Salesforce SObject Sink Connector for Confluent Cloud

The fully-managed Salesforce SObject Sink connector for Confluent Cloud performs CRUD operations (create, update, delete, and insert) on Salesforce SObject using data available from Apache Kafka® topics. This connector can be thought of as the inverse of the Salesforce PushTopic Source connector because it can operate on data created from the Salesforce PushTopic Source connector.

For example, there are two Salesforce.com organizations or Instances: Instance A and Instance B. A data engineer wants to synchronize Salesforce Lead objects from Instance A to Instance B. The engineer can configure and deploy the PushTopic Source connector to stream a Salesforce Lead from Instance A into a single Kafka topic, while the SObject Sink connector is configured to stream a Lead from the Kafka topic into Instance B. Depending upon the configuration, all changes to Lead SObject may be synchronized across organizations.

Note

This is a Quick Start for the fully-managed cloud connector. If you are installing the connector locally for Confluent Platform, see Salesforce SObject Sink Connector for Confluent Platform.

Features

The Salesforce SObject Sink connector provides the following features:

  • At least once delivery: This connector guarantees that records from the Kafka topic are delivered at least once.

  • Supports multiple tasks: The connector supports running one or more tasks. More tasks may improve performance (that is, consumer lag is reduced with multiple tasks running).

  • Automatically creates topics: The following three topics are automatically created when the connector starts:

    The suffix for each topic name is the connector’s logical ID. In the example below, there are the three connector topics and one pre-existing Kafka topic named pageviews.

    Salesforce SObject Sink Connector Topics

    Connector Topics

    If the records sent to the topic are not in the correct format, or if important fields are missing in the record, the errors are recorded in the error topic, and the connector continues to run.

  • Supported data formats: The connector supports Avro, JSON Schema (JSON-SR), and Protobuf input Kafka record value formats. Schema Registry must be enabled to use these Schema Registry-based formats.

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 Salesforce SObject Sink 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.
  • An authorized Salesforce user and credentials for the connector.
  • 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.
  • At least one source Kafka topic must exist in your Confluent Cloud cluster before creating the sink 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 SObject Sink connector card.

Salesforce SObject Sink Connector Card

Step 4: Enter the connector details

Note

  • Ensure you have all your prerequisites completed.
  • An asterisk ( * ) designates a required entry.

At the Add Salesforce SObject Sink Connector screen, complete the following:

If you’ve already populated your Kafka topics, select the topics you want to connect 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 endpoint.

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.

Tip

When you launch a connector, a Dead Letter Queue topic is automatically created. See Confluent Cloud Dead Letter Queue for details.

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": "SalesforceSObjectSink",
  "input.data.format": "AVRO",
  "name": "SalesforceSObjectSinkConnector_0",
  "kafka.auth.mode": "KAFKA_API_KEY",
  "kafka.api.key": "<my-kafka-api-key>",
  "kafka.api.secret": "<my-kafka-api-secret>",
  "salesforce.grant.type": "PASSWORD",
  "salesforce.username": "<username>",
  "salesforce.password": "<password>",
  "salesforce.password.token": "<password-token>",
  "salesforce.consumer.key": "<consumer-key>",
  "salesforce.consumer.secret": "<consumer-secret>",
  "salesforce.object": "<salesforce-SObject>",
  "tasks.max": "1",
  "topics": "orders",
}

Note the following property definitions:

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

  • "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.object": Enter the SObject name to write to.

  • "tasks.max": Enter the maximum number of tasks for the connector to use. More tasks may improve performance (that is, consumer lag is reduced with multiple tasks running).

  • "topics": Enter the topic name or a comma-separated list of topic names.

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 salesforce-SObject-sink-config.json

Example output:

Created connector SalesforceSObjectSinkConnector_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   | SalesforceSObjectSinkConnector_0 | RUNNING | sink |       |

Step 6: Check for records.

Verify that records are populating the endpoint.

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.

Tip

When you launch a connector, a Dead Letter Queue topic is automatically created. See Confluent Cloud Dead Letter Queue for details.

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.

Which topics do you want to get data from?

topics

Identifies the topic name or a comma-separated list of topic names.

  • Type: list
  • 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

Input messages

input.data.format

Sets the input Kafka record value format. Valid entries are AVRO, JSON_SR and PROTOBUF. Note that you need to have Confluent Cloud Schema Registry configured

  • Type: string
  • Importance: high

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

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.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: 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
salesforce.object

The Salesforce SObject to write to.

  • Type: string
  • Importance: high

Salesforce SObject properties

salesforce.object.override.event.type

A flag to indicate that the Kafka SObject source record EventType(create, update, delete) is overridden to use the operation specified in the SObject override operation field.

  • Type: boolean
  • Default: false
  • Importance: low
salesforce.sink.object.operation

The Salesforce sink operation to perform on the SObject. One of: insert, update, upsert, delete. Default is insert. This feature works if override.event.type is true.

  • Type: string
  • Default: insert
  • Importance: low
salesforce.ignore.fields

Comma separate list of fields from the source Kafka record to ignore when pushing a record into Salesforce.

  • Type: list
  • Default: “”
  • Importance: low
salesforce.ignore.reference.fields

Flag to prevent reference type fields from being updated or inserted in Salesforce SObjects.

  • Type: boolean
  • Default: false
  • Importance: low
salesforce.use.custom.id.field

Flag to use custom external id field in SObjects.

  • Type: boolean
  • Default: false
  • Importance: low
salesforce.custom.id.field.name

Name of a custom external id field in SObject to structure Rest Api calls for insert, upsert, delete, and update operations.

  • Type: string
  • Importance: low

Connection details

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
behavior.on.api.errors

Error handling behavior config for any API errors.

  • Type: string
  • Default: ignore
  • Importance: low

Consumer configuration

max.poll.interval.ms

The maximum delay between subsequent consume requests to Kafka. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 300000 milliseconds (5 minutes).

  • Type: long
  • Default: 300000 (5 minutes)
  • Valid Values: [60000,…,1800000] for non-dedicated clusters and [60000,…] for dedicated clusters
  • Importance: low
max.poll.records

The maximum number of records to consume from Kafka in a single request. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 500 records.

  • Type: long
  • Default: 500
  • Valid Values: [1,…,500] for non-dedicated clusters and [1,…] for dedicated clusters
  • Importance: low

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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