OpenSearch Sink Connector for Confluent Cloud

The fully-managed OpenSearch Sink connector for Confluent Cloud moves data from an Apache Kafka® topic to a specified OpenSearch index facilitating real time analysis of data in OpenSearch. The connector supports Avro, JSON Schema, JSON (schemaless), and Protobuf data output format from Apache Kafka® topics.

Note

If you require private networking for fully-managed connectors, make sure to set up the proper networking beforehand. For more information, see Manage Networking for Confluent Cloud Connectors.

Features

The OpenSearch Sink connector includes the following features:

  • Automatic index creation: The connector supports automatic creation of indexes depending on the OpenSearch configuration.
  • Multi-indexing: The connector allows you to create and manage up to 5 indexes simultaneously.
  • Input data formats: The connector supports Avro, JSON Schema, Protobuf, or JSON (schemaless) input data formats. Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON Schema, or Protobuf). For more information, see Schema Registry Enabled Environments.
  • Dual-platform OpenSearch support: The connector supports both AWS OpenSearch and OSS OpenSearch.
  • Topic-to-index mapping: The connector supports mapping a topic to a specific OpenSearch Index.
  • Schema management: The connector supports Schema Registry, Schema Context and Reference Subject Naming Strategy.

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.

Quick Start

Use this quick start to get up and running with the Confluent Cloud OpenSearch Sink connector. The quick start provides the basics of selecting the connector and configuring it to stream events to an OpenSearch deployment.

Prerequisites

  • 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 OpenSearch Sink connector card.

OpenSearch Sink Connector Card

Step 4: Enter the connector details

Note the following:

  • Ensure you have completed all the prerequisites.
  • An asterisk ( * ) designates a required entry.

At the Add OpenSearch 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 a new topic. To use the default topic settings, click Create with defaults. To modify the topic settings, click Show advanced settings, update accordingly, and then click Save & Create.

Step 5: Check the results in OpenSearch

Verify that new records are being added to your OpenSearch deployment.

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. Ensure you have completed all the prerequisites.

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.

{
  "connector.class": "OpenSearchSink",
  "input.data.format": "JSON",
  "kafka.auth.mode": "KAFKA_API_KEY",
  "kafka.api.key": "<my-kafka-api-key",
  "kafka.api.secret": "<my-kafka-api-secret",
  "name": "os_sink_connectors3ss2a",
  "instance.url": "https://your-opensearch-endpoint.example",
  "topics": "inventory,orders,users",
  "request.method": "POST",
  "tasks.max": "1",
  "indexes.num": "3",
  "auth.type": "BASIC",
  "connection.user": "username",
  "connection.password": "password",
  "index1.name" : "users_index",
  "index1.topic": "users",
  "index2.name" : "inventory_index",
  "index2.topic": "inventory",
  "index3.name" : "orders",
  "index3.topic": "orders_index"
}

Note the following property definitions:

  • "connector.class": Identifies the connector plugin name.
  • "input.data.format": Sets the input Kafka record value format (data coming from the Kafka topic). Valid entries are AVRO, JSON_SR, PROTOBUF, or JSON. You must have Confluent Cloud Schema Registry configured if using a schema-based message format (for example, Avro, JSON Schema, JSON, or Protobuf).

  • "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

  • "name": Sets a name for your new connector.

  • "instance.url": The OpenSearch instance URL. The URL you enter should look like this: http://your-opensearch-instance.com/.

  • "topics": Identifies the topic name or a comma-separated list of topic names.

  • "request.method": Enter an HTTP API Request Method. Only POST requests are supported.

  • "tasks.max": Enter the maximum number of tasks for the connector to use. More tasks might improve performance.

  • "indexes.num": The number of indexes to push data to.

Single Message Transforms: For details about adding SMTs using the CLI, see the Single Message Transforms (SMT) documentation. For a list of SMTs that are not supported with this connector, see Unsupported transformations.

