Stripe Source Connector for Confluent Cloud

The fully managed Stripe Source connector for Confluent Cloud reads records from Stripe resources, such as charges, customers, invoices, and subscriptions, and streams them to Kafka topics. On first start, the connector loads records created at or after a start timestamp that you set, and then continuously captures new records and changes from Stripe events.

Note

If you require private networking for fully managed connectors, make sure to set up the proper networking beforehand. For more information, see Manage Networking for Confluent Cloud Connectors.

Features

The Stripe Source connector provides the following features:

Supported resources: Reads up to 29 Stripe resources, including accounts, application fees, balance transactions, charges, checkout sessions, coupons, credit notes, customers, disputes, events, invoices, payment intents, payouts, plans, prices, products, refunds, setup intents, subscriptions, and transfers. Select up to seven resources per connector in the stripe.resources property, using their Stripe API names, for example balance_transactions.
Initial load and change capture: On first start, the connector copies every record created at or after stripe.initial.start.timestamp. After that, it keeps polling Stripe for new records and reads changes from Stripe events.
Topic routing: Writes each resource’s records to <topic prefix><resource>, for example stripe-charges. For most resources, the connector also writes that resource’s Stripe events, such as customer.created, customer.updated, and customer.deleted, to <topic prefix><resource>_events.
Authentication: Authenticates with a Stripe secret key (sk_...) or restricted key (rk_...). The key determines whether the connector reads sandbox or live mode data. Confluent recommends that you use a restricted key.
Connected accounts: Reads one connected account’s data through your platform’s API key. Set stripe.connected.account.id to the account’s acct_... ID.
Data formats: Writes Avro, JSON Schema (JSON_SR), or Protobuf records with Schema Registry. With Avro, and with JSON_SR configured as described in the limitations, fields that Stripe adds later are added to the topic’s schema automatically in the default EVOLVE schema mode. Schema Registry must be enabled to use these formats. For the record value schema of each resource and its events topic, see Stripe Source Connector Record Schemas.
At least once delivery: The connector supports at least once delivery. After a restart or a pause, the connector continues from where it stopped. Custom offset management lets you load a resource again from the start timestamp. 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.

For connector limitations, see Stripe Source Connector limitations.
If you plan to use one or more Single Message Transforms (SMTs), see SMT Limitations. With the default EVOLVE schema mode, avoid SMTs that add, remove, rename, or retype a field. For details, see Schema evolution.
If you plan to use Confluent Cloud Schema Registry, see Limits for Fully Managed Connectors for Confluent Cloud.

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 Connect offsets API reference.

If a task fails because the last record the connector read for a resource is deleted at Stripe, or because the last event it read is older than Stripe’s 30-day event retention, update that resource’s offset to recover. For more information about this failure, see Stripe Source Connector.

Quick Start

Use this quick start to get up and running with the Confluent Cloud Stripe Source connector. The quick start provides the basics of selecting the connector and configuring it to stream events from Stripe resources to Kafka topics.

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). For more information, see Limits for Fully Managed Connectors for Confluent Cloud.
A Stripe account with a secret key (sk_...) or restricted key (rk_...). Confluent recommends that you use a restricted key with read access to each resource you select, and to events for resources that have an _events topic.
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

To create and launch a Kafka cluster in Confluent Cloud, see Create a kafka cluster in Confluent Cloud.

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 Stripe Source connector card.

Step 4: Enter the connector details

Note

Ensure you have all your prerequisites completed.
An asterisk ( * ) designates a required entry.

At the Add Stripe Source Connector screen, complete the following:

Kafka credentials

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.
Note

Freight clusters support only service accounts for Kafka authentication.
Click Continue.

Authentication

Configure the authentication properties:

Authentication
- Stripe API key: Your Stripe secret key or restricted key. Confluent recommends a restricted key with read access to the resources you select and to events. A sandbox key reads sandbox data, and a live mode key reads live data.
- Connected account ID: Leave this blank to read your own Stripe account, or enter a connected account ID, such as acct_1Nv0FGQ9RKHgCVdK, to read that account instead. Each connector reads one account, so create one connector per connected account.
Click Continue.

Configuration

Note

Configuration properties that are not shown in the Cloud Console use the default values. For all property values and definitions, see Configuration Properties.

Output messages

Select output record value format: Output Kafka record value format. Valid entries are AVRO, JSON_SR, or PROTOBUF. Set up Confluent Cloud Schema Registry for these schema-based message formats. With PROTOBUF, set the schema evolution mode to NONE.

Stripe resources

Stripe resources to sync: The Stripe resources to sync, up to seven per connector. To sync more, create another connector.
Load data created since: Load records created at or after this time, as a Unix timestamp in seconds. 0 loads all history. Stripe keeps change events for 30 days, so older changes are not loaded.

