# Azure Cosmos DB Source 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 [Azure Cosmos DB Source V2 connector](cc-azure-cosmos-source-v2.md#cc-azure-cosmos-source-v2) before the EOL date. For more information, see [Deprecated and end of life connectors](overview.md#deprecated-connectors). The fully managed Azure Cosmos Source connector for Confluent Cloud reads records from an Azure Cosmos database and writes data to Apache Kafka® topics in Confluent Cloud. Confluent Cloud is available through [Azure Marketplace](https://azuremarketplace.microsoft.com/en/marketplace/apps/confluentinc.confluent-cloud-azure-prod?tab=Overview) or [directly from Confluent](https://www.confluent.io/get-started/). #### 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](networking/internet-resource.md#clusters-connect-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. * **Offset management capabilities**: Supports offset management. For more information, see [Manage custom offsets](#cc-azure-cosmos-source-custom-offsets). 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 [Azure Cosmos DB Source Connector](limits.md#azure-cosmos-source-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). ## Manage custom offsets You can manage the offsets for this connector. Offsets provide information on the point in the system from which the connector is accessing data. For more information, see [Manage Offsets for Fully Managed Connectors in Confluent Cloud](offsets.md#connect-custom-offsets). **To manage offsets**: - Manage offsets using Confluent Cloud APIs. For more information, see [Connect offsets API reference](https://docs.confluent.io/cloud/current/ccloud/offsets-connect-v-1/). #### NOTE The Azure Cosmos DB Source connector allows reading from multiple containers using a single connector. In the following examples, the connector is reading from two different containers and writing to two different topics. Therefore, the offset is an array with two elements, each of which specifies a container and database name. ### Get the current offset To get the current offset, make a `GET` request that specifies the environment, Kafka cluster, and connector name. ```bash GET /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets Host: https://api.confluent.cloud ``` **Response:** Successful calls return HTTP `200` with a JSON payload that describes the offset. ```bash { "id": "lcc-example123", "name": "{connector_name}", "offsets": [ { "partition": { "Container": "container2", "DatabaseName": "my-cosmos-db" }, "offset": { "recordContinuationToken": "\"24764\"" } }, { "partition": { "Container": "container1", "DatabaseName": "my-cosmos-db" }, "offset": { "recordContinuationToken": "\"18460\"" } } ], "metadata": { "observed_at": "2024-03-28T17:57:48.139635200Z" } } ``` Responses include the following information: - The position of latest offset. - The observed time of the offset in the metadata portion of the payload. The `observed_at` time indicates a snapshot in time for when the API retrieved the offset. A running connector is always updating its offsets. Use `observed_at` to get a sense for the gap between real time and the time at which the request was made. By default, offsets are observed every minute. Calling get repeatedly will fetch more recently observed offsets. - Information about the connector. ### Update the offset To update the offset, make a `POST` request that specifies the environment, Kafka cluster, and connector name. Include a JSON payload that specifies new offset and a patch type. ```bash POST /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets/request Host: https://api.confluent.cloud { "type": "PATCH", "offsets": [ { "partition": { "Container": "container2", "DatabaseName": "my-cosmos-db" }, "offset": { "recordContinuationToken": "\"20000\"" } }, { "partition": { "Container": "container1", "DatabaseName": "my-cosmos-db" }, "offset": { "recordContinuationToken": "\"18000\"" } } ] } ``` Considerations: - You can only make one offset change at a time for a given connector. - This is an asynchronous request. To check the status of this request, you must use the check offset status API. For more information, see **Get the status of an offset request**. - For source connectors, the connector attempts to read from the position defined by the requested offsets. **Response:** Successful calls return HTTP `202 Accepted` with a JSON payload that describes the offset. ```bash { "id": "lcc-example123", "name": "{connector_name}", "offsets": [ { "partition": { "Container": "container2", "DatabaseName": "my-cosmos-db" }, "offset": { "recordContinuationToken": "\"20000\"" } }, { "partition": { "Container": "container1", "DatabaseName": "my-cosmos-db" }, "offset": { "recordContinuationToken": "\"18000\"" } } ], "requested_at": "2024-03-28T17:58:45.606796307Z", "type": "PATCH" } ``` Responses include the following information: - The requested position of the offsets in the source. - The time of the request to update the offset. - Information about the connector. ### Delete the offset To delete the offset, make a `POST` request that specifies the environment, Kafka cluster, and connector name. Include a JSON payload that specifies the delete type. ```bash POST /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets/request Host: https://api.confluent.cloud { "type": "DELETE" } ``` Considerations: - This is an asynchronous request. To check the status of this request, you must use the check offset status API. For more information, see **Get the status of an offset request**. - Do not issue delete and patch requests at the same time. - If the offset you intend to delete is not found, the connector continues from where it left off. - If you want to start reading from the beginning with Azure Cosmos DB Source connector, you must update the offset to set `recordContinuationToken` to `0`. **Response**: Successful calls return HTTP `202 Accepted` with a JSON payload that describes the result. ```bash { "id": "lcc-example123", "name": "{connector_name}", "offsets": [], "requested_at": "2024-03-28T17:59:45.606796307Z", "type": "DELETE" } ``` Responses include the following information: - Empty offsets. - The time of the request to delete the offset. - Information about Kafka cluster and connector. - The type of request. ### Get the status of an offset request To get the status of a previous offset request, make a `GET` request that specifies the environment, Kafka cluster, and connector name. ```bash GET /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets/request/status Host: https://api.confluent.cloud ``` Considerations: - The status endpoint always shows the status of the most recent PATCH/DELETE operation. **Response**: Successful calls return HTTP `200` with a JSON payload that describes the result. The following is an example of an applied patch. ```bash { "request": { "id": "lcc-example123", "name": "{connector_name}", "offsets": [ { "partition": { "Container": "container2", "DatabaseName": "my-cosmos-db" }, "offset": { "recordContinuationToken": "\"20000\"" } }, { "partition": { "Container": "container1", "DatabaseName": "smy-cosmos-db" }, "offset": { "recordContinuationToken": "\"18000\"" } } ], "requested_at": "2024-03-28T17:58:45.606796307Z", "type": "PATCH" }, "status": { "phase": "APPLIED", "message": "The Connect framework-managed offsets for this connector have been altered successfully. However, if this connector manages offsets externally, they will need to be manually altered in the system that the connector uses." }, "previous_offsets": [ { "partition": { "Container": "container2", "DatabaseName": "my-cosmos-db" }, "offset": { "recordContinuationToken": "\"24764\"" } }, { "partition": { "Container": "container1", "DatabaseName": "my-cosmos-db" }, "offset": { "recordContinuationToken": "\"18460\"" } } ], "applied_at": "2024-03-28T17:58:48.079141883Z" } ``` Responses include the following information: - The original request, including the time it was made. - The status of the request: applied, pending, or failed. - The time you issued the status request. - The previous offsets. These are the offsets that the connector last updated prior to updating the offsets. Use these to try to restore the state of your connector if a patch update causes your connector to fail or to return a connector to its previous state after rolling back. ### JSON payload The table below offers a description of the unique fields in the JSON payload for managing offsets of the CosmosDB Source connector. | Field | Definition | Required/Optional | |---------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------| | `Container` | The value from `connect.cosmos.containers.topicmap` in the connector configuration, which is the format `topic#container`.
For example, `topic2#container2` | Required | | `DatabaseName` | The value from `connect.cosmos.databasename` in the connector configuration. | Required | | `recordContinuationToken` | The last processed changeFeed or the point in the changeFeed to begin processing. | Required | ## 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](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). - Authorized access to read data Azure Cosmos. For more information, see [Secure access to data in Azure Cosmos DB](https://docs.microsoft.com/en-us/azure/cosmos-db/secure-access-to-data). - The Azure Cosmos DB is configured to use the Core (SQL) API. ![Use Core SQL API](images/ccloud-azure-cosmos-source-core-sql.png) ### 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 **Azure Cosmos DB Source** connector card. ![Azure Cosmos DB Source Connector Card](images/ccloud-azure-cosmos-source-icon.png) #### Step 4: Enter the connector details #### NOTE * Make sure you have all your [prerequisites](#cc-azure-cosmos-source-prereqs) completed. * An asterisk ( \* ) designates a required entry. At the **Add Azure Cosmos DB Source Connector** screen, complete the following: ### 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: **How should we connect to your Cosmos DB database?