Redis Sink Connector for Confluent Cloud¶

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.
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¶

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 section.

Limitations¶

Be sure to review the following information.

For connector limitations, see Redis 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 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 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). See Schema Registry Enabled Environments for additional information.
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. To use a set of public egress IP addresses, see Public Egress IP Addresses for Confluent Cloud Connectors.

Kafka cluster credentials. The following lists the different ways you can provide credentials.
- Enter an existing service account resource ID.
- Create a Confluent Cloud service account for the connector. Make sure to review the ACL entries required in the service account documentation. Some connectors have specific ACL requirements.
- Create a Confluent Cloud API key and secret. To create a key and secret, you can use confluent api-key create or you can autogenerate the API key and secret directly in the Cloud Console when setting up the connector.

Using the Confluent Cloud Console¶

Step 1: Launch your Confluent Cloud cluster¶

See the Quick Start for Confluent Cloud for installation instructions.

Step 2: Add a connector¶

In the left navigation menu, click Connectors. If you already have connectors in your cluster, click + Add connector.

Step 3: Select your connector¶

Click the Redis 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 Sink Connector screen, complete the following:

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.

Enter the following Databricks Delta Lake connection details:
- 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.
Click Continue.

Note

Configuration properties that are not shown in the Cloud Console use the default values. See Configuration Properties for all property values and definitions.

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?.
- 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.
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.
See Configuration Properties for all property values and definitions.
Click Continue.

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 section.

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
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Step 2: List the connector configuration properties¶

Enter the following command to show the connector configuration properties:

confluent connect plugin describe <connector-plugin-name>
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The command output shows the required and optional configuration properties.

Step 3: Create the connector configuration file¶

Create a JSON file that contains the connector configuration properties. The following example shows required and optional connector properties.

{
  "name": "RedisSinkConnector_0",
  "config": {
    "topics": "pageviews",
    "connector.class": "RedisSink",
    "name": "RedisSinkConnector_0",
    "input.data.format": "BYTES",
    "kafka.auth.mode": "KAFKA_API_KEY",
    "kafka.api.key": "<my-kafka-api-key>",
    "kafka.api.secret": "<my-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"
  }
}
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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, 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
```
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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
```
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"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 for the connector to use. More tasks may improve performance.

See Configuration Properties for all property values and descriptions.

Step 4: Load the configuration file and create the connector¶

Enter the following command to load the configuration and start the connector:

confluent connect cluster create --config-file <file-name>.json
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For example:

confluent connect cluster create --config-file redis-sink-config.json
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Example output:

Created connector RedisSinkConnector_0 lcc-ix4dl
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Step 5: Check the connector status¶

Enter the following command to check the connector status:

confluent connect cluster list
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Example output:

ID          |       Name            | Status  | Type
+-----------+-----------------------+---------+------+
lcc-ix4dl   | RedisSinkConnector_0  | RUNNING | sink
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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 section.

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

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

Type: list
Importance: high

Schema Config¶

schema.context.name

Add a schema context name. A schema context represents an independent scope in Schema Registry. It is a separate sub-schema tied to topics in different Kafka clusters that share the same Schema Registry instance. If not used, the connector uses the default schema configured for Schema Registry in your Confluent Cloud environment.

Type: string
Default: default
Importance: medium

How should we connect to 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
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.

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

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

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

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 or the “latest” offset (the default). 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.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

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.reference.subject.name.strategy

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

Type: string
Default: DefaultReferenceSubjectNameStrategy
Importance: low

value.converter.value.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

Next Steps¶

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