Salesforce CDC 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 Salesforce Change Data Capture Source Connector for Confluent Platform.

The Kafka Connect Salesforce Change Data Capture (CDC) Source connector for Confluent Cloud provides a way to monitor Salesforce records. Salesforce sends a notification when a change to a Salesforce record occurs as part of a create, update, delete, or undelete operation. The Salesforce CDC Source connector can be used to capture these change events and write them to an Apache Kafka® topic.

Features

The Salesforce CDC Source connector provides the following features:

  • Salesforce Streaming API: This connector uses the Salesforce Streaming API (Change Data Capture). Changes captured include new records, updates to existing records, record deletions, and record undeletions.
  • Initial start: Captures the latest changes or all changes over the last 24 hours.
  • Data formats: The connector supports Avro, JSON Schema, Protobuf, JSON (schemaless), or SF_API output data. In SF_API format the record is formatted identically to the Salesforce message received by the connector and the messages are ingested as raw bytes without any schema. 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.
  • Topics created automatically: The connector can automatically create Kafka topics.
  • Tasks per connector: Organizations can run multiple connectors with a limit of one task per connector (that is, "tasks.max": "1").

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.

Quick Start

Use this quick start to get up and running with the Salesforce CDC Source connector. The quick start provides the basics of selecting the connector and configuring it to monitor changes.

Prerequisites
  • 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 Data integration, and then click Connectors. If you already have connectors in your cluster, click + Add connector.

Step 3: Select your connector.

Click the Salesforce CDC Source connector card.

Salesforce CDC Source Connector Card

Important

At least one topic must exist in your Confluent Cloud cluster before creating the 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 Salesforce CDC 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 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 section.

See also

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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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.
  • The example commands use Confluent CLI version 2. For more information see, Confluent CLI v2.

Important

At least one topic must exist in your Confluent Cloud cluster before creating the connector.

Step 1: List the available connectors.

Enter the following command to list available connectors:

confluent connect plugin list

Step 2: Show the required connector configuration properties.

Enter the following command to show the required connector properties:

confluent connect plugin describe <connector-catalog-name>

For example:

confluent connect plugin describe SalesforceCdcSource

Example output:

Following are the required configs:
connector.class: SalesforceCdcSource
name
kafka.auth.mode
kafka.api.key
kafka.api.secret
kafka.topic
salesforce.username
salesforce.password
salesforce.password.token
salesforce.consumer.key
salesforce.consumer.secret
salesforce.cdc.name
output.data.format
tasks.max

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": "SalesforceCdcSource",
  "name": "SalesforceCdcSourceConnector_0",
  "kafka.auth.mode": "KAFKA_API_KEY",
  "kafka.api.key": "****************",
  "kafka.api.secret": "****************************************************************",
  "kafka.topic": "AccountChangeEvent",
  "salesforce.username": "<my-username>",
  "salesforce.password": "**************",
  "salesforce.password.token": "************************",
  "salesforce.consumer.key": "*************************************************************************************",
  "salesforce.consumer.secret": "****************************************************************",
  "salesforce.cdc.name": "AccountChangeEvent",
  "output.data.format": "JSON",
  "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 a Kafka topic name. A topic must exist before launching the connector.

  • "output.data.format": Sets the output Kafka record value format (data coming from the connector). Valid entries are AVRO, JSON_SR, PROTOBUF, or JSON. You must have Confluent Cloud Schema Registry configured if using a schema-based message format (for example, Avro, JSON_SR (JSON Schema), or Protobuf).

  • "tasks.max": Enter the number of tasks in use by the connector. Organizations can run multiple connectors with a limit of one task per connector (that is, "tasks.max": "1").

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 create --config <file-name>.json

For example:

confluent connect create --config salesforce-cdc-source.json

Example output:

Created connector SalesforceCdcSourceConnector_0 lcc-ix4dl

Step 5: Check the connector status.

Enter the following command to check the connector status:

confluent connect list

Example output:

ID          |            Name                  | Status  |  Type
+-----------+----------------------------------+---------+-------+
lcc-ix4dl   | SalesforceCdcSourceConnector_0   | RUNNING | source

Step 6: 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 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 Salesforce Change Data Capture 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

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
  • 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
  • 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 Salesforce?

salesforce.instance

The URL of the Salesforce endpoint to use. The default is https://login.salesforce.com. This directs the connector to use the endpoint specified in the authentication response.

salesforce.username

The Salesforce username the connector should use.

  • Type: string
  • Importance: high
salesforce.password

The Salesforce password the connector should use.

  • Type: password
  • Importance: high
salesforce.password.token

The Salesforce security token associated with the username.

  • Type: password
  • Importance: high
salesforce.consumer.key

The consumer key for the OAuth application.

  • Type: password
  • Importance: high
salesforce.consumer.secret

The consumer secret for the OAuth application.

  • Type: password
  • Importance: high
salesforce.cdc.name

The Salesforce Change Data Capture event name to subscribe to.

  • Type: string
  • Importance: high

Connection details

salesforce.initial.start

Specify the initial starting point for the connector for replaying events.

  • Type: string
  • Default: latest
  • Importance: high
connection.timeout

The amount of time to wait in milliseconds while connecting to the Salesforce streaming endpoint.

  • Type: long
  • Default: 30000
  • Importance: low
request.max.retries.time.ms

In case of error when making a request to Salesforce, the connector will retry until this time (in ms) elapses. The default value is 30000 (30 seconds). Minimum value is 1 sec

  • Type: long
  • Default: 30000 (30 seconds)
  • Valid Values: [1000,…,250000]
  • Importance: low
connection.max.message.size

The maximum message size in bytes that is accepted during a long poll on the Salesforce streaming endpoint.

  • Type: int
  • Default: 1048576
  • Valid Values: [1048576,…,104857600]
  • Importance: low

Output messages

output.data.format

Sets the output Kafka record value format. Valid entries are AVRO, JSON_SR, PROTOBUF, JSON or SF_API. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF. When SF_API is selected, the record will be identical in format to the salesforce message as received by the connector. Note that in SF_API, messages are ingested as raw bytes without any schema.

  • Type: string
  • Importance: high
convert.changed.fields

Whether to convert field names within changed fields section of the ChangeEventHeader to match field names present on the Kafka record.

  • Type: boolean
  • Default: false
  • Importance: low

Number of tasks for this connector

tasks.max
  • Type: int
  • Valid Values: [1,…,1]
  • Importance: high

Next Steps

See also

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.

../_images/topology.png