** - **Cosmos Endpoint**: The Azure Cosmos database endpoint URL. For example, `https://confluent-azure-cosmosdb.documents.azure.com:443/`. - **Cosmos Connection Key**: The Azure Cosmos database connection [master (primary) key](https://docs.microsoft.com/en-us/cli/azure/cosmosdb/keys). - **Cosmos Database name**: The name of the Azure Cosmos database from which the connector reads data. 2. Click **Continue**. ### Configuration **Output messages** - **Select output record value 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 - **Kafka message key enabled**: Whether or not to set a Kafka message key. Defaults to `id`. - **Kafka message key field**: The document field to use for the Kafka message key if the default key `id` is not used. **Database details** - **Topic-Container map**: A comma-delimited list of Kafka topics mapped to Cosmos containers. For example: `topic1#con1,topic2#con2`. The field accepts regex pattern `*[\\w.-]+ *#[^,]+(, *[\\w.-]+ *#[^,]+)*`. ### **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). **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**: 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. - **Key Converter Schema ID Serializer**: The class name of the schema ID serializer for keys. This is used to serialize schema IDs in the message headers. - **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`. - **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. - **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. - **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. Applicable for AVRO,PROTOBUF and JSON_SR Converters. - **Value Converter Schema ID Serializer**: The class name of the schema ID serializer for values. This is used to serialize schema IDs in the message headers. **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. **Connection details** - **Task timeout**: The maximum number of milliseconds (ms) the connector task reads documents before sending them to Kafka. Defaults to `5000` ms. - **Task reader buffer size**: The maximum buffer size (bytes) that the connector task buffers before sending documents to Kafka. Defaults to `10000` bytes. - **Task batch size**: The maximum number of documents the connector batches before sending to Kafka. Defaults to `100`. - **Task poll interval**: The polling interval in ms that a connector source task polls for changes. Defaults to `1000` ms. **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). **Processing position** - **Set offsets**: Click **Set offsets** to define a specific offset for this connector to begin procession data from. For more information on managing offsets, see [Manage offsets](offsets.md#connect-custom-offsets). For all property and value definitions, see ref:cc_azure-cosmos-source-config-properties. - 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 tasks, use the Range Slider to select the desired number of tasks. 2. Click **Continue**. ### Review and Launch 1. Verify the connection details by previewing the running configuration. 2. After you’ve validated that the properties are configured to your satisfaction, click **Launch**. The status for the connector should go from **Provisioning** to **Running**. #### 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 Usage Examples](connect-api-section.md#ccloud-connect-api) 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](#cc-azure-cosmos-source-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 the required connector properties. ```json { "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](../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). * `"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](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 ``` * `"tasks.max"`: Enter the maximum number of [tasks](/platform/current/connect/concepts.html#tasks) for the connector to use. More tasks may improve performance. **SMTs**: For details about adding SMTs using the Confluent CLI, see the [Single Message Transformations](single-message-transforms.md#cc-single-message-transforms) documentation. See [Configuration Properties](#cc-azure-cosmos-source-config-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: ```none confluent connect cluster create --config-file .json ``` For example: ```none confluent connect cluster create --config-file azure-cosmos-source-config.json ``` Example output: ```none Created connector CosmosDbSourceConnector_0 lcc-do6vzd ``` #### Step 4: 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 | 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 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). ### 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 ### 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 ### 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 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 * Default: JSON * 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` : Maximum number of tasks for the connector.
* Type: int * Valid Values: [1,…] * Importance: high ### Additional Configs `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 `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: none * Importance: low `key.converter.key.schema.id.serializer` : The class name of the schema ID serializer for keys. This is used to serialize schema IDs in the message headers.
* Type: string * Default: io.confluent.kafka.serializers.schema.id.PrefixSchemaIdSerializer * 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.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.serializer` : The class name of the schema ID serializer for values. This is used to serialize schema IDs in the message headers.
