Amazon DocumentDB Sink Connector for Confluent Cloud

The fully-managed Amazon DocumentDB Sink connector for Confluent Cloud maps and persists events from Apache Kafka® topics directly to a DocumentDB database collection. The connector supports AVRO, JSON Schema, PROTOBUF, JSON (schemaless) or STRING data from Apache Kafka® topics. The connector ingests events from Kafka topics directly into a DocumentDB database, exposing the data to services for querying, enrichment, and analytics.

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 connector provides the following features:

Collections: Collections can be auto-created based on topic names.
Database authentication: The connector supports both username/password-based and AWS IAM role based authentication, through the provider integration framework. For more information DocumentDB authentication setup, see connector authentication.
Input data formats: The connector supports AVRO, JSON Schema, PROTOBUF, JSON (schemaless) or STRING input data formats. 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 Schema Registry Enabled Environments.
Offset management capabilities: The connector supports offset management. For more information, see Manage custom offsets.
Multiple tasks: The connector supports running one or more tasks. More tasks may improve performance.
Client-side encryption (CSFLE and CSPE) support: The connector supports CSFLE and CSPE for sensitive data. For more information about CSFLE or CSPE setup, see the connector configuration.
Dead letter queue (DLQ) support: The connector supports DLQ and routes invalid records to DLQ when configured.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.

Note

The connector is compatible with Amazon DocumentDB engine versions 4.0, 5.0, and 8.0. It does not support connections to Amazon DocumentDB elastic clusters.

Limitations

Be sure to review the following information.

For connector limitations, see Amazon DocumentDB Sink 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 Confluent Cloud Amazon DocumentDB Sink connector. The quick start provides the basics of selecting the connector and configuring it to consume data from Kafka and persist the data to a DocumentDB database.

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 Schema Registry Enabled Environments.
Access to a DocumentDB cluster located in the same region as your Kafka cluster.
For private networking setup, see Private networking setup.
Generate a valid truststore file using the AWS Truststore script.

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.

Private networking setup

Review the following networking requirements and resources:

For general networking considerations, see Networking and DNS.
To use a set of public egress IP addresses, see Public Egress IP Addresses for Confluent Cloud Connectors.
Private networking is only supported for Kafka clusters running on AWS. If your cluster is in another cloud provider, you must use a public endpoint for the DocumentDB cluster.
To enable cross-cloud connectivity, contact Confluent Support. When enabled, the connector must use the tlsAllowInvalidHostnames property to connect to the DocumentDB cluster.

Amazon DocumentDB does not allow external network connections from the internet. To connect to DocumentDB, use one of the following private networking methods:

VPC peering (recommended): Follow the steps in Use AWS VPC Peering with Confluent Cloud to set up a VPC peering connection. For DNS forwarding, use the domain docdb.amazonaws.com.
Egress PrivateLink endpoints: Follow the steps in Egress PrivateLink Endpoints Setup Guide: DocumentDB on AWS for Confluent Cloud to configure a PrivateLink endpoint. The DocumentDB cluster and the Kafka cluster must reside in the same region.

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 Amazon DocumentDB Sink 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 Amazon DocumentDB Sink Connector screen, complete the following:

Topic selection

If you’ve already populated your Kafka topics, select the topics you want to connect from the Topics list.

To create a new topic, click +Add new topic.

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:
DocumentDB connection
- Connection host: The host name and port of the AWS DocumentDB cluster. Expected format hostname:port.
Authentication method
- Authentication method: Choose an authentication mechanism for DocumentDB. Use SCRAM for username/password authentication, or IAM Roles.
- Provider Integration: Select an existing integration that has access to your resource. In case you need to integrate a new IAM role, use provider integration
- Connection user: DocumentDB connection user.
- Connection password: DocumentDB connection password.
DocumentDB Database Details
- Database name: DocumentDB database name.
- Collection name: DocumentDB collection name.
TLS Configuration
- TLS: Whether TLS is enabled on the cluster.
- SSL truststore file: The trust store file containing trusted certificates in JKS format. This is required when TLS is enabled.
- SSL truststore password: The password for the trust store file.
Click Continue.