Show advanced configurations

Reporter Error Topic Name: The name of the topic to produce errant records after each unsuccessful API operation. Defaults to error-${connector} if not set. You can provide ${connector} in the value to use it as a placeholder for the logical cluster ID.
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?.

Polling configurations

Poll Interval (ms): How long, in milliseconds, the connector waits between requests to Stripe for each resource. This also sets how fast history loads, one page of up to 100 records per interval. Lower values load history faster and deliver changes sooner, but use more of your Stripe API rate limit and read allocation.

Additional Configs

Value Converter Decimal Format: Specifies the JSON or JSON_SR serialization format for Connect DECIMAL logical type values with two allowed literals: BASE64 to serialize DECIMAL logical types as base64 encoded binary data, and NUMERIC to serialize DECIMAL logical type values in JSON or JSON_SR as a number representing the decimal value.
Key Converter Schema ID Serializer: The class name of the schema ID serializer for keys. This is used to serialize schema IDs in the message headers.
Value Converter Reference Subject Name Strategy: Sets the subject reference name strategy for values. Valid entries are DefaultReferenceSubjectNameStrategy or QualifiedReferenceSubjectNameStrategy. You can use this strategy only with PROTOBUF format; the default strategy is DefaultReferenceSubjectNameStrategy.
Errors Tolerance: Use this property to configure the connector’s error handling behavior.

Warning

Use this property with caution for sink connectors, as it can lead to data loss. If you set this property to all, the connector does not fail on errant records, but logs them (and sends to DLQ for sink connectors) and continues processing. If you set this property to none, the connector task fails on errant records.
Value Converter Connect Meta Data: Enables the Connect converter to add its metadata to the output schema. Applies to Avro converters.
Value Converter Value Subject Name Strategy: Determines how to construct the subject name under which the value schema is registered with Schema Registry.
Key Converter Key Subject Name Strategy: Determines how to construct the subject name for key schema registration.
Value Converter Ignore Default For Nullables: When set to true, this property ensures that the corresponding record in Kafka is null, instead of showing the default column value. Applies to the AVRO, PROTOBUF, and JSON_SR converters.
Value Converter Schema ID Serializer: The class name of the schema ID serializer for values. This is used to serialize schema IDs in the message headers.

Auto-restart policy

Enable Connector Auto-restart: Enables the auto-restart behavior of the connector and its task in the event of user-actionable errors. Defaults to true, enabling the connector to automatically restart in case of user-actionable errors. Set this property to false to disable auto-restart for failed connectors. If disabled, you must manually restart the connector.

Output messages

Schema evolution mode: How the connector handles a field that Stripe returns but the connector does not know. EVOLVE adds it to the topic’s schema once, with its detected type. NONE adds it as an optional string, only in the records that carry it. With PROTOBUF, use NONE.

Transforms

Single Message Transformations: To add a new SMT, see Add transforms. For more information about unsupported SMTs, see Unsupported transformations.

For all property values and definitions, see Configuration Properties.

Click Continue.

Sizing

Based on the number of resources you select, the connector recommends a number of tasks.

To change the number of recommended tasks, enter the number of tasks for the connector to use in the Tasks field.
Click Continue.

Review and Launch

Verify the connection details.
Click Launch.

The status for the connector should go from Provisioning to Running.

Step 5: Check for records

Verify that records are populating the Kafka topics. Each selected resource writes its records to <topic prefix><resource>, for example stripe-charges, and, for most resources, writes that resource’s Stripe events to <topic prefix><resource>_events.

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.

Note

Make sure you have all your prerequisites completed.

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 required and optional connector properties.

{
  "name": "StripeSource_0",
  "config": {
    "connector.class": "StripeSource",
    "name": "StripeSource_0",
    "kafka.auth.mode": "KAFKA_API_KEY",
    "kafka.api.key": "<my-kafka-api-key>",
    "kafka.api.secret": "<my-kafka-api-secret>",
    "stripe.api.key": "<stripe-restricted-key>",
    "stripe.resources": "charges, customers, invoices",
    "stripe.initial.start.timestamp": "<unix-timestamp-seconds>",
    "topic.prefix": "stripe-",
    "output.data.format": "JSON_SR",
    "value.converter.object.additional.properties": "false",
    "tasks.max": "1"
  }
}

Note the following property definitions:

