Get Started with the MongoDB Atlas Source Connector for Confluent Cloud

The Kafka Connect MongoDB Atlas Source connector for Confluent Cloud moves data from a MongoDB replica set into an Apache Kafka® cluster. The connector configures and consumes change stream event documents and publishes them to a Kafka topic.

Note

This is a Quick Start for the managed cloud connector. If you are installing the connector locally for Confluent Platform, see MongoDB Source Connector for Confluent Platform.

Features

Note

This connector supports MongoDB Atlas only and will not work with a self-managed MongoDB database.

The MongoDB Atlas Source connector provides the following features:

  • Topics created automatically: The connector automatically creates Kafka topics using the naming convention: <prefix>.<database-name>.<collection-name>. The tables are created with the properties: topic.creation.default.partitions=1 and topic.creation.default.replication.factor=3. You add the prefix when setting up the connection in the Quick Start steps. For more information, see Maximum message size. Note that if you want to create topics with specific settings, create the topics before running this connector.
  • Database authentication: Uses password authentication.
  • Output data formats: Supports Avro, Byte, JSON (schemaless), JSON Schema, Protobuf or String output data. 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.
  • Large size records: Supports MongoDb documents up to 8 MB in size on dedicated Kafka clusters and 2 MB on other clusters.
  • Select configuration properties:
    • poll.await.time.ms: The amount of time to wait before checking for new results in the change stream.
    • poll.max.batch.size: The maximum number of change stream documents to include in a single batch when polling for new data. This setting can be used to limit the amount of data buffered internally in the connector.

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.

Maximum message size

This connector creates topics automatically. When it creates topics, the internal connector configuration property max.message.bytes is set to the following:

  • Basic cluster: 2 MB
  • Standard cluster: 2 MB
  • Enterprise (Limited Availability) cluster: 2 MB
  • Dedicated cluster: 20 MB

For more information about Confluent Cloud clusters, see Kafka Cluster Types in Confluent Cloud.

Quick Start

Use this quick start to get up and running with the Confluent Cloud MongoDB Atlas Source connector. The quick start provides the basics of selecting the connector and configuring it to consume data from MongoDB and persist the data to Kafka.

Note

This connector supports MongoDB Atlas only and will not work with a self-managed MongoDB database.

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). See Schema Registry Enabled Environments for additional information.

  • Access to a MongoDB database. Note that the connection user must have privileged action “find” to query the MongoDB database. For more information, see Query and Write Actions.

  • The MongoDB hostname address must provide a service record (SRV). A standard connection string does not work.

  • The connector automatically creates Kafka topics using the naming convention: <prefix>.<database-name>.<collection-name>. The tables are created with the properties: topic.creation.default.partitions=1 and topic.creation.default.replication.factor=3. If you want to create topics with specific settings, create the topics before running this connector.

    Important

    If you are configuring granular access using a service account, and you leave the optional Topic prefix (topic.prefix) configuration property empty, the connector uses the Database name (database) entered as the prefix. You must grant ACL CREATE and WRITE access to the database name prefix (see ACL access). If both the topic.prefix and database configuration properties are not used, you must do one of the following:

    • If you know the databases to capture, create individual ACLs for each topic. The topic name will have the database name as the prefix.

    • Create ACLs for all Kafka topics, using the (*) wildcard in the ACL entries as shown below:

        confluent kafka acl create --allow --service-account
  "<service-account-id>" --operation create --topic "*"

.. code-block:: bash

  confluent kafka acl create --allow --service-account
  "<service-account-id>" --operation write --topic "*"

    • Create create RBAC role bindings.

  • If you have a VPC-peered cluster in Confluent Cloud, consider configuring a PrivateLink Connection between MongoDB Atlas and the VPC. For additional networking considerations, see Networking, DNS, and service endpoints. 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 MongoDB Atlas Source connector card.

MongoDB Atlas 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 MongoDB Atlas Source Connector screen, complete the following:

In the Topic prefix field, define a topic prefix your connector will use to publish to Kafka topics. The connector will Kafka topics using the following naming convention: <topic.prefix><tableName>. If you want to create topics with specific settings, create the topics before running this connector.