Configuration

Note

See Configuration Properties for all property values and definitions.

Input Kafka record value format: Sets the input 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.

Data decryption

Enable Client-Side Field Level Encryption for data decryption. Specify a Service Account to access the Schema Registry and associated encryption rules or keys with that schema. Select the connector behavior (ERROR or NONE) on data decryption failure. If set to ERROR, the connector fails and writes the encrypted data in the DLQ. If set to NONE, the connector writes the encrypted data in the target system without decryption. For more information on CSFLE or CSPE setup, see Manage encryption for connectors.

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?.
Input Kafka record key format: Sets the input Kafka record key format. Valid entries are AVRO, BYTES, JSON, JSON_SR, PROTOBUF, or STRING. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF

Additional Configs

Value Converter Replace Null With Default: Whether to replace fields that have a default value and that are null to the default value. When set to true, the default value is used, otherwise null is used. Applicable for JSON Converter.
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.
Value Converter Schemas Enable: Include schemas within each of the serialized values. Input messages must contain schema and payload fields and may not contain additional fields. For plain JSON data, set this to false. Applicable for JSON Converter.
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.
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.
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.
Value Converter Connect Meta Data: Allow the Connect converter to add its metadata to the output schema. Applicable for 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: How to construct the subject name for key schema registration.

Auto-restart policy

Enable Connector Auto-restart: Control 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. In such cases, you would need to manually restart the connector.

Consumer configuration

Max poll interval(ms): Set the maximum delay between subsequent consume requests to Kafka. Use this property to improve connector performance in cases when the connector cannot send records to the sink system. The default is 300,000 milliseconds (5 minutes).
Max poll records: Set the maximum number of records to consume from Kafka in a single request. Use this property to improve connector performance in cases when the connector cannot send records to the sink system. The default is 500 records.

Writes

Write Model Strategy: The class that specifies the WriteModel to use for bulk writes.
Max batch size: The maximum number of sink records to possibly batch together for processing.
Use ordered bulk writes: Whether the batches controlled by ‘max.batch.size’ must be written via ordered bulk writes.
Rate limiting timeout: How long in ms processing should wait before continuing after triggering a rate limit.
Rate limiting batch number: The number of processed batches that will trigger rate limiting. The default value of 0 sets no rate limiting.
Delete on null values: Whether or not the connector should try to delete documents based on key when value is null.

ID strategies

Document ID strategy: The IdStrategy class name to use for generating a unique document id (_id).

Namespace mapping

Namespace mapper class: The class that determines the namespace to write the sink data to. By default this will be based on the ‘database’ configuration and either the topic name or the ‘collection’ configuration.
Key field for destination database name: The key field to use as the destination database name.
Key field for destination collection name: The key field to use as the destination collection name.
Value field for destination database name: The value field to use as the destination database name.
Value field for destination collection name: The value field to use as the destination collection name.
Mapped field error: Whether to throw an error if the mapped field is missing or invalid. Defaults to false.

Error handling

Error tolerance: Use this property if you would like to configure the connector’s error handling behavior differently from the Connect framework’s.

Transforms

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

Processing position

Set offsets: Click Set offsets to define a specific offset for this connector to begin procession data from. For more information on managing offsets, see Manage offsets.

Click Continue.

Sizing

Based on the number of topic partitions you select, you will be provided with a recommended number of tasks. One task can handle up to 100 partitions.

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

Review the configuration summary and verify the following:

Verify the connection details and click Launch.

Step 5: Check Amazon DocumentDB

After the connector is running, verify that messages are populating your Amazon DocumentDB database.

Tip

When you launch a connector, a Dead Letter Queue topic is automatically created. See View Connector Dead Letter Queue Errors in Confluent Cloud for details.

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 the required connector properties.