"name": Sets a name for your new connector.
"connector.class": Identifies the connector plugin name.
"stripe.api.key": Your Stripe secret key (sk_...) or restricted key (rk_...). The key determines whether the connector reads sandbox or live mode data.
"stripe.resources": A comma-separated list of Stripe resources to read, identified by their Stripe API names, for example balance_transactions.
"stripe.initial.start.timestamp": How far back to load history, as a Unix timestamp in seconds. The connector loads everything created at or after this instant, and then follows changes from that point on.
"topic.prefix": The prefix for the Kafka topics of every selected resource. With the default, stripe-, charges are written to stripe-charges and their changes to stripe-charges_events.
"output.data.format": Sets the output Kafka record value format. Valid entries are AVRO, JSON_SR, or PROTOBUF.
"value.converter.object.additional.properties": With JSON_SR, the default output format, set this property to false when you create the connector. Otherwise, the connector stops when Stripe adds a field to a selected resource.

"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
```

"tasks.max": Maximum tasks for the connector to use. Set it to a value no greater than the number of selected resources.

See Configuration Properties for all property values and descriptions.

Step 4: Load the configuration 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 stripe-source-config.json

Example output:

Created connector StripeSource_0 lcc-ix4dl

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-ix4dl   | StripeSource_0      | RUNNING | source

Step 6: Check for records

Verify that records are populating the Kafka topics for the resources you selected.

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.

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, whenever possible.

Type: string
Valid Values: SERVICE_ACCOUNT, KAFKA_API_KEY
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

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

Output messages

output.data.format

Output Kafka record value format: AVRO, JSON_SR, or PROTOBUF, each with Confluent Cloud Schema Registry. With PROTOBUF, set Schema evolution mode to NONE.

Type: string
Default: JSON_SR
Importance: high

schema.enforce

How the connector handles a field that Stripe returns but the connector doesn’t know. EVOLVE adds it to the topic’s schema once, with its detected type. NONE adds it as an optional string, only in the records that carry it. With PROTOBUF, use NONE.

Type: string
Default: EVOLVE
Importance: medium

Number of tasks for this connector

tasks.max

Maximum number of tasks for the connector.

Type: int
Valid Values: [1,…]
Importance: high

Authentication

stripe.api.key

Your Stripe secret key or restricted key. We recommend a restricted key with Read access to the resources you select and to Events. A sandbox key reads sandbox data, and a live mode key reads live data.

Type: password
Importance: high

stripe.connected.account.id

Leave blank to read your own Stripe account, or enter a connected account ID, such as acct_1Nv0FGQ9RKHgCVdK, to read that account instead. Each connector reads one account, so create one connector per connected account.

Type: string
Default: “”
Importance: medium

Stripe resources

stripe.resources

The Stripe resources to sync, up to 7 per connector. To sync more, create another connector.

Type: list
Importance: high

topic.prefix

Prefix for the Kafka topics of every selected resource. With the default, Charges are written to stripe-charges and their changes to stripe-charges_events.

Type: string
Default: stripe-
Valid Values: Must match the regex ^[a-zA-Z0-9._-]*$ and A string at most 200 characters long
Importance: medium

stripe.initial.start.timestamp

Load records created at or after this time, as a Unix timestamp in seconds. 0 loads all history. Stripe keeps change events for 30 days, so older changes are not loaded.

Type: string
Default: 0
Importance: high

Polling configurations

poll.interval.ms

How long, in milliseconds, the connector waits between requests to Stripe for each resource. This also sets how fast history loads, one page of up to 100 records per interval. Lower values load history faster and deliver changes sooner, but use more of your Stripe API rate limit and read allocation.

Type: int
Default: 10000 (10 seconds)
Valid Values: [1000,…]
Importance: medium

Reporter

reporter.error.topic.name

The name of the topic to produce errant records after each unsuccessful API operation. Defaults to ‘error-${connector}’ if not set. You can provide ${connector} in the value to use it as a placeholder for the logical cluster ID.

Type: string
Default: error-${connector}
Importance: low

Additional Configs

header.converter

The converter class for the headers. This is used to serialize and deserialize the headers of the messages.

Type: string
Importance: low

producer.override.compression.type

The compression type for all data generated by the producer. Valid values are none, gzip, snappy, lz4, and zstd.

Type: string
Importance: low

producer.override.linger.ms

The producer groups together any records that arrive in between request transmissions into a single batched request. More details can be found in the documentation: https://docs.confluent.io/platform/current/installation/configuration/producer-configs.html#linger-ms.

Type: long
Valid Values: [100,…,1000]
Importance: low

value.converter.allow.optional.map.keys

Allow optional string map key when converting from Connect Schema to Avro Schema. Applicable for Avro Converters.

Type: boolean
