# Redis Sink Connector [Deprecated] for Confluent Cloud #### IMPORTANT This connector is deprecated and will reach its end of life (EOL) on April 6, 2027. Confluent recommends migrating to [Redis Kafka Sink connector](cc-redis-kafka-db-sink.md#cc-redis-kafka-sink) before the EOL date. For more information, see [Deprecated and end of life connectors](overview.md#deprecated-connectors). The fully managed Redis Sink connector for Confluent Cloud is used to export data from Apache Kafka® topics to Redis. The connector works with Redis Enterprise Cloud, Azure Cache for Redis, and Amazon ElastiCache for Redis #### NOTE * This Quick Start is for the fully managed Confluent Cloud connector. If you are installing the connector locally for Confluent Platform, see [Redis Sink Connector for Confluent Platform](https://docs.confluent.io/kafka-connectors/redis/current/). * 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](networking/internet-resource.md#clusters-connect-cloud). ## Features * **At least once delivery**: The connector guarantees that records are delivered at least once. * **Supports multiple tasks**: The connector supports running one or more tasks. * **SSL support**: Supports one-way SSL. * **Deletions**: The connector supports deletions. If the record stored in Kafka has a null value, the connector sends a delete message with the corresponding key to Redis. Note that the connector always expects non-null keys. * **Supported input data formats**: This connector supports storing raw bytes or strings (as inserts) in Redis. For more information and examples to use with the Confluent Cloud API for Connect, see the [Confluent Cloud API for Connect Usage Examples](connect-api-section.md#ccloud-connect-api) section. ## Limitations Be sure to review the following information. * For connector limitations, see [Redis Sink Connector](limits.md#cc-redis-sink-limits) limitations. * If you plan to use one or more Single Message Transformations (SMTs), see [SMT Limitations](single-message-transforms.md#cc-single-message-transforms-limitations). ## Quick Start Use this quick start to get up and running with the Confluent Cloud Redis Sink connector. The quick start provides the basics of selecting the connector and configuring it to stream events to Redis. Prerequisites : - Authorized access to a [Confluent Cloud](https://www.confluent.io/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](https://docs.confluent.io/confluent-cli/current/install.html). - [Schema Registry](../get-started/schema-registry.md#cloud-sr-config) must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf). - Access to one of the following fully managed Redis services: * Redis Enterprise Cloud * Azure Cache for Redis * Amazon ElastiCache for Redis. Note that to use this service, your Kafka cluster must be VPC peered. - Redis credentials, hostname, and database index name. - The Redis instance must be in the same region as your Confluent Cloud cluster. - For networking considerations, see [Networking and DNS](overview.md#connect-internet-access-resources). To use a set of public egress IP addresses, see [Public Egress IP Addresses for Confluent Cloud Connectors](static-egress-ip.md#cc-static-egress-ips).
- Kafka cluster credentials. The following lists the different ways you can provide credentials. - Enter an existing [service account](service-account.md#s3-cloud-service-account) resource ID. - Create a Confluent Cloud [service account](service-account.md#s3-cloud-service-account) for the connector. Make sure to review the ACL entries required in the [service account documentation](service-account.md#s3-cloud-service-account). 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](https://docs.confluent.io/confluent-cli/current/command-reference/api-key/confluent_api-key_create.html) *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](../get-started/index.md#cloud-create-kafka-cluster). #### 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 Sink** connector card.  #### Step 4: Enter the connector details #### NOTE * Ensure you have all your [prerequisites](#cc-redis-sink-prereqs) completed. * An asterisk ( \* ) designates a required entry. At the **Add Redis 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 access 1. 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](service-account.md#s3-cloud-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. 2. Click **Continue**. ### Authentication 1. Configure the authentication properties: - **Redis hostname**: Hostname of Redis server. - **Redis port number**: Port number of Redis server. - **Redis database index**: Database index you want to write to. - **Redis server password**: Password for Redis server. - **SSL mode**: Choose how the Redis server is secured. `server` requires a truststore with CA certificate. `server+client` additionally requires a keystore with a valid certificate/key pair. - **Keystore file**: The key store containing server certificate. - **Keystore password**: The store password for the key store file. - **Truststore file**: The trust store containing server CA certificate. - **Truststore password**: The trust store password containing server CA certificate. - **Redis server mode**: Select whether the Redis server should run on one or multiple nodes. 