Important

If you are configuring granular access using a service account, and you leave the optional Topic prefix (topic.prefix) configuration property empty, the connector uses the Database name (database) entered as the prefix. You must grant ACL CREATE and WRITE access to the database name prefix (see ACL access). If both the topic.prefix and database configuration properties are not used, you must do one of the following:

  • If you know the databases to capture, create individual ACLs for each topic. The topic name will have the database name as the prefix.

  • Create ACLs for all Kafka topics, using the (*) wildcard in the ACL entries as shown below:

      confluent kafka acl create --allow --service-account
  "<service-account-id>" --operation create --topic "*"

.. code-block:: bash

  confluent kafka acl create --allow --service-account
  "<service-account-id>" --operation write --topic "*"

  • Create create RBAC role bindings.

Step 5: Check the Kafka topic.

After the connector is running, verify that MongoDB documents are populating the Kafka topic. If the config startup.mode=copy_existing and the connector restarts due to any reason, you may see duplicate records in the topic.

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

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-catalog-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 the required connector properties.

 {
     "connector.class": "MongoDbAtlasSource",
     "name": "<my-connector-name>",
     "kafka.auth.mode": "KAFKA_API_KEY",
     "kafka.api.key": "<my-kafka-api-key>",
     "kafka.api.secret": "<my-kafka-api-secret>",
     "topic.prefix": "<topic-prefix>",
     "connection.host": "<database-host-address>",
     "connection.user": "<database-username>",
     "connection.password": "<database-password>",
     "database": "<database-name>",
     "collection": "<database-collection-name>",
     "poll.await.time.ms": "5000",
     "poll.max.batch.size": "1000",
     "startup.mode": "copy_existing",
     "output.data.format": "JSON"
     "tasks.max": "1"
}

Note the following property definitions:

  • "connector.class": Identifies the connector plugin name.
  • "name": Sets a name for your new connector.

  • "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

  • (Optional) "topic.prefix": Enter a topic prefix. The connector automatically creates Kafka topics using the naming convention: <prefix>.<database-name>.<collection-name>. The tables are created with the properties: topic.creation.default.partitions=1 and topic.creation.default.replication.factor=3. If you want to create topics with specific settings, create the topics before running this connector. Note the following:

    • If you are configuring granular access using a service account, you must set up ACLs for the topic prefix.
    • If you are using a dedicated cluster and have a MongoDb document greater than 2MB in size, create the topic beforehand with property max.message.bytes set to match the largest document size or greater than the largest document size (8388608 bytes maximum).

    Important

    If you are configuring granular access using a service account, and you leave the optional Topic prefix (topic.prefix) configuration property empty, you must grant ACL CREATE and WRITE access to all the Kafka topics or create RBAC role bindings. To add ACLs, you use the (*) wildcard in the ACL entries as shown in the following examples.

    confluent kafka acl create --allow --service-account
"<service-account-id>" --operation create --topic "*"

    confluent kafka acl create --allow --service-account
"<service-account-id>" --operation write --topic "*"

  • (Optional) "topic.namespace.map": A JSON map that maps change stream document namespaces to topics. For example: {\"db\": \"dbTopic\", \"db.coll\": \"dbCollTopic\"} will map all change stream documents from the db database to dbTopic.<collectionName> apart from any documents from the db.coll namespace which map to the dbCollTopic topic. If you want to map all messages to a single topic use *. For example: {\"*\": \"everyThingTopic\", \"db.coll\": \"exceptionToTheRuleTopic\"} will map all change stream documents to the everyThingTopic apart from the db.coll messages. Note that any prefix configuration will still apply. If multiple collections with records having varying schema are mapped to a single topic with AVRO, JSON_SR, and PROTOBUF, then multiple schemas will be registered under a single subject name. If these schemas are not backward compatible to each other, the connector will fail until you change the schema compatibility in Confluent Cloud Schema Registry.

  • "connection.host": The MongoDB host. Use a hostname address and not a full URL. For example: cluster4-r5q3r7.gcp.mongodb.net. The MongoDB hostname address must provide a service record (SRV). A standard connection string does not work.

  • (Optional) "collection": The collection name. If the property is not used, all collections are watched in the supplied database.

  • (Optional) "poll.await.time.ms": The amount of time to wait before checking for new results in the change stream. If not used, this property defaults to 5000 ms (5 seconds).

  • (Optional) "poll.max.batch.size": The maximum number of change stream documents to include in a single batch when polling for new data. This setting can be used to limit the amount of data buffered internally in the connector. If not used, this property defaults to 1000 records.

