Salesforce Bulk API Source Connector for Confluent Cloud¶
The fully-managed 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.
Note
- This is a Quick Start for the fully-managed cloud connector. If you are installing the connector locally for Confluent Platform, see Salesforce Bulk API Source Connector for Confluent Platform.
- If you are using Salesforce Bulk API 2.0, see the Salesforce Bulk API 2.0 Source Connector for Confluent Cloud.
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 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"
). - 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 Managed and Custom Connectors 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 Schema Registry Enabled Environments.
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.
- 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 Schema Registry Enabled Environments 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. 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 Bulk API 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 Source Connector screen, complete the following:
- Select the way you want to provide Kafka Cluster credentials. You can
choose one of the following options:
- My account: This setting allows your connector to globally access everything that you have access to. With a user account, the connector uses an API key and secret to access the Kafka cluster. This option is not recommended for production.
- Service account: This setting limits the access for your connector by using a service account. This option is recommended for production.
- Use an existing API key: This setting allows you to specify an API key and a secret pair. You can use an existing pair or create a new one. This method is not recommended for production environments.
- Click Continue.
- Add the Salesforce connection and authentication details:
- 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 to use.
- Salesforce password: The Salesforce password the connector to use.
- Salesforce password token: The Salesforce security token associated with the username.
- Click Continue.
Add the following details:
- 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). For additional information, see Schema Registry Enabled Environments.
- Salesforce Object: The Salesforce object to create a topic for.
- Salesforce since:
CreatedDate
after which the records should be pulled. The time is in UTC and has the required format:yyyy-MM-dd
.
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?.
Poll interval (ms)t: How often to query Salesforce for new records.
Enable batching: Enable batching to use PK Chunking for batching records. The default value is
false
.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: For details, see the Single Message Transforms (SMT) documentation.
For all property values and definitions, see Configuration Properties.
Click Continue.
Based on the number of topic partitions you select, you will be provided with a recommended number of tasks.
- To change the number of tasks, use the Range Slider to select the desired number of tasks.
- Click Continue.
Verify the connection details by previewing the running configuration.
Tip
For information about previewing your connector output, see Confluent Cloud Connector Data Previews.
After you’ve validated that the properties are configured to your satisfaction, click Launch.
The status for the connector should go from Provisioning to Running.
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": "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 cluster create --config-file <file-name>.json
For example:
confluent connect cluster create --config-file 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 cluster 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 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.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
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
batch.enable
Enable batching by applying PK-chunking. The default value is TRUE.
- Type: boolean
- Default: true
- Importance: low
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.