2. Click **Continue**. ### Configuration #### NOTE Configuration properties that are not shown in the Cloud Console use the default values. See [Configuration Properties](#cc-redis-sink-config-properties) for all property values and definitions. - **Input Kafka record value format**: Select an **Input Kafka record value** format (data coming from the Kafka topic): BYTES or STRING. If the Kafka topic is using JSON or a schema-based format, like Avro, you should select BYTES. ### **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?](../sr/faqs-cc.md#faq-schema-contexts). - **Input Kafka record key format**: Select an **Input Kafka record key** format. Sets the input Kafka record value format for the record key. `BYTES` passes keys as they are serialized in Kafka, while `STRING` enforces UTF-8 encoding on keys. **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. - **Value Converter Replace Null With Default**: Specifies whether to replace fields that have a default value and that are null to the default value. When set to `true`, the connector uses the default value; otherwise, it uses `null`. Applies to the `JSON` converter. - **Schema GUID For Key Converter**: Sets the schema GUID to use for deserialization when using `ConfigSchemaIdDeserializer`. This lets you specify a fixed schema GUID for deserializing message keys. This property is applicable only when `key.converter.key.schema.id.deserializer` is set to `ConfigSchemaIdDeserializer`. - **Value Converter Schema ID Deserializer**: Sets the class name of the schema ID deserializer for values. The deserializer reads schema IDs from message headers. - **Schema GUID For Value Converter**: Sets the schema GUID to use for deserialization when using `ConfigSchemaIdDeserializer`. This lets you specify a fixed schema GUID for deserializing message values. This property is applicable only when `value.converter.value.schema.id.deserializer` is set to `ConfigSchemaIdDeserializer`. - **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`. - **Schema ID For Value Converter**: Sets the schema ID to use for deserialization when using `ConfigSchemaIdDeserializer`. This lets you specify a fixed schema ID for deserializing message values. This property is applicable only when `value.converter.value.schema.id.deserializer` is set to `ConfigSchemaIdDeserializer`. - **Value Converter Schemas Enable**: Includes schema within each of the serialized values. Input messages must contain `schema` and `payload` fields and must not contain additional fields. For plain `JSON` data, set this to `false`. Applies to the `JSON` converter. - **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. - **Key Converter Schema ID Deserializer**: Sets the class name of the schema ID deserializer for keys. The deserializer reads schema IDs from message headers. - **Schema ID For Key Converter**: Sets the schema ID to use for deserialization when using `ConfigSchemaIdDeserializer`. This lets you specify a fixed schema ID for deserializing message keys. This property is applicable only when `key.converter.key.schema.id.deserializer` is set to `ConfigSchemaIdDeserializer`. **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. **Consumer configuration** - **Max poll interval(ms)**: Sets 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**: Sets 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 Transformations**: To add a new SMT, see [Add transforms](single-message-transforms.md#cc-single-message-transforms-ui). For more information about unsupported SMTs, see [Unsupported transformations](single-message-transforms.md#cc-single-message-transforms-unsupported-transforms). See [Configuration Properties](#cc-redis-sink-config-properties) for all property values and definitions. - Click **Continue**. ### Sizing Based on the number of topic partitions you select, you will be provided with a recommended number of tasks. 1. To change the number of recommended tasks, enter the number of [tasks](/platform/current/connect/concepts.html#tasks) for the connector to use in the **Tasks** field. 2. Click **Continue**. ### Review and Launch 1. Verify the connection details. 