Salesforce Platform Event Source Connector for Confluent Cloud¶

The fully-managed Salesforce Platform Event Source connector for Confluent Cloud provides a way to subscribe to Salesforce Platform Events and write them to an Apache Kafka® topic.

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 Source Connector for Confluent Platform.

Features¶

The Salesforce Platform Event Source connector provides the following features:

Uses the Salesforce streaming API: This connector uses the Salesforce Streaming API for Platform Events.
Set an initial start: Start consuming new platform events or start by consuming all events from the last 72 hours.
Client-side field level encryption (CSFLE) support: The connector supports CSFLE for sensitive data. For more information about CSFLE setup, see the connector configuration.
Supported data formats: The connector supports Avro, JSON Schema, Protobuf, or JSON (schemaless) output data. 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.
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 Managed and Custom Connectors section.

Limitations¶

Be sure to review the following information.

For connector limitations, see Salesforce Platform Event Source 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.

Considerations¶

Note the following when using the Salesforce Platform Events Source connector for Confluent Cloud:

The connector converts Kafka topic names to all lowercase letters. So, when adding ACLs for a topic, ensure you use the all-lowercase form of the topic name.

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:

Manage offsets using Confluent Cloud APIs. For more information, see Cluster API reference.

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": 120572741
           }
        }
     ],
    "metadata": {
        "observed_at": "2024-03-28T17:57:48.139635200Z"
    }
}

Responses include the following information:

replayId indicates the position of latest offset.
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.

To update the offset, make a POST request that specifies the environment, Kafka cluster, and connector name. Include a JSON payload that specifies new offset and a patch type.

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

 {
     "type": "PATCH",
      "offsets": [
         {
            "partition": {},
            "offset": {
            "replayId": 120572000
            }
         }
      ]
 }

Considerations:

You can only make one offset change at a time for a given connector.
This is an asynchronous request. To check the status of this request, you must use the check offset status API. For more information, see Get the status of an offset request.
For source connectors, the connector attempts to read from the position defined by the requested offsets.

Response:

Successful calls return HTTP 202 Accepted with a JSON payload that describes the offset.

{
    "id": "lcc-example123",
    "name": "{connector_name}",
    "offsets": [
        {
           "partition": {},
           "offset": {
           "replayId": 120572000
           }
        }
    ],
    "requested_at": "2024-03-28T17:58:45.606796307Z",
    "type": "PATCH"
}

Responses include the following information:

The requested position of the offsets in the source.
The time of the request to update the offset.
Information about the connector.

To delete the offset, make a POST request that specifies the environment, Kafka cluster, and connector name. Include a JSON payload that specifies the delete type.

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

{
  "type": "DELETE"
}

Considerations:

Delete requests delete the offset for the provided partition and reset to the base state. A delete request is as if you created a fresh new connector.
This is an asynchronous request. To check the status of this request, you must use the check offset status API. For more information, see Get the status of an offset request.
Do not issue delete and patch requests at the same time.
For source connectors, the connector attempts to read from the position defined in the base state.

Response:

Successful calls return HTTP 202 Accepted with a JSON payload that describes the result.

{
  "id": "lcc-example123",
  "name": "{connector_name}",
  "offsets": [],
  "requested_at": "2024-03-28T17:59:45.606796307Z",
  "type": "DELETE"
}

Responses include the following information:

Empty offsets.
The time of the request to delete the offset.
Information about Kafka cluster and connector.
The type of request.

To get the status of a previous offset request, 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/request/status
Host: https://api.confluent.cloud

Considerations:

The status endpoint always shows the status of the most recent PATCH/DELETE operation.

Response:

Successful calls return HTTP 200 with a JSON payload that describes the result. The following is an example of an applied patch.

{
   "request": {
      "id": "lcc-example123",
      "name": "{connector_name}",
      "offsets": [],
      "requested_at": "2024-03-28T17:58:45.606796307Z",
      "type": "DELETE"
   },
   "status": {
      "phase": "APPLIED",
      "message": "The Connect framework-managed offsets for this connector have been altered successfully. However, if this connector manages offsets externally, they will need to be manually altered in the system that the connector uses."
   },
   "previous_offsets": [
      {
         "partition": {},
         "offset": {
         "replayId": 120572741
         }
      }
   ],
   "applied_at": "2024-03-28T17:58:48.079141883Z"
}

Responses include the following information:

The original request, including the time it was made.
The status of the request: applied, pending, or failed.
The time you issued the status request.
The previous offsets. These are the offsets that the connector last updated prior to updating the offsets. Use these to try to restore the state of your connector if a patch update causes your connector to fail or to return a connector to its previous state after rolling back.