For all property values and definitions, see Configuration Properties.

Step 4: Load the configuration file and create the connector

Enter the following Confluent CLI 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 opensearch-sink-config.json

Example output:

Created connector os_sink_connectors3ss2a lcc-ix4dl

Step 5: Check the connector status

Enter the following Confluent CLI command to check the connector status:

confluent connect cluster list

Example output:

ID          |       Name                 | Status  | Type
+-----------+----------------------------+---------+------+
lcc-ix4dl   | os_sink_connectors3ss2a    | RUNNING | sink

Step 6: Check the results in OpenSearch

Verify new records are being added to the OpenSearch deployment.

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 OpenSearch Sink connector.

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

Input messages

input.data.format

Sets the input Kafka record value format. Valid entries are AVRO, JSON_SR, PROTOBUF, JSON or BYTES. 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
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: high

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

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

Authentication

instance.url

The OpenSearch instance URL. For example: https://your-opensearch-instance.com/.

  • Type: string
  • Importance: high
auth.type

Authentication type of the endpoint. Valid values are NONE, BASIC.

  • Type: string
  • Default: BASIC
  • Importance: high
connection.user

The username to be used with an endpoint requiring basic authentication.

  • Type: string
  • Importance: medium
connection.password

The password to be used with an endpoint requiring basic authentication.

  • Type: password
  • Importance: medium
opensearch.ssl.enabled

Whether or not to connect to the endpoint via SSL.

  • Type: boolean
  • Default: false
  • Importance: medium
opensearch.ssl.keystorefile

The key store containing the server certificate.

  • Type: password
  • Importance: low
opensearch.ssl.keystore.password

The store password for the key store file.

  • Type: password
  • Importance: high
opensearch.ssl.key.password

The password for the private key in the key store file.

  • Type: password
  • Importance: high
opensearch.ssl.truststorefile

The trust store containing a server CA certificate.

  • Type: password
  • Importance: high
opensearch.ssl.truststore.password

The trust store password containing a server CA certificate.

  • Type: password
  • Importance: high
opensearch.ssl.protocol

The protocol to use for SSL connections

  • Type: string
  • Default: TLSv1.3
  • Importance: medium

Behavior On Error

behavior.on.error

Error handling behavior setting for handling error response from HTTP requests.

  • Type: string
  • Default: FAIL
  • Importance: low

Indexes

indexes.num

The number of indexes to push data to. This value should be less than or equal to 5

  • Type: int
  • Default: 1
  • Valid Values: [1,…,5]
  • Importance: high

Retry Configs

retry.backoff.policy

The backoff policy to use in terms of retry - CONSTANT_VALUE or EXPONENTIAL_WITH_JITTER

  • Type: string
  • Default: EXPONENTIAL_WITH_JITTER
  • Importance: medium
retry.backoff.ms

The initial duration in milliseconds to wait following an error before a retry attempt is made. Subsequent backoff attempts can be a constant value or exponential with jitter (can be configured using api*.retry.backoff.policy parameter). Jitter adds randomness to the exponential backoff algorithm to prevent synchronized retries.

  • Type: int
  • Default: 3000 (3 seconds)
  • Valid Values: [100,…]
  • Importance: medium
retry.on.status.codes

Comma-separated list of HTTP status codes or range of codes to retry on. Ranges are specified with start and optional end code. Range boundaries are inclusive. For instance, 400- includes all codes greater than or equal to 400. 400-500 includes codes from 400 to 500, including 500. Multiple ranges and single codes can be specified together to achieve fine-grained control over retry behavior. For example, 404,408,500- will retry on 404 NOT FOUND, 408 REQUEST TIMEOUT, and all 5xx error codes. Note that some status codes will always be retried, such as unauthorized, timeouts and too many requests.

  • Type: string
  • Default: 400-
  • Importance: medium
max.retries

The maximum number of times to retry on errors before failing the task.