Importance: low

value.converter.auto.register.schemas

Specify if the Serializer should attempt to register the Schema.

Type: boolean
Importance: low

value.converter.connect.meta.data

Allow the Connect converter to add its metadata to the output schema. Applicable for Avro Converters.

Type: boolean
Importance: low

value.converter.enhanced.avro.schema.support

Enable enhanced schema support to preserve package information and Enums. Applicable for Avro Converters.

Type: boolean
Importance: low

value.converter.enhanced.protobuf.schema.support

Enable enhanced schema support to preserve package information. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.flatten.unions

Whether to flatten unions (oneofs). Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.generate.index.for.unions

Whether to generate an index suffix for unions. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.generate.struct.for.nulls

Whether to generate a struct variable for null values. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.int.for.enums

Whether to represent enums as integers. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.latest.compatibility.strict

Verify latest subject version is backward compatible when use.latest.version is true.

Type: boolean
Importance: low

value.converter.object.additional.properties

Whether to allow additional properties for object schemas. Applicable for JSON_SR Converters.

Type: boolean
Importance: low

value.converter.optional.for.nullables

Whether nullable fields should be specified with an optional label. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.optional.for.proto2

Whether proto2 optionals are supported. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.scrub.invalid.names

Whether to scrub invalid names by replacing invalid characters with valid characters. Applicable for Avro and Protobuf Converters.

Type: boolean
Importance: low

value.converter.use.latest.version

Use latest version of schema in subject for serialization when auto.register.schemas is false.

Type: boolean
Importance: low

value.converter.use.optional.for.nonrequired

Whether to set non-required properties to be optional. Applicable for JSON_SR Converters.

Type: boolean
Importance: low

value.converter.wrapper.for.nullables

Whether nullable fields should use primitive wrapper messages. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.wrapper.for.raw.primitives

Whether a wrapper message should be interpreted as a raw primitive at root level. Applicable for Protobuf Converters.

Type: boolean
Importance: low

errors.tolerance

Use this property if you would like to configure the connector’s error handling behavior. WARNING: This property should be used with CAUTION for SOURCE CONNECTORS as it may lead to dataloss. If you set this property to ‘all’, the connector will not fail on errant records, but will instead log them (and send to DLQ for Sink Connectors) and continue processing. If you set this property to ‘none’, the connector task will fail on errant records.

Type: string
Default: none
Importance: low

key.converter.key.schema.id.serializer

The class name of the schema ID serializer for keys. This is used to serialize schema IDs in the message headers.

Type: string
Default: io.confluent.kafka.serializers.schema.id.PrefixSchemaIdSerializer
Importance: low

key.converter.key.subject.name.strategy

How to construct the subject name for key schema registration.

Type: string
Default: TopicNameStrategy
Importance: low

value.converter.decimal.format

Specify the JSON/JSON_SR serialization format for Connect DECIMAL logical type values with two allowed literals:

BASE64 to serialize DECIMAL logical types as base64 encoded binary data and

NUMERIC to serialize Connect DECIMAL logical type values in JSON/JSON_SR as a number representing the decimal value.

Type: string
Default: BASE64
Importance: low

value.converter.flatten.singleton.unions

Whether to flatten singleton unions. Applicable for Avro and JSON_SR Converters.

Type: boolean
Default: false
Importance: low

value.converter.ignore.default.for.nullables

When set to true, this property ensures that the corresponding record in Kafka is NULL, instead of showing the default column value. Applicable for AVRO,PROTOBUF and JSON_SR Converters.

Type: boolean
Default: false
Importance: low

value.converter.reference.subject.name.strategy

Set the subject reference name strategy for value. Valid entries are DefaultReferenceSubjectNameStrategy or QualifiedReferenceSubjectNameStrategy. Note that the subject reference name strategy can be selected only for PROTOBUF format with the default strategy being DefaultReferenceSubjectNameStrategy.

Type: string
Default: DefaultReferenceSubjectNameStrategy
Importance: low

value.converter.value.schema.id.serializer

The class name of the schema ID serializer for values. This is used to serialize schema IDs in the message headers.

Type: string
Default: io.confluent.kafka.serializers.schema.id.PrefixSchemaIdSerializer
Importance: low

value.converter.value.subject.name.strategy

Determines how to construct the subject name under which the value schema is registered with Schema Registry.

Type: string
Default: TopicNameStrategy
Importance: low

Auto-restart policy

auto.restart.on.user.error

Enable connector to automatically restart on user-actionable errors.

Type: boolean
Default: true
Importance: medium

Next Steps

For an example that shows fully managed Confluent Cloud connectors in action with Confluent Cloud for Apache Flink, see the Cloud ETL Demo. This example also shows how to use Confluent CLI to manage your resources in Confluent Cloud.