{
    "connector.class": "AmazonDocumentDBSink",
    "name": "confluent-documentdb-sink",
    "kafka.auth.mode": "KAFKA_API_KEY",
    "kafka.api.key": "<my-kafka-api-key>",
    "kafka.api.secret": "<my-kafka-api-secret>",
    "input.data.format" : "JSON",
    "connection.host": "<database-host-address>",
    "connection.user": "<my-username>",
    "connection.password": "<my-password>",
    "topics": "<kafka-topic-name>",
    "database": "<database-name>",
    "collection": "<collection-name>",
    "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
```

"input.data.format": Sets the input Kafka record value format (data coming from the Kafka topic). Valid entries are AVRO, JSON_SR, PROTOBUF, JSON, or STRING. You must have Confluent Cloud Schema Registry configured if using a schema-based message format (for example, AVRO, JSON_SR (JSON Schema), or PROTOBUF).
"connection.host": The DocumentDB host with connection string options. Use a hostname address and not a full URL. For example, use example.cluster-example.us-west-2.docdb.amazonaws.com:27017. The port number is optional and defaults to 27017.

Note

The connector does not support following connection string options in connection.host configuration property: tlsCertificateKeyFile, tlsCertificateKeyFilePassword, tlsCAFile, tlsAllowInvalidCertificates, tlsInsecure, tlsAllowInvalidHostnames, authMechanism, authMechanismProperties, gssapiServiceName.
Other options like readPreference, readConcernLevel, or w defined in Connection String Options can be configured in connection.host configuration property. For example, example.cluster-example.us-west-2.docdb.amazonaws.com:27017/?readPreference=secondary&readConcernLevel=local&appName=test&w=majority.

"collection": The DocumentDB collection name. For multiple topics, this is the default collection the topics are mapped to.

The following are optional (with the exception of the number of tasks).

"doc.id.strategy": Sets the strategy to generate a unique document ID (_id). Enter the strategy to generate a unique document ID (_id). Valid entries are BsonOidStrategy, KafkaMetaDataStrategy, FullKeyStrategy, PartialKeyStrategy, PartialValueStrategy, ProvidedInKeyStrategy, ProvidedInValueStrategy, or UuidStrategy. To delete the document when the value is null, you must set the strategy to FullKeyStrategy, PartialKeyStrategy, or ProvidedInKeyStrategy. The default value is BsonOidStrategy. For more information, see DocumentIdAdder.
"write.strategy": Sets the write model for bulk write operations. Valid entries are DefaultWriteModelStrategy, ReplaceOneDefaultStrategy, InsertOneDefaultStrategy or UpdateOneDefaultStrategy. If not used, this property defaults to DefaultWriteModelStrategy. For detailed information about each write strategy, see Strategies.
Enter the number of tasks for the connector. For more information, see Confluent Cloud connector limitations.

Note

To enable CSFLE or CSPE for data encryption, specify the following properties:

csfle.enabled: Flag to indicate whether the connector honors CSFLE or CSPE rules.
sr.service.account.id: A Service Account to access the Schema Registry and associated encryption rules or keys with that schema.
csfle.onFailure: Configures the connector behavior (ERROR or NONE) on data decryption failure. If set to ERROR, the connector fails and writes the encrypted data in the DLQ. If set to NONE, the connector writes the encrypted data in the target system without decryption.

When using CSFLE or CSPE with connectors that route failed messages to a Dead Letter Queue (DLQ), be aware that data sent to the DLQ is written in unencrypted plaintext. This poses a significant security risk as sensitive data that should be encrypted may be exposed in the DLQ.

Do not use DLQ with CSFLE or CSPE in the current version. If you need error handling for CSFLE- or CSPE-enabled data, use alternative approaches such as:

Setting the connector behavior to ERROR to throw exceptions instead of routing to DLQ
Implementing custom error handling in your applications
Using NONE to pass encrypted data through without decryption

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

Single Message Transforms: For more information about adding SMTs using the CLI, see the Single Message Transforms (SMT).

For all property values and definitions, see Configuration Properties.

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 amazon-document-db-sink.json

Example output:

Created connector confluent-documentdb-sink 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   | confluent-documentdb-sink  | RUNNING | sink

Step 6: Check DocumentDB

After the connector is running, verify that records are populating your DocumentDB database.

Tip