* Type: string * Default: io.confluent.kafka.serializers.schema.id.PrefixSchemaIdSerializer * 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 ### 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 Azure Cosmos DB Source connector for Confluent Cloud. ### How do I configure container to topic mapping? The connector uses the `connect.cosmos.containers.topicmap` property to map Cosmos DB containers to Kafka topics. Container mapping configuration: 1. **Map specific containers to topics**: Use the format `topic#container`: ```json { "connect.cosmos.containers.topicmap": "users-topic#users-container,orders-topic#orders-container" } ``` This maps `users-container` to `users-topic` and `orders-container` to `orders-topic`. 2. **Multiple mappings**: Separate multiple mappings with commas: Each mapping follows the pattern `topic#container`, and multiple mappings are comma-separated. #### IMPORTANT The topic mapping format must follow the pattern `topic#container`. Each container can only be mapped to one topic. ### Why is my connector not reading changes from Cosmos DB? The connector captures changes from Cosmos DB using the change feed. Missing changes can indicate configuration or permission issues. Common causes and solutions: 1. **Change feed not enabled**: Ensure the change feed is available for your Cosmos DB account: The change feed is automatically available for Cosmos DB SQL API accounts. Verify you are using the SQL API. 2. **Insufficient permissions**: The master key must have read access: Verify the `connect.cosmos.master.key` in the Azure portal under **Keys** in your Cosmos DB account settings. 3. **Container name mismatch**: Verify container names in the topic mapping: Check that container names in `connect.cosmos.containers.topicmap` match the actual containers in Cosmos DB. 4. **Worker assignment mode**: The connector assigns containers to workers: Each container is processed by a single worker. Ensure tasks are properly configured. #### NOTE The change feed provides access to document insert and update operations. Delete operations are not captured by the change feed. ### What Azure Cosmos DB permissions are required for the connector? The connector requires specific permissions to read data from Cosmos DB. Required permissions: 1. **Master key access**: The connector uses the master key for authentication: Obtain the master key from the Azure portal: Navigate to your Cosmos DB account > **Keys** > Copy the `PRIMARY KEY` or `SECONDARY KEY`. 2. **Read permissions**: The master key provides full read access to all containers: The connector can read from any container in the specified database. #### IMPORTANT Master keys provide full access to the Cosmos DB account. Store keys securely and rotate them periodically. Consider upgrading to the V2 connector for service principal authentication support. ### How can I optimize connector performance? Performance depends on Cosmos DB throughput, connector task configuration, and network latency. Performance optimization: 1. **Increase tasks**: More tasks can improve performance: ```json { "tasks.max": "4" } ``` Each task processes assigned containers independently. 2. **Optimize Cosmos DB throughput**: Ensure adequate Request Units (RUs): * **Use autoscale**: Configure autoscale to handle variable workloads * **Monitor RU consumption**: Check Cosmos DB metrics for throttling * **Increase provisioned throughput**: Allocate more Request Units if throttling occurs 3. **Use same region**: Deploy the connector in the same Azure region as Cosmos DB: Cross-region reads have higher latency and cost more. 4. **Monitor worker assignments**: Check how containers are distributed across workers: The connector automatically assigns containers to workers for balanced processing. #### NOTE Consider upgrading to the V2 connector for enhanced performance features including throughput control and the change feed pull model. ### Why is my connector failing with authentication errors? Authentication errors indicate issues with the master key or account endpoint. ```text Unauthorized: The input authorization token can't serve the request ``` Common causes and solutions: 1. **Invalid master key**: The `connect.cosmos.master.key` is incorrect: Verify the master key in the Azure portal under **Keys** in your Cosmos DB account settings. Ensure you copied the full key including any trailing characters. 2. **Wrong account endpoint**: The endpoint URL is incorrect: Verify the endpoint format: ```json { "connect.cosmos.connection.endpoint": "https://your-account.documents.azure.com:443/" } ``` The endpoint must include `https://` and port `:443/`. 3. **Regenerated keys**: Keys were regenerated in the Azure portal: If keys are rotated, update the connector configuration with the new master key. #### IMPORTANT Master keys provide full access to the Cosmos DB account. For enhanced security, consider upgrading to the V2 connector which supports service principal authentication. ### What should I do if my connector keeps failing or restarting? Frequent connector failures indicate configuration issues, network problems, or Cosmos DB capacity constraints. Common causes and solutions: 1. **Check connector logs**: In the Cloud Console, review error messages: * **Authentication failures**: Verify master key and endpoint * **Throttling errors**: Check RU consumption and increase throughput * **Network errors**: Verify network connectivity * **Configuration errors**: Check container names and mapping 2. **Verify Cosmos DB connectivity**: Test that Cosmos DB is accessible: * **Check firewall rules**: Ensure Confluent Cloud can connect to Cosmos DB * **Verify endpoint**: Confirm the account endpoint is correct * **Test credentials**: Use Azure portal to verify account access 3. **Monitor Cosmos DB metrics**: Check for resource constraints: * **RU consumption**: Monitor Request Unit usage and throttling * **Storage capacity**: Ensure adequate storage * **Network latency**: Check for network issues 4. **Verify container configuration**: Ensure containers exist and are accessible: Check that containers listed in `connect.cosmos.containers.topicmap` exist in the database. #### IMPORTANT For persistent failures, use the connector diagnostics feature and share logs with Confluent Support. Consider upgrading to the V2 connector for enhanced features and improved performance. ## 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. [![image](images/topology.png)](https://docs.confluent.io/platform/current/tutorials/examples/cloud-etl/docs/index.html)