Salesforce Bulk API Source Connector for Confluent Cloud¶
Note
If you are installing the connector locally for Confluent Platform, see Salesforce Bulk API Source Connector for Confluent Platform.
The Salesforce Bulk API Source connector for Confluent Cloud integrates Salesforce.com with Apache Kafka®. This connector pulls records and captures changes from Salesforce.com using the Salesforce Bulk Query API.
Features¶
The Salesforce Bulk API Source connector provides the following features:
- 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 Environment Limitations for additional information.
- Tasks per connector: Organizations can run multiple connectors with a limit of one task per connector (that is,
"tasks.max": "1"
). - Supported SObjects: See the following lists for supported and unsupported Salesforce objects. See Confluent Cloud connector limitations for additional information.
The following Salesforce objects are supported by this connector:
- Account
- Campaign
- CampaignMember
- Case
- Contact
- Contract
- Event
- Group
- Lead
- Opportunity
- OpportunityContactRole
- OpportunityLineItem
- Period
- PricebookEntry
- Product2
- Task
- TaskFeed
- TaskRelation
- User
- UserRole
The following Salesforce objects are not supported by this connector:
- Feed (for example, AccountFeed and AssetFeed, etc.)
- Share (for example, AccountBrandShare and ChannelProgramLevelShare, etc.)
- History (for example, AccountHistory, ActivityHistory, etc.)
- EventRelation (for example, AcceptedEventRelation, DeclinedEventRelation, etc.)
- AggregateResult
- AttachedContentDocument
- CaseStatus
- CaseTeamMember
- CaseTeamRole
- CaseTeamTemplate
- CaseTeamTemplateMember
- CaseTeamTemplateRecord
- CombinedAttachment
- ContentFolderItem
- ContractStatus
- EventWhoRelation
- FolderedContentDocument
- KnowledgeArticleViewStat
- KnowledgeArticleVoteStat
- LookedUpFromActivity
- Name
- NoteAndAttachment
- OpenActivity
- OwnedContentDocument
- PartnerRole
- RecentlyViewed
- ServiceAppointmentStatus
- SolutionStatus
- TaskPriority
- TaskStatus
- TaskWhoRelation
- UserRecordAccess
- WorkOrderLineItemStatus
- WorkOrderStatus
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 Bulk API 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 Environment Limitations.
Quick Start¶
Use this quick start to get up and running with the Salesforce Bulk API Source connector. The quick start provides the basics of selecting the connector and configuring it to capture records and record changes from Salesforce.
- Prerequisites
- Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud Platform (GCP).
- Salesforce account credentials.
- 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 Environment Limitations for additional information.
- At least one topic must exist in your Confluent Cloud cluster before creating the connector.
- For networking considerations, see Networking and DNS Considerations. To use static egress IPs, see Static Egress IP Addresses.
- 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 Apache Kafka using 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 3: Select your connector.¶
Click the Salesforce Bulk API Source connector icon.
Important
At least one topic must exist in your Confluent Cloud cluster before creating the connector.
Step 4: Set up the connection.¶
Complete the following steps and click Continue.
Note
- Make sure you have all your prerequisites completed.
- An asterisk ( * ) designates a required entry.
- Enter a connector name.
- 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).
- Add your Salesforce connection details.
- Salesforce instance is optional. If not entered, this property defaults to
https://login.salesforce.com
. The connector uses the endpoint specified in the authentication response from Salesforce. The remaining Salesforce credentials are required. - Salesforce credentials: Enter the username, password, and password token to authenticate with Salesforce.
- Salesforce Object is the SObject that the connector polls for new and changed records.
- Poll interval (ms) is optional. Enter a time in milliseconds (ms) that the connector waits before polling the SObject again. The default is
30000
ms (30 seconds). The maximum value allowed is300000
(5 minutes). - Enable Batching is optional. Enable batching to use PK Chunking for batching records. The default value is
false
. - Enter a Salesforce since date. The connector pulls data starting from this date. The required format is
yyyy-MM-dd
. - Max Retry Time in Milliseconds: If an error occurs when the connector makes a request to Salesforce, it retries until the time in milliseconds (ms) elapses. The default value is 30000 ms (30 seconds). The minimum value is 1000 ms (1 second).
- Salesforce instance is optional. If not entered, this property defaults to
- Select the Output Kafka record value format (data coming from the connector): AVRO, JSON (schemaless), 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 Environment Limitations for additional information.
- 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"
). - 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 by previewing the running configuration. Once you’ve validated that the properties are configured to your satisfaction, click Launch.
Tip
For information about previewing your connector output, see Connector Data Previews.
Step 6: Check the connector status.¶
The status for the connector should go from Provisioning to Running. It may take a few minutes.
Step 7: 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 section.
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.
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.
- 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 SalesforceBulkApiSource
Example output:
Following are the required configs:
connector.class: SalesforceBulkApiSource
name
kafka.auth.mode
kafka.api.key
kafka.api.secret
kafka.topic
salesforce.username
salesforce.password
salesforce.password.token
salesforce.object
output.data.format
tasks.max
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": "SalesforceBulkApiSource,
"name": "SalesforceBulkApiSource_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.username": "<my-username>",
"salesforce.password": "**************",
"salesforce.password.token": "************************",
"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
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
""kafka.topic"
: Enter a Kafka topic name. A topic must exist before launching the connector.""salesforce.<...>""
: Enter the required Salesforce connection details.""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 create --config <file-name>.json
For example:
confluent connect create --config salesforce-bulk-api-source.json
Example output:
Created connector SalesforceBulkApiSource_0 lcc-aj3qr
Step 5: Check the connector status.¶
Enter the following command to check the connector status:
confluent connect list
Example output:
ID | Name | Status | Type
+-----------+------------------------------+---------+-------+
lcc-aj3qr | SalesforceBulkApiSource_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 section.
Configuration Properties¶
Use the following configuration properties with this connector.
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
Which topic do you want to send data to?¶
kafka.topic
Identifies the topic name to write the data to.
- Type: string
- 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.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
batch.enable
Enable batching by applying PK-chunking. The default value is TRUE.
- Type: boolean
- Default: true
- Importance: low
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
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
- Importance: high
Number of tasks for this connector¶
tasks.max
- Type: int
- Valid Values: [1,…,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.