2. Click **Launch**. The status for the connector should go from **Provisioning** to **Running**. #### Step 5: Check the results in Redis. Verify that data is populating the Redis instance. For more information and examples to use with the Confluent Cloud API for Connect, see the [Confluent Cloud API for Connect Usage Examples](connect-api-section.md#ccloud-connect-api) 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](#cc-redis-sink-prereqs) completed. #### Step 1: List the available connectors Enter the following command to list available connectors: ```none confluent connect plugin list ``` #### Step 2: List the connector configuration properties Enter the following command to show the connector configuration properties: ```none confluent connect plugin describe ``` 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. ```none { "name": "RedisSinkConnector_0", "config": { "topics": "pageviews", "connector.class": "RedisSink", "name": "RedisSinkConnector_0", "input.data.format": "BYTES", "kafka.auth.mode": "KAFKA_API_KEY", "kafka.api.key": "", "kafka.api.secret": "", "redis.hostname": "test.redis.cache.windows.net", "redis.portnumber": "6380", "redis.database": "1", "redis.password": "********************************************", "redis.ssl.mode": "enabled", "tasks.max": "1" } } ``` Note the following property definitions: * `"name"`: Sets a name for your new connector. * `"connector.class"`: Identifies the connector plugin name. * `"topics"`: Identifies the topic name or a comma-separated list of topic names. * `"input.data.format"`: Sets the input Kafka record value format (data coming from the Kafka topic). Valid entries are **BYTES** or **STRING**. If the Kafka topic is using JSON or a schema-based format, like Avro, you should select BYTES. * `"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](service-account.md#s3-cloud-service-account), specify the **Resource ID** in the property `kafka.service.account.id=`. To list the available service account resource IDs, use the following command: ```bash confluent iam service-account list ``` For example: ```bash 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 ``` * `"redis.ssl.mode"`: Sets the SSL mode for the connection. Options are `enabled`, `disabled`, `server`, and `server+client`. The default is `disabled`. If set the property to `enabled`, the connector uses SSL to make the connection. If you select `server`, the connector uses a truststore. If you select `server+client`, the connector uses both the truststore and a keystore with a valid key pair and the associated certificate. - `"redis.ssl.mode": "server"`: If you use SSL mode `server`, the connector uses a truststore CA certificate to secure the connection. You add two additional properties: `redis.ssl.truststore.file` and `redis.ssl.truststore.password`. A truststore file is a binary file. For the `redis.ssl.truststore.file` property, you encode the binary truststore file in base64, take the encoded string, add the `data:text/plain;base64` prefix, and then specify the entire string as the property entry. For example: `"redis.ssl.truststore.file" : "data:text/plain;base64,/u3+7QAAAAIAAAACAAAAAQAGY2xpZ...=="`. - `"redis.ssl.mode": "server+client"`: If you use SSL mode `server+client`, the connector uses a truststore CA certificate and an additional keystore to secure the connection. You add four additional properties: `redis.ssl.truststore.file`, `redis.ssl.truststore.password`, `redis.ssl.keystore.file`, and `redis.ssl.keystore.password`. The truststore and keystore files are binary files. For the `redis.ssl.truststore.file` and `redis.ssl.keystore.file` properties, you encode the binary truststore and keystore files in base64, take the encoded string, add the `data:text/plain;base64` prefix, and then specify the entire string as the property entry. For example: `"redis.ssl.keystore.file" : "data:text/plain;base64,/u3+7QAAAAIAAAACAAAAAQAGY2xpZ...=="`. * `"tasks.max"`: Maximum [tasks](/platform/current/connect/concepts.html#tasks) for the connector to use. More tasks may improve performance. See [Configuration Properties](#cc-redis-sink-config-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: ```none confluent connect cluster create --config-file .json ``` For example: ```none confluent connect cluster create --config-file redis-sink-config.json ``` Example output: ```none Created connector RedisSinkConnector_0 lcc-ix4dl ``` #### Step 5: Check the connector status Enter the following command to check the connector status: ```none confluent connect cluster list ``` Example output: ```none ID | Name | Status | Type +-----------+-----------------------+---------+------+ lcc-ix4dl | RedisSinkConnector_0 | RUNNING | sink ``` #### Step 6: Check the results in Redis. Verify that data is populating the Redis instance. For more information and examples to use with the Confluent Cloud API for Connect, see the [Confluent Cloud API for Connect Usage Examples](connect-api-section.md#ccloud-connect-api) 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](/platform/current/connect/kafka_connectors.html). ### 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 ### Input messages `input.data.format` : Sets the input Kafka record value format. BYTES will pass keys as they are serialized in Kafka, while STRING will enforce a UTF-8 encoding on record values
* Type: string * Default: JSON * Importance: high `input.key.format` : Sets the input Kafka record key format. BYTES will pass keys as they are serialized in Kafka, while STRING will enforce a UTF-8 encoding on keys.
