Salesforce Platform Event Sink Connector for Confluent Cloud¶
Note
If you are installing the connector locally for Confluent Platform, see Salesforce Platform Event Sink Connector for Confluent Platform.
Salesforce platform events are user-defined publish-subscribe events. The full-managed Salesforce Platform Event Sink connector publishes platform events from Apache Kafka® topics to Salesforce.
The 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.
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 Connect 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 Platform (GCP).
- 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 Data integration, and then click Connectors. If you already have connectors in your cluster, click + Add connector.
Step 4: Set up the connection.¶
Note
- Make sure you have all your prerequisites completed.
- An asterisk ( * ) designates a required entry.
Select one or more topics.
Enter a connector Name.
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.
Select the way you want to provide Kafka Cluster credentials. You can either select a service account resource ID or you can enter an API key and secret (or generate these in the Cloud Console).
Enter the Salesforce connection details. For more information about Salesforce authentication details and what they mean, see Connected App and OAuth Terminology.
Note
The Salesforce Platform Event Name is case sensitive.
Enter the Connection timeout. The amount of time to wait in milliseconds (ms) when connecting to the Salesforce endpoint. The default is 30000 ms (30 seconds).
Enter the number of tasks to use with the connector. More tasks may improve performance.
Transforms and Predicates: See the Single Message Transforms (SMT) documentation for details.
See Configuration Properties for all property values and descriptions.
Step 5: Launch the connector.¶
Verify the connection details and click Launch.
Step 6: Check the connector status.¶
The status for the connector should go from Provisioning to Running.
Step 7: 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 Connect section.
Tip
When you launch a connector, a Dead Letter Queue topic is automatically created. See 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.
- The example commands use Confluent CLI version 2. For more information see, Confluent CLI v2.
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 SalesforcePlatformEventSink
Example output:
Following are the required configs:
connector.class: SalesforcePlatformEventSink
input.data.format
name
kafka.auth.mode
kafka.api.key
kafka.api.secret
salesforce.username
salesforce.password
salesforce.password.token
salesforce.consumer.key
salesforce.consumer.secret
salesforce.platform.event.name
tasks.max
topics
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.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
orKAFKA_API_KEY
(the default). To use an API key and secret, specify the configuration propertieskafka.api.key
andkafka.api.secret
, as shown in the example configuration (above). To use a service account, specify the Resource ID in the propertykafka.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.<...>
Required Salesforce connection details. For more information about Salesforce authentication details and what they mean, see Connected App and OAuth Terminology.Note
The
salesforce.platform.event.name
is case sensitive."tasks.max"
: This connector supports one task only."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 create --config <file-name>.json
For example:
confluent connect create --config 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 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 Connect section.
Tip
When you launch a connector, a Dead Letter Queue topic is automatically created. See Dead Letter Queue for details.
Configuration Properties¶
Use the following configuration properties with this connector.
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
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
- 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
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.
- 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: high
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
Number of tasks for this connector¶
tasks.max
- Type: int
- Valid Values: [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.