type topic.
- Azure Service Bus Namespace: Azure Service Bus namespace that the
messaging entity belongs to. Only enter the
- 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.
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 Schema contexts.
For transforms and predicates, see the Single Message Transforms (SMT) documentation for details. Also, see Configuration Properties for all property values and descriptions.
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 for records.¶
Verify that records are being produced at the Kafka topic.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect 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-catalog-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": "AzureServiceBusSource",
"name": "AzureServiceBusSource_0",
"kafka.auth.mode": "KAFKA_API_KEY",
"kafka.api.key": "****************",
"kafka.api.secret": "************************************************",
"kafka.topic": "<topic-name>",
"azure.servicebus.namespace": "<namespace>",
"azure.servicebus.sas.keyname": "<keyname>",
"azure.servicebus.sas.key": "****************************************",
"azure.servicebus.entity.name": "<entity>",
"output.data.format": "AVRO",
"tasks.max": "1",
}
Note the following property definitions:
"connector.class"
: Identifies the connector plugin name."name"
: Sets a name for your new connector.
"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"
: Enter the topic name where data is sent."azure.servicebus.<>"
: Enter the Azure Service Bus details. Forazure.servicebus.namespace
, only use thenamespace
section from<namespace>.servicebus.windows.net
. Do not use the fully-qualified domain name (FQDN). For additional information, see the Azure Service Bus docs. For details about shared access signature (SAS) authorization, see Shared Access Authorization Policies.“
output.data.format"
: Enter an output Kafka record value format (data going into the Kafka topic): AVRO, JSON_SR (JSON Schema), PROTOBUF, or JSON (schemaless). 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."tasks.max"
: Enter the maximum number of tasks for the connector to use.
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 descriptions.
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 azure-service-bus-source-config.json
Example output:
Created connector AzureServiceBusSource_0 lcc-do6vzd
Step 5: Check the connector status.¶
Enter the following command to check the connector status:
confluent connect cluster list
Example output:
ID | Name | Status | Type | Trace
+------------+-------------------------------+---------+------+-------+
lcc-do6vzd | AzureServiceBusSource_0 | RUNNING | sink | |
Step 6: Check for records.¶
Verify that records are being produced at the Kafka topic.
For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect section.
Configuration Properties¶
Use the following configuration properties with this connector.
Note
These are properties for the managed cloud connector. If you are installing the connector locally for Confluent Platform, see Azure Service Bus Source connector 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
Schema Config¶
schema.context.name
A schema context represents an independent scope in Schema Registry, and can be used to create any number of separate ‘sub-registries’ within one Schema Registry cluster. Please refer Confluent documentation for more details.
- Type: string
- Default: default
- Importance: medium
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
How should we connect to Azure Service Bus?¶
azure.servicebus.namespace
Azure Service Bus Namespace that the messaging entity belongs to.
- Type: string
- Importance: high
azure.servicebus.sas.keyname
Shared access policy name to use for access authentication.
- Type: string
- Importance: high
azure.servicebus.sas.key
Shared access key to use for access authentication.
- Type: password
- Importance: high
azure.servicebus.entity.name
Azure Service Bus messaging entity name. Should be either the name of the queue or topic from which messages have to be polled.
- Type: string
- Importance: high
azure.servicebus.subscription
The Azure Service Bus Subscription Name for the configured topic from which messages have to be polled. This should only be configured when messaging entity is of type topic.
- Type: string
- Importance: high
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
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.