Azure Cosmos DB Source Connector for Confluent Cloud

Note

This is a Quick Start for the managed cloud connector.

The fully-managed Microsoft Azure Cosmos Source connector for Confluent Cloud reads records from an Azure Cosmos database and writes data to Apache Kafka® topics in Confluent Cloud.

Features

The Azure Cosmos DB Source connector supports the following features:

  • Topic to Container mapping: The connector can map a container (table) to an individual Kafka topic (that is, topic1#con1,topic2#con2).
  • At least once delivery: This connector guarantees that records from the Kafka topic are delivered at least once.
  • Supports multiple tasks: The connector supports running one or more tasks. More tasks may improve performance. Note that one container (table) can be handled by one task.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect section.

Limitations

Be sure to review the following information.

Quick Start

Use this quick start to get up and running with the Confluent Cloud Azure Cosmos DB Source connector. The quick start provides the basics of selecting the connector and configuring it to stream events from a database to Kafka.

Prerequisites
  • Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud Platform (GCP).

  • 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).

  • Authorized access to read data Azure Cosmos. For more information, see Secure access to data in Azure Cosmos DB.

  • The Azure Cosmos DB is configured to use the Core (SQL) API.

    Use Core SQL API

    Core (SQL) API selection

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 Data integration, and then click Connectors. If you already have connectors in your cluster, click + Add connector.

Step 3: Select your connector.

Click the Azure Cosmos DB Source connector card.

Azure Cosmos DB Source Connector Card

Step 4: Enter the connector details.

Note

  • Make sure you have all your prerequisites completed.
  • An asterisk ( * ) designates a required entry.

At the Add Azure Cosmos DB Source Connector screen, complete the following:

  1. Select the way you want to provide Kafka Cluster credentials. You can choose one of the following options:
    • Global Access: Allows your connector to access everything you have access to. With global access, connector access will be linked to your account. This option is not recommended for production.
    • Granular access: Limits the access for your connector. You will be able to manage connector access through a service account. This option is recommended for production.
    • Use an existing API key: Allows you to enter an API key and secret part you have stored. You can enter an API key and secret (or generate these in the Cloud Console).
  2. Click Continue.

Step 5: Check for files.

Verify that data is being produced in Kafka.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect section.

Using the Confluent CLI

To set up and run the connector using the Confluent CLI, complete the following steps.

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: Show the required connector configuration properties.

Enter the following command to show the required connector properties:

confluent connect plugin describe <connector-catalog-name>

For example:

confluent connect plugin describe CosmosDbSource

Example output:

The following are required configs:
connector.class : CosmosDbSource
name : ["name" is required]
kafka.api.key : ["kafka.api.key" is required when "kafka.auth.mode==KAFKA_API_KEY"]
kafka.api.secret : ["kafka.api.secret" is required when "kafka.auth.mode==KAFKA_API_KEY"]
connect.cosmos.connection.endpoint
connect.cosmos.master.key
connect.cosmos.databasename
connect.cosmos.containers.topicmap
output.data.format
tasks.max

Step 3: Create the connector configuration file.

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

{
  "name": "CosmosDbSourceConnector_0",
  "config": {
    "connector.class": "CosmosDbSource",
    "name": "CosmosDbSourceConnector_0",
    "connect.cosmos.connection.endpoint": "https://confluent-azure-cosmosdb.documents.azure.com:443/",
    "connect.cosmos.master.key": "****************************************",
    "connect.cosmos.databasename": "ToDoList",
    "connect.cosmos.containers.topicmap": "Kafka-Items#Items",
    "output.data.format": "AVRO",
    "connect.cosmos.messagekey.enabled": "true",
    "kafka.auth.mode": "KAFKA_API_KEY",
    "kafka.api.key": "****************",
    "kafka.api.secret": "**********************************",
    "tasks.max": "1"
  }
}

Note the following property definitions:

  • "connector.class": Identifies the connector plugin name.
  • "name": Sets a name for your new connector.
  • "connect.cosmos.containers.topicmap": Enter a comma-delimited list of Kafka topics mapped to Cosmos containers. For example: topic1#con1,topic2#con2. The field accepts regex pattern *[\\w.-]+ *#[^,]+(, *[\\w.-]+ *#[^,]+)*.
  • "output.data.format" (data going to the Kafka topic): Supports AVRO, JSON_SR (JSON Schema), PROTOBUF, or JSON (schemaless). 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.
  • "connect.cosmos.messagekey.enabled": Whether or not to set a Kafka message key. Defaults to id. To set a different field for the message key, add the configuration property connect.cosmos.messagekey.field.
  • "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
    
  • "tasks.max": Enter the maximum number of tasks for the connector to use. More tasks may improve performance.

Single Message Transforms: See the Single Message Transforms (SMT) documentation for details about adding SMTs using the CLI.

See Configuration Properties for all property values and descriptions.

Step 3: Load the properties file and create the connector.

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

confluent connect create --config <file-name>.json

For example:

confluent connect create --config azure-cosmos-source-config.json

Example output:

Created connector CosmosDbSourceConnector_0 lcc-do6vzd

Step 4: Check the connector status.

Enter the following command to check the connector status:

confluent connect list

Example output:

ID           |             Name           | Status  | Type   | Trace
+------------+----------------------------+---------+--------+-------+
lcc-do6vzd   |CosmosDbSourceConnector_0   | RUNNING | Source |       |

Step 5: Check for files.

Verify that data is being produced in Kafka.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect section.

Configuration Properties

Use the following configuration properties with this connector.

Note

These are properties for the managed cloud connector.

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
  • 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
  • Type: password
  • Importance: high

How should we connect to your Cosmos DB database?

connect.cosmos.connection.endpoint

Cosmos endpoint URL.

  • Type: string
  • Importance: high
connect.cosmos.master.key

Cosmos connection master (primary) key.

  • Type: password
  • Importance: high
connect.cosmos.databasename

Name of the database to read from.

  • Type: string
  • Importance: high

Database details

connect.cosmos.containers.topicmap

A comma delimited list of Kafka topics mapped to Cosmos containers. For example: topic1#con1,topic2#con2.

  • Type: string
  • Valid Values: Must match the regex \s*[\w.-]+ *#[^,]+(, *[\w.-]+ *#[^,]+)*
  • Importance: high

Connection details

connect.cosmos.task.timeout

The maximum number of milliseconds the source task will use to read documents before sending them to Kafka.

  • Type: int
  • Default: 5000
  • Importance: low
connect.cosmos.task.buffer.size

The max size the container of documents (in bytes) the source task will buffer before sending them to Kafka.

  • Type: int
  • Default: 10000
  • Valid Values: [1,…,1000000]
  • Importance: low
connect.cosmos.task.batch.size

The max number of documents the source task will buffer before sending them to Kafka.

  • Type: int
  • Default: 100
  • Valid Values: [1,…]
  • Importance: low
connect.cosmos.task.poll.interval

The polling interval in milliseconds that a source task polls for changes.

  • Type: int
  • Default: 1000
  • Importance: low

Output messages

output.data.format

Sets the output Kafka record value format. Valid entries are AVRO, JSON_SR, PROTOBUF, or JSON. 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
  • Importance: high
connect.cosmos.messagekey.enabled

Whether to set the Kafka message key.

  • Type: boolean
  • Default: true
  • Importance: high
connect.cosmos.messagekey.field

The document field to use as the message key.

  • Type: string
  • Default: id
  • Importance: high

Number of tasks for this connector

tasks.max
  • Type: int
  • Valid Values: [1,…]
  • Importance: high

Next Steps

See also

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.

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