  • (Optional) "pipeline": An array of JSON objects that represents the pipeline operations to filter or modify the change stream output. For example: [{"$match": {"ns.coll": {"$regex": /^(collection1|collection2)$/}}}] sets the connector to listen to the collection1 and collection2 collections only. If not used, this property defaults to an empty array.

  • (Optional) "startup.mode": Specifies how the connector should start up when there is no source offset available. Resuming a change stream requires a resume token, which the connector gets from the source offset. If no source offset is available, the connector may either ignore all or some of the existing source data, or may at first copy all existing source data and then continue with processing new data. When set to latest (default), the connector ignores all existing source data. If set to timestamp, the connector actuates startup.mode.timestamp.* properties. If no properties are configured, timestamp is equivalent to latest. If startup.mode=copy_existing, the connector copies all existing source data to Change Stream events. This setting is equivalent to the deprecated setting copy.existing=true.

  • (Optional) "startup.mode.timestamp.start.at.operation.time": Actuated only if startup.mode=timestamp. Specifies the starting point for the change stream. Accepted values can be an integer number of seconds since the Epoch in decimal format (for example, 30), or an instant in the ISO-8601 format with one second precision (for example, 1970-01-01T00:00:30Z), or a BSON Timestamp in the canonical extended JSON (v2) format (for example, {"$timestamp": {"t": 30, "i": 0}})

  • (Optional) "startup.mode.copy.existing.namespace.regex": Regex that matches the namespaces from which the existing documents are copied. A namespace is represented as databaseName.collectionName. For example, stats\.page.* matches all collections that start with page in the stats database.

  • (Optional) "startup.mode.copy.existing.pipeline": An array of JSON objects that describes the pipeline operations to run when copying existing data. It is applied to existing documents that are being copied. If not used, this property defaults to an empty array.

  • (Optional) "publish.full.document.only": Set whether to return only the fullDocument field from the change stream event document produced by any update event. The fullDocument field contains the most current version of the updated document. Sets the change.stream.full.document=updateLookup setting so updated documents will be included.

  • (Optional) "publish.full.document.only.tombstone.on.delete": When set to true, the connector returns the tombstone events when documents are deleted. Tombstone events contain the keys of deleted documents with null values. This setting applies only when publish.full.document.only is true.

  • (Optional) "change.stream.full.document": Determines what to return for update operations when using a Change Stream. The default setting returns the differences between the original document and the updated document. When set to updateLookup setting returns the differences between the original document and updated document as well as a copy of the entire updated document at a point in time after the update. The whenAvailable setting returns the updated document, if available. The required setting returns the updated document and raises an error if it is not available.

  • (Optional) "change.stream.full.document.before.change": Configures the document pre-image your change stream returns on update operations. The default setting suppresses the document pre-image. When set to whenAvailable setting returns the document pre-image if it’s available, before it was replaced, updated, or deleted. When set to required setting returns the document pre-image and raises an error if it is not available.

  • "output.data.format": Sets the output Kafka record value format (data coming from the connector). 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_SR (JSON Schema), or Protobuf).

    If you select AVRO, be sure to set Compatibility mode (schema.compatibility.level) to NONE in Schema Registry. Note that schemas are generated per document in isolation. If not set to NONE, there is a chance that the new schema generated for the new document will not be backward compatible with previous versions of the schema.

  • (Optional) "heartbeat.interval.ms": The number of milliseconds the connector waits between sending heartbeat messages. If not used, this property defaults to 0. Thus, no heartbeat message is sent by default. If set to a positive number, the connector sends heartbeat messages when source records are not published in the specified interval. This mechanism improves resumability of the connector for low volume namespaces. See the Invalid Resume Token page in MongoDb documentation for more information on this feature. When using SMTs, use predicates to prevent SMTs from processing the heartbeat messages. For example, if the heartbeat topic name is __mongodb_heartbeats and the connector is writing the actual database records into topics that do not share common prefix with the heartbeat topic; use the following configuration to prevent heartbeat messages from being processed by the transform with an alias say, mongoTransform: "predicates": "isHeartbeatTopicPrefix", "predicates.isHeartbeatTopicPrefix.type": "org.apache.kafka.connect.transforms.predicates.TopicNameMatches", "predicates.isHeartbeatTopicPrefix.pattern": "__mongodb.*", "transforms.mongoTransform.predicate": "isHeartbeatTopicPrefix", "transforms.mongoTransform.negate": "true".