* Type: string * 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 ### How should we connect to your Redis server? `redis.hostname` : Hostname of Redis server.
* Type: string * Importance: high `redis.portnumber` : Port number of Redis server.
* Type: int * Importance: high `redis.client.mode` : Whether Redis server is running on one or multiple nodes.
* Type: string * Default: Standalone * Importance: high `redis.database` : DB index that you want to write to.
* Type: int * Default: 0 * Importance: high `redis.password` : Password for Redis server.
* Type: password * Importance: medium ### SSL configuration `redis.ssl.mode` : How the Redis server is secured. ‘server’ requires a truststore with CA certificate. ‘server+client’ additionally requires a keystore with a valid certificate/key pair.
* Type: string * Default: disabled * Importance: medium `redis.ssl.keystore.file` : The key store containing server certificate.
* Type: password * Importance: low `redis.ssl.keystore.password` : The store password for the key store file.
* Type: password * Importance: low `redis.ssl.truststore.file` : The trust store containing server CA certificate.
* Type: password * Importance: low `redis.ssl.truststore.password` : The trust store password containing server CA certificate.
* Type: password * Importance: low ### 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 ### 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](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](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 `key.converter.use.schema.guid` : The schema GUID to use for deserialization when using ConfigSchemaIdDeserializer. This allows you to specify a fixed schema GUID to be used for deserializing message keys. Only applicable when key.converter.key.schema.id.deserializer is set to ConfigSchemaIdDeserializer.
* Type: string * Importance: low `key.converter.use.schema.id` : The schema ID to use for deserialization when using ConfigSchemaIdDeserializer. This allows you to specify a fixed schema ID to be used for deserializing message keys. Only applicable when key.converter.key.schema.id.deserializer is set to ConfigSchemaIdDeserializer.
* Type: int * 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.use.schema.guid` : The schema GUID to use for deserialization when using ConfigSchemaIdDeserializer. This allows you to specify a fixed schema GUID to be used for deserializing message values. Only applicable when value.converter.value.schema.id.deserializer is set to ConfigSchemaIdDeserializer.
* Type: string * Importance: low `value.converter.use.schema.id` : The schema ID to use for deserialization when using ConfigSchemaIdDeserializer. This allows you to specify a fixed schema ID to be used for deserializing message values. Only applicable when value.converter.value.schema.id.deserializer is set to ConfigSchemaIdDeserializer.
* Type: int * 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.schema.id.deserializer` : The class name of the schema ID deserializer for keys. This is used to deserialize schema IDs from the message headers.
* Type: string * Default: io.confluent.kafka.serializers.schema.id.DualSchemaIdDeserializer * 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.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.schema.id.deserializer` : The class name of the schema ID deserializer for values. This is used to deserialize schema IDs from the message headers.
* Type: string * Default: io.confluent.kafka.serializers.schema.id.DualSchemaIdDeserializer * 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 ### Number of tasks for this connector `tasks.max` : Maximum number of tasks for the connector.
* Type: int * Valid Values: [1,…] * Importance: high ### Auto-restart policy `auto.restart.on.user.error` : Enable connector to automatically restart on user-actionable errors.
