Azure Service Bus Source Connector for Confluent Cloud

The Azure Service Bus is a multitenant cloud messaging service you can use to send information between applications and services. The fully-managed Azure Service Bus Source connector for Confluent Cloud reads data from an Azure Service Bus queue or topic, and persists the data in an Apache Kafka® topic.

Note

This is a Quick Start for the fully-managed cloud connector. If you are installing the connector locally for Confluent Platform, see Azure Service Bus Source connector for Confluent Platform.

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 Managed and Custom Connectors section.

Limitations

Be sure to review the following information.

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

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 Azure Service Bus Source connector card.

Azure Service Bus 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 Azure Service Bus 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.

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 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": "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 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": Enter the topic name where data is sent.

  • "azure.servicebus.<>": Enter the Azure Service Bus details. For azure.servicebus.namespace, only use the namespace 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 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

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

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.

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