  • (Optional) "heartbeat.topic.name": The name of the topic on which the connector should publish heartbeat messages. You must provide a positive value in the heartbeat.interval.ms setting to enable this feature. If setting the heartbeat messages for multiple connectors, you must ensure that the heartbeat topic names for the connectors are unique. If not set, this defaults to __mongodb_heartbeats.

  • "tasks.max": The connector supports running a single task.

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 definitions.

Step 4: Load the properties 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 mongo-db-source.json

Example output:

Created connector confluent-mongodb-source 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   | confluent-mongodb-source  | RUNNING | source

Step 6: Check the Kafka topic.

After the connector is running, verify that MongoDB documents are populating the Kafka topic. If the config startup.mode=copy_existing and the connector restarts due to any reason, you may see duplicate records in the topic.

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. If you are installing the connector locally for Confluent Platform, see MongoDB Source Connector for Confluent Platform.

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

Schema Config

schema.context.name

A schema context represents an independent scope in Schema Registry, and can be used to create any number of separate ‘sub-registries’ within one Schema Registry cluster. Please refer Confluent documentation for more details.

  • Type: string
  • Default: default
  • Importance: medium

How do you want to name your topic(s)?

topic.prefix

Prefix to prepend to table names to generate the name of the Apache Kafka® topic to publish data to.

  • Type: string
  • Importance: high
topic.namespace.map

JSON object that maps change stream document namespaces to topics. Any prefix configuration will still apply. In case multiple collections with records having varying schema are mapped to single topic with AVRO, JSON_SR, and PROTOBUF, then multiple schemas will be registered under single subject name. If these schemas are not backward compatible to each other, the connector will fail until you change the schema compatibility in Confluent Cloud Schema Registry.

  • Type: string
  • Default: “”
  • Importance: low

How should we connect to your MongoDB Atlas database?

connection.host

MongoDB Atlas connection host (e.g. confluent-test.mycluster.mongodb.net).

  • Type: string
  • Default: “”
  • Importance: high
connection.user

MongoDB Atlas connection user.

  • Type: string
  • Importance: high
connection.password

MongoDB Atlas connection password.

  • Type: password
  • Importance: high
database

MongoDB Atlas database name. If not set, all databases in the cluster are watched.

  • Type: string
  • Importance: high

Database details

collection

Single MongoDB Atlas collection to watch. If not set, all collections in the specified database are watched.

  • Type: string
  • Importance: medium

Connection details

poll.await.time.ms

The amount of time to wait before checking for new results on the change stream.

  • Type: int
  • Default: 5000 (5 seconds)
  • Valid Values: [1,…]
  • Importance: low
poll.max.batch.size

Maximum number of change stream documents to include in a single batch when polling for new data. This setting can be used to limit the amount of data buffered internally in the connector.

  • Type: int
  • Default: 100
  • Valid Values: [1,…,1000]
  • Importance: low
pipeline

An array of JSON objects describing the pipeline operations to filter or modify the change events output. For example, [{“$match”: {“ns.coll”: {“$regex”: /^(collection1|collection2)$/}}}] will set your source connector to listen to the “collection1” and “collection2” collections only.

  • Type: string
  • Default: []
  • Importance: medium
startup.mode

Specifies how the connector should start up when there is no source offset available. If set to ‘latest’, the connector ignores all existing source data. If set to ‘timestamp’, the connector actuates startup.mode.timestamp.* properties. If no properties are configured, timestamp is equivalent to latest. If startup.mode=copy_existing, the connector copies all existing source data to Change Stream events.

  • Type: string
  • Default: “”
  • Importance: high
startup.mode.copy.existing.namespace.regex

Regular expression that matches the namespaces (databaseName.collectionName) from which to copy data. For example, stats.page.* matches all collections that starts with “page” in “stats” database.

  • Type: string
  • Default: “”
  • Importance: medium
startup.mode.copy.existing.pipeline

An array of JSON objects describing the pipeline operations to run when copying existing data. It will only be applied for existing documents which are being copied.

  • Type: string
  • Default: “”
  • Importance: medium
startup.mode.timestamp.start.at.operation.time

Actuated only if startup.mode=timestamp. Specifies the starting point for the change stream.