* Type: boolean * Default: true * Importance: medium ## Frequently asked questions Find answers to frequently asked questions about the Redis Sink connector for Confluent Cloud. ### Why is my connector stuck in `PROVISIONING` state? If your connector remains in `PROVISIONING` state indefinitely without transitioning to `RUNNING`, the connector failed to complete the deployment process. Common causes and solutions: * **Network connectivity issues**: The connector cannot reach your Redis instance. Verify that the Redis instance and Confluent Cloud Kafka cluster are in the same region. For private Redis instances such as AWS ElastiCache with no public endpoint, configure VPC peering between Confluent Cloud and your cloud provider. * **Invalid Redis credentials**: The Redis hostname, port, or password is incorrectly configured. Verify that your `redis.hostname`, `redis.portnumber`, and `redis.password` properties are correct. Test connectivity using a Redis client before you configure the connector. * **SSL/TLS configuration errors**: The SSL mode does not match your Redis instance configuration. If you use SSL, verify that the `redis.ssl.mode` setting matches your Redis instance configuration. For `server` mode, verify that the `redis.ssl.truststore.file` property contains the truststore file correctly encoded in base64 with the `data:text/plain;base64,` prefix. * **Regional mismatch**: The Redis database service endpoint and the Kafka cluster are in different regions. Verify that both are in the same region. Cross-region connections are not supported. If the connector remains stuck after you verify these settings, delete and recreate the connector with the corrected configuration. ### Why does my connector fail with `null` key errors? The Redis Sink connector requires non-null keys for all records because Redis stores data as key-value pairs. Error example: ```none org.apache.kafka.connect.errors.DataException: The key for the record cannot be null ``` Common causes and solutions: * **Records without keys**: The Kafka records do not have keys. Kafka records must have non-null keys. The connector cannot process tombstone records or records with null keys. * **Error tolerance limitations**: The `errors.tolerance` property is set to `all` but the connector still fails. Setting `errors.tolerance=all` does not prevent null key failures because the error occurs during the `put()` stage before the error handling framework can process the error. To resolve this issue, complete the following steps: 1. Apply the `ValueToKey` Single Message Transform to extract a field from the record value and use it as the key: ```none "transforms": "ValueToKey", "transforms.ValueToKey.type": "org.apache.kafka.connect.transforms.ValueToKey", "transforms.ValueToKey.fields": "id" ``` 2. Modify your producer application or upstream connector to ensure that all records have non-null keys. 3. Use ksqlDB to filter out records with null keys before they reach the Redis Sink connector. ### How do I configure SSL/TLS for secure connections to Redis? The connector supports multiple SSL modes for secure connections to Redis instances. SSL mode options: * **disabled**: No SSL encryption. Use this mode only for development or when Redis is in a trusted network. * **enabled**: Basic SSL encryption without certificate validation. The connector establishes an SSL connection but does not verify the server certificate. * **server**: SSL encryption with server certificate validation using a truststore. Use this mode to validate the Redis server’s identity. * **server+client**: Mutual SSL authentication that requires both truststore for server validation and keystore for client certificate. Use this mode when Redis requires client certificate authentication. To configure `server` mode: ```none "redis.ssl.mode": "server", "redis.ssl.truststore.file": "data:text/plain;base64,/u3+7QAAAAIAAAACAAAAAQAGY2xpZ...", "redis.ssl.truststore.password": "truststore-password" ``` To configure `server+client` mode: ```none "redis.ssl.mode": "server+client", "redis.ssl.truststore.file": "data:text/plain;base64,/u3+7QAAAAIAAAACAAAAAQAGY2lpZ...", "redis.ssl.truststore.password": "truststore-password", "redis.ssl.keystore.file": "data:text/plain;base64,/u3+7QAAAAIAAAACAAAAAQAGY2xpZ...", "redis.ssl.keystore.password": "keystore-password" ``` Important considerations: * **Base64 encoding**: The `redis.ssl.truststore.file` and `redis.ssl.keystore.file` properties must contain truststore and keystore files encoded in base64. Encode the files as binary files in JKS or PKCS12 format. Add the `data:text/plain;base64,` prefix before the encoded string. * **Certificate chain**: The truststore file must include the complete certificate chain. * **Password protection**: Both the `redis.ssl.truststore.password` and `redis.ssl.keystore.password` properties are required. ### How do I connect to a private Redis instance in AWS, Azure, or Google Cloud? To connect to a private Redis instance, configure the network to allow Confluent Cloud to reach your Redis endpoint. For AWS ElastiCache for Redis, complete the following steps: 1. Configure VPC peering between your Confluent Cloud cluster and the AWS VPC that contains your ElastiCache instance. 