  • Type: int
  • Default: 3
  • Importance: medium

Index 1 configuration

index1.name

The index name together with the OpenSearch Instance URL will form the complete HTTP(S) URL. This path can be templated with offset information.

  • Type: string
  • Importance: high
index1.topic

Topic from where data will be pulled for this Index

  • Type: string
  • Default: “”
  • Importance: high
index1.behavior.on.null.values

How to handle records with a non-null key and a null value (i.e. Kafka tombstone records). Valid options are IGNORE, DELETE and FAIL

  • Type: string
  • Default: IGNORE
  • Importance: low
index1.batch.size

Size of the batch of records to be sent to the OpenSearch. Note that Basic and Standard Clusters may experience throughput limitations, even with a higher batch size.

  • Type: int
  • Default: 1
  • Importance: low

Index 2 configuration

index2.name

The index name together with the OpenSearch Instance URL will form the complete HTTP(S) URL. This path can be templated with offset information.

  • Type: string
  • Importance: high
index2.topic

Topic from where data will be pulled for this Index

  • Type: string
  • Default: “”
  • Importance: high
index2.behavior.on.null.values

How to handle records with a non-null key and a null value (i.e. Kafka tombstone records). Valid options are IGNORE, DELETE and FAIL

  • Type: string
  • Default: IGNORE
  • Importance: low
index2.batch.size

Size of the batch of records to be sent to the OpenSearch. Note that Basic and Standard Clusters may experience throughput limitations, even with a higher batch size.

  • Type: int
  • Default: 1
  • Importance: low

Index 3 configuration

index3.name

The index name together with the OpenSearch Instance URL will form the complete HTTP(S) URL. This path can be templated with offset information.

  • Type: string
  • Importance: high
index3.topic

Topic from where data will be pulled for this Index

  • Type: string
  • Default: “”
  • Importance: high
index3.behavior.on.null.values

How to handle records with a non-null key and a null value (i.e. Kafka tombstone records). Valid options are IGNORE, DELETE and FAIL

  • Type: string
  • Default: IGNORE
  • Importance: low
index3.batch.size

Size of the batch of records to be sent to the OpenSearch. Note that Basic and Standard Clusters may experience throughput limitations, even with a higher batch size.

  • Type: int
  • Default: 1
  • Importance: low

Index 4 configuration

index4.name

The index name together with the OpenSearch Instance URL will form the complete HTTP(S) URL. This path can be templated with offset information.

  • Type: string
  • Importance: high
index4.topic

Topic from where data will be pulled for this Index

  • Type: string
  • Default: “”
  • Importance: high
index4.behavior.on.null.values

How to handle records with a non-null key and a null value (i.e. Kafka tombstone records). Valid options are IGNORE, DELETE and FAIL

  • Type: string
  • Default: IGNORE
  • Importance: low
index4.batch.size

Size of the batch of records to be sent to the OpenSearch. Note that Basic and Standard Clusters may experience throughput limitations, even with a higher batch size.

  • Type: int
  • Default: 1
  • Importance: low

Index 5 configuration

index5.name

The index name together with the OpenSearch Instance URL will form the complete HTTP(S) URL. This path can be templated with offset information.

  • Type: string
  • Importance: high
index5.topic

Topic from where data will be pulled for this Index

  • Type: string
  • Default: “”
  • Importance: high
index5.behavior.on.null.values

How to handle records with a non-null key and a null value (i.e. Kafka tombstone records). Valid options are IGNORE, DELETE and FAIL

  • Type: string
  • Default: IGNORE
  • Importance: low
index5.batch.size

Size of the batch of records to be sent to the OpenSearch. Note that Basic and Standard Clusters may experience throughput limitations, even with a higher batch size.

  • Type: int
  • Default: 1
  • 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.

    ../_images/topology.png

  • Try Confluent Cloud on AWS Marketplace with $1000 of free usage for 30 days, and pay as you go. No credit card is required.