When you launch a connector, a Dead Letter Queue topic is automatically created. See View Connector Dead Letter Queue Errors in Confluent Cloud for details.

Configuration Properties

Use the following configuration properties with the fully-managed 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

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

Input messages

input.data.format

Sets the input 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

input.key.format

Sets the input Kafka record key format. Valid entries are AVRO, BYTES, JSON, JSON_SR, PROTOBUF, or STRING. 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: STRING
Valid Values: AVRO, BYTES, JSON, JSON_SR, PROTOBUF, STRING
Importance: high

Writes

max.batch.size

The maximum number of sink records to possibly batch together for processing.

Type: int
Default: 0
Valid Values: [0,…]
Importance: low

rate.limiting.timeout

How long in ms processing should wait before continuing after triggering a rate limit.

Type: int
Default: 0
Importance: low

bulk.write.ordered

Whether the batches controlled by ‘max.batch.size’ must be written via ordered bulk writes.

Type: boolean
Default: true
Importance: low

rate.limiting.every.n

The number of processed batches that will trigger rate limiting. The default value of 0 sets no rate limiting.

Type: int
Default: 0
Importance: low

write.strategy

The class that specifies the WriteModel to use for bulk writes.

Type: string
Default: DefaultWriteModelStrategy
Valid Values: DefaultWriteModelStrategy, InsertOneDefaultStrategy, ReplaceOneDefaultStrategy, UpdateOneDefaultStrategy
Importance: low

delete.on.null.values

Whether or not the connector should try to delete documents based on key when value is null.

Type: boolean
Default: false
Importance: low

ID strategies

doc.id.strategy

The IdStrategy class name to use for generating a unique document id (_id).

Type: string
Default: BsonOidStrategy
Importance: low

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

Which topics do you want to get data from?

topics.regex

A regular expression that matches the names of the topics to consume from. This is useful when you want to consume from multiple topics that match a certain pattern without having to list them all individually.

Type: string
Importance: low

topics

Identifies the topic name or a comma-separated list of topic names.

Type: list
Importance: high

errors.deadletterqueue.topic.name

The name of the topic to be used as the dead letter queue (DLQ) for messages that result in an error when processed by this sink connector, or its transformations or converters. Defaults to ‘dlq-${connector}’ if not set. The DLQ topic will be created automatically if it does not exist. You can provide ${connector} in the value to use it as a placeholder for the logical cluster ID.

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

How should we connect to your Amazon DocumentDB database?

connection.host

The host name and port of the AWS DocumentDB cluster. Expected format hostname:port.

Type: string
Default: “”
Importance: high

authentication.method

Choose an authentication mechanism for DocumentDB. Use SCRAM for username/password authentication, or IAM Roles.

Type: string
Default: SCRAM
Valid Values: IAM Roles, SCRAM
Importance: high

connection.user

DocumentDB connection user.

Type: string
Importance: high

provider.integration.id

Select an existing integration that has access to your resource. In case you need to integrate a new IAM role, use provider integration

Type: string
Importance: high

connection.password

DocumentDB connection password.

Type: password
Importance: high

database

DocumentDB database name.

Type: string
Importance: high

collection

DocumentDB collection name.

Type: string
Importance: medium

connection.tls.enabled

Whether TLS is enabled on the cluster.

Type: boolean
Default: true
Importance: high

connection.ssl.truststore.file

The trust store file containing trusted certificates in JKS format. This is required when TLS is enabled.

Type: password
Default: [hidden]
Importance: medium

connection.ssl.truststorePassword

The password for the trust store file.

Type: password
Default: [hidden]
Importance: medium

Namespace mapping

namespace.mapper.class

The namespace mapper specifies which database or collection to sink the data to. The default DefaultNamespaceMapper uses values specified in the database and collection properties. If you configure your sink connector to use the FieldPathNamespaceMapper, you can specify which database and collection to sink a document based on the data’s field values.

Type: string
Default: DefaultNamespaceMapper
Importance: low

namespace.mapper.key.database.field

The key field to use as the destination database name, when using FieldPathNamespaceMapper

