Salesforce Bulk API 2.0 Source Connector for Confluent Cloud

The fully-managed Salesforce Bulk API 2.0 Source connector for Confluent Cloud integrates Salesforce.com with Apache Kafka®. This connector pulls records and captures changes from Salesforce.com using Salesforce Bulk API 2.0.

Note

Features

The Salesforce Bulk API 2.0 Source connector provides the following features:

  • API 2.0: Supports Salesforce Bulk API 2.0.
  • At least once delivery: The connector guarantees that records are delivered at least once to the Kafka topic. If the connector restarts, there could be duplicate records in the Kafka topic.
  • 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 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": {
          "table": "Account"
        },
        "offset": {
          "jobId": "7505i00000Ug2TKAAZ",
          "locator": "null",
          "time": "2024-04-09T15:32:45Z"
        }
      }
    ],
    "metadata": {
        "observed_at": "2024-03-28T17:57:48.139635200Z"
    }
}

Responses include the following information:

  • jobId, locator, and time indicate the position of the 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.

JSON payload

The table below offers a description of the unique fields in the JSON payload for managing offsets of the Salesforce Bulk API 2.0 Source connector.

Field Definition Required/Optional
time

Represents the time of the last query to bulk API. When you reset the offset, the connector selects events with a time greater than and equal to the specified value in time. To update offsets, it is recommended that you only use a value in time and two double quotes ("") for jobID and locater.

Use the following format for time: yyyy-MM-dd'T'hh:mm:ss'Z'

 Required
jobId Unique ID for the bulk v2 query job. This field is not available in kafka records. Optional
locator Pointer to the next batch of records. This field is not available in kafka records. Optional

Quick Start

Use this quick start to get up and running with the Salesforce Bulk API 2.0 Source connector. The quick start provides the basics of selecting the connector and configuring it to capture records and record changes from Salesforce.

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 Bulk API 2.0 Source connector card.

Salesforce Bulk API 2.0 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 Bulk API 2.0 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.

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.

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": "SalesforceBulkApiV2Source,
  "name": "SalesforceBulkApiV2Source_0",
  "kafka.auth.mode": "KAFKA_API_KEY",
  "kafka.api.key": "<my-kafka-api-key>",
  "kafka.api.secret": "<my-kafka-api-secret>",
  "kafka.topic": "TestBulkAPI",
  "salesforce.grant.type": "PASSWORD",
  "salesforce.username": "<my-username>",
  "salesforce.password": "**************",
  "salesforce.password.token": "************************",
  "salesforce.consumer.key": "**************",
  "salesforce.consumer.secret": "************************",
  "salesforce.object": "<SObject-name>","
  "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. A topic must exist before launching the connector.

  • "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"": The SObject that the connector polls for new and changed records.

  • "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").

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-bulk-api-v2-source.json

Example output:

Created connector SalesforceBulkApiV2Source_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   | SalesforceBulkApiV2Source_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.

Note

These are properties for the fully-managed cloud connector that uses Salesforce Bulk API 2.0. If you are installing the fully-managed cloud connector that supports the original Salesforce Bulk Query API, see Salesforce Bulk API Source Connector for Confluent Cloud.

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.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 object to create topic for.

  • Type: string
  • Importance: high
poll.interval.ms

How often to query Salesforce for new records.

  • Type: int
  • Default: 30000 (30 seconds)
  • Valid Values: [8700,…,300000]
  • Importance: medium
salesforce.since

CreatedDate after which the records should be pulled. Note that the time is in UTC and has required format: yyyy-MM-dd.

  • Type: string
  • Importance: medium
result.max.rows

The maximum number of records to retrieve per set of results for the Bulk API 2.0 query. The default/max value is set to 1000

  • Type: int
  • Default: 1000
  • Valid Values: [1,…,1000]
  • Importance: medium

Connection details

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,…]
  • 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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