JSON payload¶

The table below offers a description of the unique fields in the JSON payload for managing offsets of the Salesforce Platform Event 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 Platform Event Source connector. The quick start provides the basics of selecting the connector and configuring it to subscribe to a Salesforce Platform Event.

Prerequisites

Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud.
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 topic must exist in your Confluent Cloud cluster before creating the connector.
The Salesforce account should have at least one Platform Event to subscribe to. You will need to know the security token, key, and secret used for the Salesforce account when setting up the connector.
For networking considerations, see Networking and DNS. To use a set of public egress IP addresses, see Public Egress IP Addresses for Confluent Cloud Connectors.

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 Platform Event 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 Platform Event 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.

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.

Add the following details:
- (Optional) Enable Client-Side Field Level Encryption for data encryption. Specify a Service Account to access the Schema Registry and associated encryption rules or keys with that schema. For more information on CSFLE setup, see Manage CSFLE for connectors.
- Select the output record value format (data going to the Kafka topic): AVRO, JSON, JSON_SR (JSON Schema), or PROTOBUF. Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON Schema, or Protobuf). See Schema Registry Enabled Environments for additional information.
- Salesforce platform event name: The Salesforce platform event name to subscribe to.
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?.
- Salesforce initial starting: Specify the initial starting point for the connector to use when consuming events. Use all to consume all events from the last 72 hours. Use latest* to consume only the events that arrive after the connector starts. This property defaults to latest.
- 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.
See Configuration Properties for all property values and definitions.
Click Continue.

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 Managed and Custom Connectors section.

Using the Confluent CLI¶

Complete the following steps to set up and run the connector using the Confluent CLI.

Important

Make sure you have all your prerequisites completed.
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: 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": "SalesforcePlatformEventSource",
  "name": "SalesforcePlatformEventSource_0",
  "kafka.auth.mode": "KAFKA_API_KEY",
  "kafka.api.key": "****************",
  "kafka.api.secret": "**********************************************",
  "kafka.topic": "testplatformevent",
  "salesforce.grant.type": "PASSWORD",
  "salesforce.username": "<my-username>",
  "salesforce.password": "**************",
  "salesforce.password.token": "************************",
  "salesforce.consumer.key": "******************************************",
  "salesforce.consumer.secret": "***************************************",
  "salesforce.platform.event.name": "TestEvent__e",
  "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 the name of the Kafka topic or topics. Note that Kafka topic names are converted to all lower case letters.
"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.
"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").

Note

(Optional) To enable CSFLE for data encryption, specify the following properties:

csfle.enabled: Flag to indicate whether the connector honors CSFLE rules.
sr.service.account.id: A Service Account to access the Schema Registry and associated encryption rules or keys with that schema.

For more information on CSFLE setup, see Manage CSFLE for connectors.

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-source.json

Example output:

Created connector SalesforcePlatformEventSource_0 lcc-aj3qr

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-aj3qr   | SalesforcePlatformEventSource_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 Managed and Custom Connectors 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.

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 subscribe to

Type: string
Importance: high

CSFLE¶

csfle.enabled

Determines whether the connector honours CSFLE rules or not

Type: boolean
Default: false
Importance: high

sr.service.account.id

Select the service account that has appropriate permissions to schemas and encryption keys in the Schema Registry.

Type: string
Importance: high

Connection details¶

salesforce.initial.start

Specify the initial starting point for the connector. Allowed values are

latest: only read events that arrive after the connector has started.

all: read all events including past events from the beginning of the Event Bus.

The default value is latest.

Type: string
Default: latest
Importance: medium

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

Output messages¶

output.data.format

Sets the output Kafka record value format. Valid entries are AVRO, JSON_SR, PROTOBUF, or JSON. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF

Type: string
Default: JSON
Importance: high

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.