Type: string
Importance: low

namespace.mapper.key.collection.field

The key field to use as the destination collection name, when using FieldPathNamespaceMapper

Type: string
Importance: low

namespace.mapper.value.database.field

The value field to use as the destination database name, when using FieldPathNamespaceMapper

Type: string
Importance: low

namespace.mapper.value.collection.field

The value field to use as the destination collection name, when using FieldPathNamespaceMapper

Type: string
Importance: low

namespace.mapper.error.if.invalid

Whether to throw an error if the mapped field is missing or invalid. Defaults to false, in which case the connector falls back to the database and collection configuration properties. When set to true, the connector does not process documents missing the mapped field or that contain an invalid BSON type. The connector may halt or skip processing depending on the related error-handling configuration settings.

Type: boolean
Default: false
Importance: low

Error handling

documentdb.errors.tolerance

Use this property if you would like to configure the connector’s error handling behavior differently from the Connect framework.

Type: string
Default: ALL
Valid Values: ALL, NONE
Importance: medium

Consumer configuration

max.poll.interval.ms

The maximum delay between subsequent consume requests to Kafka. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 300000 milliseconds (5 minutes).

Type: long
Default: 300000 (5 minutes)
Valid Values: [60000,…,1800000] for non-dedicated clusters and [60000,…] for dedicated clusters
Importance: low

max.poll.records

The maximum number of records to consume from Kafka in a single request. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 500 records.

Type: long
Default: 500
Valid Values: [1,…,500] for non-dedicated clusters and [1,…] for dedicated clusters
Importance: low

Number of tasks for this connector

tasks.max

Maximum number of tasks for the connector.

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

Additional Configs

consumer.override.auto.offset.reset

Defines the behavior of the consumer when there is no committed position (which occurs when the group is first initialized) or when an offset is out of range. You can choose either to reset the position to the “earliest” offset (the default) or the “latest” offset. You can also select “none” if you would rather set the initial offset yourself and you are willing to handle out of range errors manually. More details: https://docs.confluent.io/platform/current/installation/configuration/consumer-configs.html#auto-offset-reset

Type: string
Importance: low

consumer.override.isolation.level

Controls how to read messages written transactionally. If set to read_committed, consumer.poll() will only return transactional messages which have been committed. If set to read_uncommitted (the default), consumer.poll() will return all messages, even transactional messages which have been aborted. Non-transactional messages will be returned unconditionally in either mode. More details: https://docs.confluent.io/platform/current/installation/configuration/consumer-configs.html#isolation-level

Type: string
Importance: low

header.converter

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

Type: string
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: all
Importance: low

key.converter.key.subject.name.strategy

How to construct the subject name for key schema registration.

Type: string
Default: TopicNameStrategy
Importance: low

key.converter.replace.null.with.default

Whether to replace fields that have a default value and that are null to the default value. When set to true, the default value is used, otherwise null is used. Applicable for JSON Key Converter.

Type: boolean
Default: true
Importance: low

key.converter.schemas.enable

Include schemas within each of the serialized keys. Input message keys must contain schema and payload fields and may not contain additional fields. For plain JSON data, set this to false. Applicable for JSON Key Converter.

Type: boolean
Default: false
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.replace.null.with.default

Whether to replace fields that have a default value and that are null to the default value. When set to true, the default value is used, otherwise null is used. Applicable for JSON Converter.

Type: boolean
Default: true
Importance: low

value.converter.schemas.enable

Include schemas within each of the serialized values. Input messages must contain schema and payload fields and may not contain additional fields. For plain JSON data, set this to false. Applicable for JSON Converter.

Type: boolean
Default: false
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.