2. Configure security groups to allow inbound traffic from Confluent Cloud on the Redis port. Standard Redis uses port 6379. SSL connections typically use port 6380. 3. Set the `redis.hostname` property to the private endpoint hostname. 4. Verify DNS resolution from Confluent Cloud to your private endpoint. For Azure Cache for Redis, complete the following steps: 1. Verify that the Redis instance has a public endpoint, or configure Virtual Network peering. 2. Configure firewall rules to allow connections from Confluent Cloud egress IP addresses. For the list of static egress IPs, see [Public Egress IP Addresses for Confluent Cloud Connectors](static-egress-ip.md#cc-static-egress-ips). 3. Set the `redis.hostname` property to the primary or secondary connection hostname. For Redis Enterprise Cloud or other managed services, complete the following steps: 1. Verify that the Redis instance is configured for external connectivity. 2. Add Confluent Cloud egress IP addresses to the Redis instance’s IP allowlist. 3. Configure network routing and firewall rules. Important considerations: * **Region matching**: The Redis instance and Confluent Cloud Kafka cluster must be in the same cloud region. * **Port configuration**: Set the `redis.portnumber` property to the correct port for your Redis instance. Standard Redis uses port 6379. SSL connections typically use port 6380. * **Test connectivity**: Before you create the connector, verify network connectivity using tools such as `telnet` or `nc` from a machine in the same network. ### What data formats are supported for the Redis Sink connector? The Redis Sink connector supports limited data formats that are optimized for Redis storage. Supported input formats: * **BYTES**: Stores raw bytes from Kafka record values directly in Redis. Use this format when your Kafka topic contains binary data or when you want to preserve the exact serialization format. If your topic contains JSON, Avro, or Protobuf data, select `BYTES` as the `input.data.format` to store the serialized form. * **STRING**: Converts Kafka record values to strings before storing in Redis. Use this format only when your Kafka topic contains string data that is serialized with `StringConverter` or `StringSerializer`. Important considerations: * **Schema-based formats not supported as input**: The Redis Sink connector does not support `AVRO`, `JSON_SR`, or `PROTOBUF` as direct input formats. If your topic uses these formats, set the `input.data.format` property to `BYTES` to store the serialized representation. * **Key format**: The `input.key.format` property supports `BYTES` or `STRING` for record keys. Record keys are used as Redis keys. * **No automatic conversion**: The connector does not perform automatic schema conversion or transformation. Data is stored in Redis based on the `input.data.format` property that you specify. ### Why is my connector not writing data to Redis? If your connector shows `RUNNING` status but data is not appearing in Redis, verify the following. Common causes and solutions: * **Topic consumption lag**: The connector is not consuming messages from the topic. View the connector metrics in the Confluent Cloud Console to verify throughput. * **Incorrect Redis database index**: You are checking the wrong Redis database index. Verify that you are checking the correct Redis database index that is specified in the `redis.database` property. Redis supports multiple databases with indexes 0 through 15 by default. * **Key naming mismatch**: The Redis key format does not match your expectations. The Redis key is derived from the Kafka record key. Verify that the key format matches your expectations. You can use Redis commands such as `KEYS *` to list all keys. Use this command with caution in production environments. * **Data eviction**: Redis is configured with a `maxmemory-policy` that evicts data. The connector does not set TTL on keys by default, but Redis can evict data based on its eviction policy. * **Records in DLQ**: Records failed to write and were sent to the Dead Letter Queue. Check the connector’s DLQ topic for any records that failed to be written. View DLQ topics in the Confluent Cloud Console under the connector’s monitoring section. To troubleshoot this issue, complete the following steps: 1. Use the Redis CLI to connect to your Redis instance and run the `DBSIZE` command to check if keys exist. 2. Monitor the connector logs in the Confluent Cloud Console for error messages. 3. Verify that the connector’s consumer group has committed offsets. Committed offsets indicate that the connector has consumed messages. 4. Check Redis server logs for connection or authentication errors. ## 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](/platform/current/tutorials/examples/cloud-etl/docs/index.html). This example also shows how to use Confluent CLI to manage your resources in Confluent Cloud. [](https://docs.confluent.io/platform/current/tutorials/examples/cloud-etl/docs/index.html)