Salesforce Platform Event Sink Connector for Confluent Cloud¶

Salesforce platform events are user-defined publish-subscribe events. The fully-managed Salesforce Platform Event Sink connector for Confluent Cloud publishes platform events from Apache Kafka® topics to Salesforce.

The fully-managed Salesforce Platform Event Sink connector can be thought of as the inverse of the Platform Events Source connector. It is designed to read platform event records from a Kafka topic containing data streamed from the Platform Event Source connector. The connector then publishes this data as new platform events to the configured organization.

Note

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

Features¶

The Salesforce Platform Event Sink connector supports 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:
- Success topic
- Error topic
- Dead letter queue (DLQ) topic
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.

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 format 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.

For connector limitations, see Salesforce Platform Event Sink 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.

Data Fields¶

The UI configuration property Salesforce platform event name (CLI property salesforce.platform.event.name) designates the name of the event. Event names must end with __e. For example, MyPlatformEvent__e.

The connector only publishes data fields that are part of the Platform Event Definition (that is, data fields ending with __c). All other fields are ignored. If there are no fields in the message that have the required __c suffix, the entire message is not sent to Salesforce.

Note

The Platform Event Definition must exist in Salesforce before the connector can publish events to Salesforce. See the Salesforce Developer Guide for more information.

Quick Start¶

Use this quick start to get up and running with the Confluent Cloud Salesforce Platform Event 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.
An authorized Salesforce consumer key and secret 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 Platform Event Sink connector card.

Step 4: Set up the connection.¶

Note

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

At the Add Salesforce Platform Event Sink 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.

Add the Salesforce connection and authentication details:
- Salesforce grant type: Sets the authentication grant type to PASSWORD or JWT_BEARER (Salesforce JSON Web Token (JWT)). Defaults to PASSWORD.
- 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.
  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 password for the connector to use.
- 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: If using the grant type JWT_BEARER, upload the JWT keystore file.
- Salesforce JWT keystore password: Enter the password used to access the JWT keystore file.
Click Continue.

Select the Input Kafka record value format (data coming from the Kafka topic): AVRO, JSON_SR (JSON Schema), or PROTOBUF. A valid schema must be available in Schema Registry to use a schema-based message format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). See Schema Registry Enabled Environments for additional information.
Enter the Salesforce platform event name. This name is case sensitive.
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 What are schema contexts and when should you use them?.
- Connection timeout. The amount of time to wait in milliseconds (ms) when connecting to the Salesforce endpoint. The default is 30000 ms (30 seconds).
- Behavior on API errors: How the connector behaves when an Salesforce API error occurs. Valid options are fail and ignore (the default). If set to fail, the connector stops.
- Max Retry Time in Milliseconds: In case of error when making a request to Salesforce, the connector will retry until this time (in milliseconds) elapses.
- Transforms and Predicates: See the Single Message Transforms (SMT) documentation for details.
Click Continue.

See Configuration Properties for all property values and descriptions.

Step 5: Check the connector status¶

The status for the connector should go from Provisioning to Running.

Step 6: 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": "SalesforcePlatformEventSink",
  "input.data.format": "AVRO",
  "name": "SalesforcePlatformEventSinkConnector_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.platform.event.name": "<event-name>__e",
  "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
```

Important

If using a service account, you must add ACL entries. For standard service account ACL entries, see Sink connector service account. For the additional ACLs required for this connector, see Sink connector SUCCESS and ERROR topics.

"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.platform.event.name": The event name. This name is case sensitive.
"tasks.max": The connector supports running one or more tasks. 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-platform-event-sink-config.json

Example output:

Created connector SalesforcePlatformEventSinkConnector_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   | SalesforcePlatformEventSinkConnector_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.

Type: string
Default: https://login.salesforce.com
Importance: high

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.platform.event.name

The Salesforce platform event to publish to

Type: string
Importance: high

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 Salesforce 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.