Redis Kafka Sink Connector for Confluent Cloud

The fully-managed Redis Kafka Sink connector for Confluent Cloud maps and writes records from Apache Kafka® topics directly to a Redis database. The connector supports AVRO, BYTES, JSON, JSON Schema, PROTOBUF, and STRING data formats from Apache Kafka® topics. The connector reads records from a Kafka topic and writes them to Redis., making the data available for querying, enrichment, and analytics.

Features

The fully-managed Redis Kafka Sink connector provides the following features:

At least once delivery: The connector guarantees that records are written at least once to Redis.
Database authentication: The connector supports password-based authentication.
Compatibility: The connector supports Redis-compatible databases, including AWS Valkey and AWS MemoryDB.
Redis data structure: The connector supports STREAM, LIST, SET, ZSET, STRING, HASH, TIMESERIES, JSON Redis data-structure types as targets.
Client-side field level encryption (CSFLE) support: The connector supports CSFLE for sensitive data. For more information about CSFLE setup, see the connector configuration.
Input data formats: The connector accepts AVRO, BYTES, JSON, JSON_SR (JSON Schema), PROTOBUF, or STRING input data formats for record keys and values. 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.
Time to live (TTL) support: The connector supports allows you to set a TTL for Redis keys to automatically expire data after a specified duration.
Multiple tasks: The connector supports running one or more tasks. More tasks may improve performance.

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 Redis Kafka Sink 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 Redis Kafka 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 Redis Kafka 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. For more information, 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 Redis Kafka database.
The Redis Kafka database service endpoint and the Kafka cluster must be in the same region.
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 Redis Kafka 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 Redis Kafka 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

Add the following database connection details:

Connection credentials
- Redis host: The IP address or hostname of the Redis database server.
- Redis port: The port number used to connect to Redis database server.
- Redis database index: The numerical index of the Redis database you want to write data to.
- Redis username: The username of the Redis user connecting to the Redis database server.
- Redis password: The password of the Redis user connecting to the Redis database server.
TLS configuration
- Enable TLS: Specify whether to use Transport Layer Security (TLS) to connect to the Redis database. Defaults to false.
- CA certificate file: If you set Enable TLS property to true, upload the CA certificate file. The connector uses a TLS-encrypted connection and verifies the server’s TLS certificate against the configured Certificate Authority (CA) certificates. You can use this with or without client certificates.
Client certificate authentication
- Private Key File: Upload the private key file in PEM format. Use this file along with the certificate file for client certificate authentication.
- Certificate File: Upload the certificate file in PEM format. Use this file along with the private key file for client certificate authentication.
- Key password: Specify the password of the private key file if it is password-protected.
Click Continue.

Configuration

Note

See Configuration Properties for all property values and definitions.

Configure the following:
- Redis data type: Defines the destination Redis data structure. Valid entries are STREAM, LIST, SET, ZSET, STRING, HASH, TIMESERIES, JSON. Note that multi/exec transactions only work with STREAM, LIST, SET, or ZSET data types.
- Input Kafka record value format: Select the input Kafka record value format (data coming from the Kafka topic). Valid entires are AVRO, BYTES, JSON, JSON_SR (JSON Schema), PROTOBUF, or STRING. A valid schema must be available in Schema Registry to use a schema-based message format (for example, AVRO, JSON_SR, or PROTOBUF). See Schema Registry Enabled Environments for additional information.
- Input Kafka record key format: Select the input Kafka record key format. Valid entires are AVRO, BYTES, JSON, JSON_SR (JSON Schema), PROTOBUF, or STRING. A valid schema must be available in Schema Registry to use a schema-based message format (for example, AVRO, JSON_SR, or PROTOBUF).
Configuration
- Key space: A format string for the destination key space. It may contain ${topic} as a placeholder for the originating topic name. For example, kafka_${topic} for the topic orders maps to the Redis key space kafka_orders.
- Key separator: Species the separator for non-collection destination keys.
- Key TTL: The time to live (in seconds) for the key. If not set (default -1), the record will not expire.
  
  You can set a TTL for individual records by including a redis.key.ttl header in your Kafka message. When present, this record-level TTL header takes precedence over the global configuration.
- Use multi/exec transactions: Specifies whether to execute Redis commands in multi/exec transactions. This option only works with STREAM, LIST, SET, ZSET data types.
- Wait for replicas: The number of replicas to wait for. Use 0 to disable waiting for replicas.
- Character set: Specifies the character set to encode Redis key and value strings. This must be a valid charset name.
Data encryption
- (Optional) 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 setup, see Manage CSFLE 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?.
- Command timeout: Set the Redis command timeout in seconds. Defaults to 60.
- Connection pool size: Specify the maximum number of connections in the pool. Defaults to 8.
- Redis server mode: Specify whether the Redis server runs on a single node or across multiple nodes. Defaults to Standalone.
Additional configurations

To add an additional configuration, see Additional Connector Configuration Reference for Confluent Cloud.

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.
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

Verify the connection details by previewing the running configuration.
After you’ve validated that the properties are configured to your satisfaction, click Launch.

Tip

For information about previewing your connector output, see Data Previews for Confluent Cloud Connectors.
Verify the connection details and click Launch.

The status for the connector should go from Provisioning to Running. It may take a few minutes.