  • Type: string
  • Default: “”
  • Importance: medium
batch.size

The number of documents to return in a batch.

  • Type: int
  • Default: 0
  • Valid Values: […,50]
  • Importance: low

Output messages

output.data.format

Sets the output Kafka record value format. Valid entries are AVRO, JSON_SR, PROTOBUF, JSON, STRING or BSON. 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: STRING
  • Importance: high
publish.full.document.only

Only publish the changed document instead of the full change stream document. Sets the change.stream.full.document=updateLookup automatically so updated documents will be included.

  • Type: boolean
  • Default: false
  • Importance: high
publish.full.document.only.tombstone.on.delete

Return the tombstone events when documents are deleted. Tombstone events contain the keys of deleted documents with null values. This setting applies only when publish.full.document.only is true

  • Type: boolean
  • Default: false
  • Importance: high
json.output.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
change.stream.full.document

Determines what to return for update operations when using a Change Stream. When set to ‘updateLookup’ setting returns the differences between the original document and updated document as well as a copy of the entire updated document at a point in time after the update. The ‘whenAvailable’ setting returns the updated document, if available. The ‘required’ setting returns the updated document and raises an error if it is not available.

  • Type: string
  • Default: default
  • Importance: high
change.stream.full.document.before.change

Configures the document pre-image your change stream returns on update operations. When set to ‘whenAvailable’ setting returns the document pre-image if it’s available, before it was replaced, updated, or deleted. When set to ‘required’ setting returns the document pre-image and raises an error if it is not available.

  • Type: string
  • Default: default
  • Importance: high
output.json.format

The output format of json strings can be configured to be either: DefaultJson: The legacy strict json formatter. ExtendedJson: The fully type safe extended json formatter. SimplifiedJson: Simplified Json, with ObjectId, Decimals, Dates and Binary values represented as strings. Users can provide their own implementation of the com.mongodb.kafka.connect.source.json.formatter.

  • Type: string
  • Default: DefaultJson
  • Importance: high
topic.separator

Separator to use when joining prefix, database, collection, and suffix values. This generates the name of the Kafka topic to publish data to. Used by the ‘DefaultTopicMapper’.

  • Type: string
  • Default: .
  • Importance: low
topic.suffix

Suffix to append to database and collection names to generate the name of the Kafka topic to publish data to.

  • Type: string
  • Importance: low
value.subject.name.strategy

Determines how to construct the subject name under which the value schema is registered with Schema Registry. In the case of RecordNameStrategy, schema is registered under subject default; use transforms SetSchemaMetadata$Value to set a different schema name.

  • Type: string
  • Default: TopicNameStrategy
  • Valid Values: RecordNameStrategy, TopicNameStrategy
  • Importance: medium

Error handling

heartbeat.interval.ms

The number of milliseconds the connector waits between sending heartbeat messages. The connector sends heartbeat messages when source records are not published in the specified interval. This mechanism improves resumability of the connector for low volume namespaces. When using SMTs, use predicates to prevent SMTs from processing the heartbeat messages. See connector documentation for more details.

  • Type: int
  • Default: 0
  • Importance: medium
heartbeat.topic.name

The name of the topic on which the connector should publish heartbeat messages. You must provide a positive value in the “heartbeat.interval.ms” setting to enable this feature.

  • Type: string
  • Default: __mongodb_heartbeats
  • Importance: medium
mongo.errors.tolerance

Use this property if you would like to configure the connector’s error handling behavior differently from the Connect framework’s.

  • Type: string
  • Default: NONE
  • Importance: medium
mongo.errors.deadletterqueue.topic.name

Whether to output conversion errors to the dead letter queue. Stops poison messages when using schemas, any message will be outputted as extended json on the specified topic. By default messages are not outputted to the dead letter queue. Also requires errors.tolerance=all.

  • Type: string
  • Importance: medium

Server API

server.api.version

The server API version to use. Disabled by default.

  • Type: string
  • Importance: low
server.api.deprecation.errors

Sets whether the connector requires use of deprecated server APIs to be reported as errors.

  • Type: boolean
  • Default: false
  • Importance: low
server.api.strict

Sets whether the application requires strict server API version enforcement.

  • Type: boolean
  • Default: false
  • Importance: low

Number of tasks for this connector

tasks.max

Maximum number of tasks for the connector.

  • Type: int
  • Valid Values: [1,…,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.

../_images/topology.png