Salesforce CDC Source Connector for Confluent Cloud

The fully-managed 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.

Note

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.
  • Support for single entity channels: The connector supports single entity channels like the LeadChangeEvent channel.
  • Support for multiple entity channels: The connector supports multiple entity channels like the ChangeEvents Standard Channel or a Custom Channel like LeadCustom__chn.
  • Initial start: Captures the latest changes or all changes over the last 72 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. When using multiple entity channels with the connector, you can add ${_ObjectType} to the topic name to create different topic names based on the entity name.
  • Tasks per connector: Organizations can run multiple connectors with a limit of one task per connector (that is, "tasks.max": "1").
  • Offset management capabilities: Supports offset management. For more information, see Manage custom offsets.

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.

Manage custom offsets

You can manage the offsets for this connector. Offsets provide information on the point in the system from which the connector is accessing data. For more information, see Manage Offsets for Fully-Managed Connectors in Confluent Cloud.

To manage offsets:

To get the current offset, make a GET request that specifies the environment, Kafka cluster, and connector name.

GET /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets
Host: https://api.confluent.cloud

Response:

Successful calls return HTTP 200 with a JSON payload that describes the offset.

{
    "id": "lcc-example123",
    "name": "{connector_name}",
    "offsets": [
      {
        "partition": {},
        "offset": {
          "replayId": 75314157
        }
      }
    ],
    "metadata": {
        "observed_at": "2024-03-28T17:57:48.139635200Z"
    }
}

Responses include the following information:

  • The position of latest offset - represented by replayId.
  • The observed time of the offset in the metadata portion of the payload. The observed_at time indicates a snapshot in time for when the API retrieved the offset. A running connector is always updating its offsets. Use observed_at to get a sense for the gap between real time and the time at which the request was made. By default, offsets are observed every minute. Calling get repeatedly will fetch more recently observed offsets.
  • Information about the connector.

JSON payload

The table below offers a description of the unique fields in the JSON payload for managing offsets of the Salesforce CDC Source connector.

Field Definition Required/Optional
replayId The ReplayId field value, which is populated by the Salesforce system refers to the position of the event in the event stream. Replay ID values are not guaranteed to be contiguous for consecutive events. For more information, see Message Durability in the Salesforce documentation. Required

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 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

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:

Enter a topic name.

The connector can automatically create Kafka topics. When using multiple entity channels (MULTI) with the connector, you can add ${_ObjectType} to the topic name to create different topic names based on the entity name.

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": "SalesforceCdcSource",
  "name": "SalesforceCdcSourceConnector_0",
  "kafka.auth.mode": "KAFKA_API_KEY",
  "kafka.api.key": "****************",
  "kafka.api.secret": "****************************************************************",
  "kafka.topic": "AccountChangeEvent",
  "salesforce.grant.type": "PASSWORD",
  "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. When using multiple entity channels with the connector, you can add ${_ObjectType} to the topic name to create different topic names based on the entity name.

  • "salesforce.grant.type": Sets the authentication grant type to PASSWORD (username+password) or JWT_BEARER (Salesforce JSON Web Token (JWT)). Defaults to PASSWORD.

    Note

    The following properties are used based on the salesforce.grant.type you choose.

    • JWT_BEARER: Requires username, consumer key, JWT keystore file, and JWT keystore password.
    • PASSWORD: Requires username, password, password token, consumer key, and consumer secret.

  • "salesforce.username": The Salesforce username for the connector to use.

  • "salesforce.password": The Salesforce username password.

  • "salesforce.password.token": The Salesforce security token associated with the username.

  • "salesforce.consumer.key": The consumer key for the OAuth application.

  • "salesforce.consumer.secret": The consumer secret for the OAuth application.

  • "salesforce.jwt.keystore.file": Salesforce JWT keystore file. The JWT keystore file is a binary file and you supply the contents of the file in the property encoded in Base64. To use the salesforce.jwt.keystore.file property, encode the keystore contents in Base64, take the encoded string, add the data:text/plain:base64 prefix, and then use the entire string as the property entry. For example:

    "salesforce.jwt.keystore.file" : "data:text/plain;base64,/u3+7QAAAAIAAAACAAAAGY2xpZ...==",
"salesforce.jwt.keystore.password" : "<password>",

  • "salesforce.jwt.keystore.password": Enter the password used to access the JWT keystore file.

  • "salesforce.cdc.name": The Salesforce Change Data Capture event name to subscribe to.

  • "output.data.format": Sets the output Kafka record value format (data coming from the connector). Valid entries are AVRO, JSON_SR, PROTOBUF, JSON, or SF_API. You must have Confluent Cloud Schema Registry configured if using a schema-based message format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). Note that if you select SF_API, records are ingested as raw bytes and the record format is identical to the salesforce message format. For additional information, see Schema Registry Enabled Environments.

  • "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 cluster create --config-file <file-name>.json

For example:

confluent connect cluster create --config-file 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 cluster 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 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

How should we connect to Salesforce?

salesforce.grant.type

Salesforce grant type. Valid options are ‘PASSWORD’ and ‘JWT_BEARER’.

  • Type: string
  • Default: PASSWORD
  • Importance: high
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.channel.type

Indicates the type of Salesforce CDC channel from which the connector shall consume the events. The value can be SINGLE or MULTI. SINGLE should be used for a single entity channel like LeadChangeEvent. MULTI should be used for the Standard (ChangeEvents) channel or a Custom channel like LeadCustom__chn.

  • Type: string
  • Importance: high
salesforce.password

The Salesforce password the connector should use.

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

The Salesforce Change Data Capture event name to subscribe to.

  • Type: string
  • 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.channel.entities

Comma seperated list of entities in the standard or custom channel. Eg LeadChangeEvent, AccountChangeEvent.

  • Type: list
  • Importance: medium
salesforce.consumer.secret

The consumer secret for the OAuth application.

  • Type: password
  • Importance: medium
salesforce.jwt.keystore.file

Salesforce JWT keystore file which contains the private key.

  • Type: password
  • Default: [hidden]
  • Importance: medium
salesforce.jwt.keystore.password

Password used to access JWT keystore file.

  • Type: password
  • Importance: medium

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

Maximum number of tasks for the connector.

  • Type: int
  • Valid Values: [1,…,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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