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 is a Quick Start for the fully-managed cloud connector. If you are installing the connector locally for Confluent Platform, see Redis Sink Connector for Confluent Platform.
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 Managed and Custom Connectors 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 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.
- 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.
- Click Continue.
- 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, whileSTRING
enforces UTF-8 encoding on keys.For Transforms and Predicates, see the Single Message Transforms (SMT) documentation for details.
See Configuration Properties for all property values and definitions.
Click Continue.
Based on the number of topic partitions you select, you will be provided with a recommended number of tasks.
- To change the number of recommended tasks, enter the number of tasks for the connector to use in the Tasks field.
- Click Continue.
Verify the connection details.
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 Managed and Custom Connectors section.
Tip
When you launch a connector, a Dead Letter Queue topic is automatically created. See Confluent Cloud Dead Letter Queue 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 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"
}
}
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
orKAFKA_API_KEY
(the default). To use an API key and secret, specify the configuration propertieskafka.api.key
andkafka.api.secret
, as shown in the example configuration (above). To use a service account, specify the Resource ID in the propertykafka.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
"redis.ssl.mode"
: Sets the SSL mode for the connection. Options areenabled
,disabled
,server
, andserver+client
. The default isdisabled
. If set the property toenabled
, the connector uses SSL to make the connection. If you selectserver
, the connector uses a truststore. If you selectserver+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 modeserver
, the connector uses a truststore CA certificate to secure the connection. You add two additional properties:redis.ssl.truststore.file
andredis.ssl.truststore.password
. A truststore file is a binary file. For theredis.ssl.truststore.file
property, you encode the binary truststore file in base64, take the encoded string, add thedata: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 modeserver+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
, andredis.ssl.keystore.password
. The truststore and keystore files are binary files. For theredis.ssl.truststore.file
andredis.ssl.keystore.file
properties, you encode the binary truststore and keystore files in base64, take the encoded string, add thedata: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
For example:
confluent connect cluster create --config-file redis-sink-config.json
Example output:
Created connector RedisSinkConnector_0 lcc-ix4dl
Step 5: Check the connector status¶
Enter the following command to check the connector status:
confluent connect cluster list
Example output:
ID | Name | Status | Type
+-----------+-----------------------+---------+------+
lcc-ix4dl | 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 Managed and Custom Connectors section.
Tip
When you launch a connector, a Dead Letter Queue topic is automatically created. See Confluent Cloud Dead Letter Queue 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
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.