Step 5: Check Redis database

After the connector is running, verify that messages are being added to your Redis 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": "RedisKafkaSink",
    "name": "RedisKafkaSinkConnector_0",
    "kafka.auth.mode": "KAFKA_API_KEY",
    "kafka.api.key": "<my-kafka-api-key",
    "kafka.api.secret": "<my-kafka-api-secret>",
    "redis.host": "test-18211.c90.us-east-1.ec2.redis-cloud.com",
    "redis.port": "18211",
    "redis.database": "0",
    "redis.tls": "false",
    "redis.timeout": "60",
    "redis.pool": "8",
    "redis.server.mode": "Standalone",
    "topics": "keys_source",
    "input.data.format" : "JSON",
    "input.key.format" : "STRING",
    "redis.charset": "UTF-8",
    "redis.type": "STREAM",
    "redis.multiexec": "false",
    "redis.separator": ":",
    "redis.wait.replicas": "0",
    "redis.key.ttl": "-1",
    "tasks.max": "1",
    "auto.restart.on.user.error": "true"
}

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 entires are AVRO, BYTES, JSON, JSON_SR (JSON Schema), PROTOBUF, 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).
"input.key.format": Sets the input record key format (data coming from the Kafka topic). Valid entries are AVRO, JSON_SR (JSON Schema), PROTOBUF, or STRING. You must have Confluent Cloud Schema Registry configured if using a schema-based message format.
"redis.host": The IP address or hostname of the Redis database server.
"redis.port": The port number used to connect to Redis database server.
"redis.tls": Specify whether to use Transport Layer Security (TLS) to connect to the Redis database. Defaults to false.
"tasks.max": Enter the number of tasks for the connector. For more information, see Confluent Cloud connector limitations.

Note

(Optional) To enable CSFLE for data encryption, specify the following properties:

csfle.enabled: Flag to indicate whether the connector honors CSFLE 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.

Warning

Security Risk: Dead Letter Queue (DLQ) with CSFLE

When using CSFLE with connectors that route failed messages to a Dead Letter Queue (DLQ), be aware that data sent to the DLQ is written in plaintext (unencrypted). 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 in the current version. If you need error handling for CSFLE-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 setup, see Manage CSFLE for connectors.

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

See Configuration Properties for all property values and definitions.

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 RedisKafkaSink.json

Example output:

Created connector confluent-RedisKafkaSink 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-RedisKafkaSink | RUNNING | sink

Step 6: Check Redis Kafka

After the connector is running, verify that records are populating your Redis Kafka 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. For self-managed connector property definitions and other details, see the connector docs in Self-managed connectors for Confluent Platform.

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

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 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

Redis connection

redis.host

The hostname of Redis server to connect to.

Type: string
Importance: high

redis.port

The port number of Redis server to connect to.

Type: string
Importance: high

redis.database

The database index to write to.

Type: int
Default: 0
Importance: medium

redis.username

The username of the Redis user connecting to the Redis database server.

Type: string
Importance: medium

redis.password

The password of the Redis user connecting to the Redis database server.

Type: password
Importance: medium

Redis security

redis.tls

Establish a secure TLS connection to Redis.

Type: boolean
Default: false
Importance: medium

redis.cacert

X.509 CA certificate file to verify with. Use this with or without client certificates.

Type: password
Importance: medium

Redis client certificate auth

redis.key.file

Private key file (PEM format) to authenticate with. Use this file along with the certificate file for client certificate authentication.

Type: password
Importance: medium

redis.key.cert

X.509 certificate chain file (PEM format) to authenticate with. Use this file along with the private key file for client certificate authentication.

Type: password
Importance: medium

redis.key.password

Password of the private key file. Leave empty if key file is not password-protected.

Type: password
Importance: medium

Redis data structure

redis.type

Destination Redis data structure. Valid entries are STREAM, LIST, SET, ZSET, STRING, HASH, TIMESERIES, or JSON. Note that multi/exec transactions only work with STREAM, LIST, SET, or ZSET data types.

Type: string
Default: STREAM
Importance: high

Input messages

input.data.format

Sets the input Kafka record value 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: JSON
Importance: high

input.key.format

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

Redis configuration

redis.keyspace

A format string for destination key space, which may contain ${topic} as a placeholder for the originating topic name. For example, kafka_${topic} for the topic orders will map to the Redis key space kafka_orders.

Type: string
Default: ${topic}
Importance: medium

redis.separator

Separator for non-collection destination keys.

Type: string
Default: :
Importance: medium

redis.key.ttl

Time to live in seconds for the key to automatically expire data after a specified duration. If not set (default -1), the record will not expire.

Type: long
Default: -1
Valid Values: [-1,…,2147483647]
Importance: medium

redis.multiexec

Whether to execute Redis commands in multi/exec transactions. Only works with STREAM, LIST, SET, or ZSET data types.

Type: boolean
Default: false
Importance: medium

redis.wait.replicas

Number of replicas to wait for. Use 0 to disable waiting for replicas.

Type: int
Default: 0
Valid Values: [0,…,100]
Importance: medium

redis.charset

Character set to encode Redis key and value strings. Must be a valid charset name.

Type: string
Default: UTF-8
Importance: high

redis.wait.timeout

Timeout in milliseconds for WAIT command.

Type: long
Default: 1000
Valid Values: [1,…,60000]
Importance: medium

redis.timeout

Redis command timeout in seconds.

Type: long
Default: 60
Valid Values: [1,…,3600]
Importance: medium

redis.pool

Maximum number of connections in the pool in the range of 1 to 100.

Type: int
Default: 8
Valid Values: [1,…,100]
Importance: medium

redis.server.mode

Whether redis server is running on one or multiple nodes.

Type: string
Default: Standalone
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

Egress allowlist

connector.egress.whitelist

Type: string
Default: “”
Importance: high

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.