# Amazon DynamoDB Sink Connector for Confluent Cloud The fully managed Amazon DynamoDB Sink connector for Confluent Cloud exports messages from Apache Kafka® topics to Amazon DynamoDB tables. The connector periodically polls data from Kafka and writes it to Amazon DynamoDB. The data from each Kafka topic is batched and sent to DynamoDB. Because of constraints from DynamoDB, each batch can only contain one change per key, and each failure in a batch must be handled before the next batch is processed. These constraints ensure exactly once delivery. When a table doesn’t exist, the connector creates the table dynamically (depending on the connector configuration and permissions). #### NOTE * This Quick Start is for the fully managed Confluent Cloud connector. If you are installing the connector locally for Confluent Platform, see [Amazon DynamoDB Sink Connector for Confluent Platform](https://docs.confluent.io/kafka-connectors/aws-dynamodb/current/). * 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 * **Auto-created tables**: Tables can be auto-created based on topic names and auto-evolved based on the record schema. * **Select configuration properties**: - `aws.dynamodb.pk.hash`: Defines how the DynamoDB table hash key is extracted from the records. By default, the Kafka partition number where the record is generated is used as the hash key. Other record references can be used to create the hash key. See [DynamoDB hash keys and sort keys](#cc-amazon-dynamodb-sink-hash-sort) for examples. - `aws.dynamodb.pk.sort`: Defines how the DynamoDB table sort key is extracted from the records. By default, the record offset is used as the sort key. The sort key can be created from other references. See [DynamoDB hash keys and sort keys](#cc-amazon-dynamodb-sink-hash-sort) for examples. * **Provider integration support**: The connector supports IAM role-based authorization using Confluent Provider Integration. For more information about provider integration setup, see the [IAM roles authentication](#cc-amazon-dynamodb-sink-setup-connection). * **Secret manager integration**: The connector supports secret manager integration. For `Access Keys` based authentication, the connector can retrieve the following configurations from an integrated secret manager at runtime as needed. | **Secret manager managed configuration** | **Type** | |--------------------------------------------|------------| | `aws.access.key.id` | `PASSWORD` | | `aws.secret.access.key` | `PASSWORD` | For more information, see [Create a secret manager integration in Confluent Cloud](secret-manager-integration/overview.md#cloud-secret-manager-quickstart). 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 [Amazon DynamoDB Sink Connector](limits.md#cc-amazon-dynamodb-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). ## DynamoDB IAM policy Create an IAM user for the connector. Assign an IAM policy to the user you create. The policy must have the following minimum permissions. * CreateTable * BatchWriteItem * Scan * DescribeTable You can copy the following JSON policy. For more information, see [Creating policies on the JSON tab](https://docs.aws.amazon.com/IAM/latest/UserGuide/access_policies_create-console.html#access_policies_create-json-editor). ```json { "Version": "2012-10-17", "Statement": [ { "Sid": "", "Effect": "Allow", "Action": [ "dynamodb:CreateTable", "dynamodb:BatchWriteItem", "dynamodb:Scan", "dynamodb:DescribeTable" ], "Resource": "*" } ] } ``` ## DynamoDB hash keys and sort keys The following examples show how the `aws.dynamodb.pk.hash` and `aws.dynamodb.pk.sort` are used. The following Avro record is used for the examples: ```text { "ordertime": 1511538140542, "orderid": 3243, "itemid": "Item_117", "orderunits": 1.135368875862714, "address": { "city": "City_43", "state": "State_53", } } ``` **Example 1** The table hash key is set to the `"partition"` number where the record was generated. The table sort key is the record `"offset"`. The following example uses these default configuration properties: * `"aws.dynamodb.pk.hash":"partition"` * `"aws.dynamodb.pk.sort":"offset"` Using these properties, the table in DynamoDB would be similar to the following example: | partition | offset | address | itemid | orderid | ordertime | orderunits | |-------------|----------|---------------------------------------------------|----------|-----------|---------------|--------------| | 0 | 6075 | {“city”:{“S”:City_66}, “state”:{“S”:”State_42},…} | Item_246 | 6075 | 1503153618445 | 3.08187 | | 0 | 6076 | {“city”:{“S”:City_38}, “state”:{“S”:”State_49},…} | Item_536 | 6076 | 1515872966736 | 1.62643 | | 0 | 6077 | {“city”:{“S”:City_32}, “state”:{“S”:”State_62},…} | Item_997 | 6077 | 1515872966736 | 4.18973 | **Example 2** The table hash key is set to `"value.orderid"`. The table sort key is `""`. Note that in this example, no sort key is required so you can use an empty string: `"aws.dynamodb.pk.sort":""`. * `"aws.dynamodb.pk.hash":"value.orderid"` * `"aws.dynamodb.pk.sort":""` Using these properties, the table in DynamoDB would be similar to the following example: | orderid | address | itemid | ordertime | orderunits | |-----------|---------------------------------------------------|----------|---------------|--------------| | 2007 | {“city”:{“S”:City_69}, “state”:{“S”:”State_19},…} | Item_809 | 1502071602628 | 8.98667 | | 2011 | {“city”:{“S”:City_32}, “state”:{“S”:”State_11},…} | Item_524 | 1494848995282 | 2.58143 | | 2012 | {“city”:{“S”:City_88}, “state”:{“S”:”State_94},…} | Item_169 | 1491811930181 | 1.57163 | **Example 3** The table hash key is set to `"value.orderid"`. The table sort key is set to `"value.ordertime"`. Note that in this example, one of the record fields (`"ordertime"`) is used as the sort key. * `"aws.dynamodb.pk.hash":"value.orderid"` * `"aws.dynamodb.pk.sort":"value.ordertime"` Using these properties, the table in DynamoDB would be similar to the following example: | orderid | ordertime | address | itemid | orderunits | |-----------|---------------|---------------------------------------------------|----------|--------------| | 4520 | 1519049522647 | {“city”:{“S”:City_99}, “state”:{“S”:”State_38},…} | Item_650 | 7.65878 | | 4522 | 1519049522647 | {“city”:{“S”:City_72}, “state”:{“S”:”State_89},…} | Item_503 | 2.13833 | | 4523 | 1507101063792 | {“city”:{“S”:City_74}, “state”:{“S”:”State_99},…} | Item_369 | 2.13833 | ## Managing Throughput When the connector creates a table automatically, [10 write capacity units](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/ProvisionedThroughput.html) are provisioned. If the connector needs to send records faster than the provisioned capacity, you may see the following error message: ```text Hit provisioning capacity, will retry indefinitely.. Increase your throughput capacity ``` You can increase the write capacity or use [Amazon DynamoDB Auto Scaling](https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/AutoScaling.html). ## Quick Start Use this quick start to get up and running with the Confluent Cloud Amazon DynamoDB Sink connector. The quick start provides the basics of selecting the connector and configuring it to stream events to Amazon Redshift. Prerequisites : - Authorized access to a [Confluent Cloud](https://www.confluent.io/confluent-cloud/) cluster on Amazon Web Services. - 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 AWS and the Amazon DynamoDB database. For more information, see [DynamoDB IAM policy](#cc-dynamodb-policy). - The database must be in the same region as your Confluent Cloud cluster. - For networking considerations, see [Networking and DNS](overview.md#connect-internet-access-resources). To use a set of public egress IP addresses, see [Public Egress IP Addresses for Confluent Cloud Connectors](static-egress-ip.md#cc-static-egress-ips).
- Kafka cluster credentials. The following lists the different ways you can provide credentials. - Enter an existing [service account](service-account.md#s3-cloud-service-account) resource ID. - Create a Confluent Cloud [service account](service-account.md#s3-cloud-service-account) for the connector. Make sure to review the ACL entries required in the [service account documentation](service-account.md#s3-cloud-service-account). 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](https://docs.confluent.io/confluent-cli/current/command-reference/api-key/confluent_api-key_create.html) *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 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 **Amazon DynamoDB Sink** connector card.  #### Step 4: Enter the connector details #### NOTE * Ensure you have all your [prerequisites](#cc-amazon-dynamodb-sink-prereqs) completed. * An asterisk ( \* ) designates a required entry. At the **Add Amazon DynamoDB Sink Connector** screen, complete the following: ### Topic selection If you’ve already populated your Kafka topics, select the topics you want to connect from the **Topics** list. To create a new topic, click **+Add new topic**. ### 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: **Authentication method** - **Authentication method**: Select how you want to authenticate with AWS. * If you select **Access Keys**, enter your AWS credentials in the **Amazon Access Key ID** and **Amazon Secret Access Key fields**. For information about how to set these up, [Access Keys](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_access-keys.html). * If you select **IAM Roles**, choose an existing integration name under Provider integration name dropdown that has access to your resource. For more information, see [Manage Provider Integration for Fully Managed Connectors in Confluent Cloud](provider-integration.md#cloud-pi-quickstart). - **Use secret manager**: Fetch sensitive configuration values from a secret manager. **AWS credentials** - **Provider Integration**: Select an existing integration that has access to your resource if you select **IAM Roles** as your authentication method. - **AWS access key ID**: Enter your Amazon Access Key ID to allow this connector to access your DynamoDB resource if you select **Access Keys** as your authentication method. - **AWS secret access key**: Enter your Amazon Secret Access Key to allow this connector to access your DynamoDB resource if you select **Access Keys** as your authentication method. **Secret manager configuration** - **Secret manager**: Select the secret manager to use for retrieving sensitive data. - **Configurations from Secret manager**: Select the configurations whose values Confluent Cloud should fetch from the secret manager. - **Provider Integration**: Select an existing integration that has access to your resource if you select **IAM Roles** as your authentication method. 2. Click **Continue**. ### Configuration #### NOTE Configuration properties that are not shown in the Cloud Console use the default values. See [Configuration Properties](#cc-amazon-dynamodb-sink-config-properties) for all property values and definitions. - **Input Kafka record value format**: Sets the input Kafka record value format. Valid entries are `AVRO`, `JSON_SR`, `PROTOBUF`, or `JSON`. A valid schema must be available in [Schema Registry](../get-started/schema-registry.md#cloud-sr-config) to use a schema-based message format (for example, Avro, JSON Schema, or Protobuf). - **DynamoDB hash key**: In the **DynamoDB hash key** and **DynamoDB sort key** fields, enter the hash key and sort key, respectively. By default, the Kafka partition number is used for the hash key and the record offset is used as the sort key. For a few examples of how these keys work with other record references, see [DynamoDB hash keys and sort keys](#cc-amazon-dynamodb-sink-hash-sort). Note that the maximum size of a partition using the default configuration is limited to 10 GB (defined by Amazon DynamoDB). - **DynamoDB sort key**: In the **DynamoDB hash key** and **DynamoDB sort key** fields, enter the hash key and sort key, respectively. By default, the Kafka partition number is used for the hash key and the record offset is used as the sort key. For a few examples of how these keys work with other record references, see [DynamoDB hash keys and sort keys](#cc-amazon-dynamodb-sink-hash-sort). Note that the maximum size of a partition using the default configuration is limited to 10 GB (defined by Amazon DynamoDB). ### **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). - **Input Kafka record key format**: Sets the input Kafka record key format. Valid entries are AVRO, BYTES, JSON, JSON_SR, PROTOBUF, or STRING. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF - **Table Name Format**: A format string for the destination table name, which may contain ‘${topic}’ as a placeholder for the originating topic name. For example, `kafka_${topic}` for the topic ‘orders’ will map to the table name ‘kafka_orders’. - **Behavior on Null Values**: How to handle records with a non-null key and a null value, for example Kafka tombstone records. Use the `UPSERT` option to update and insert the tombstone records along with the key. Use the `IGNORE` option to skip processing of the tombstone records. Use the `DELETE` option to delete the corresponding tombstone record in DynamoDB table. - **Instant Flush**: If set to true, the connector flushes the data to DynamoDB. This setting is for low throughput workloads and not for high throughput workloads. If enabled, it affects the DynamoDB API calls for the user. **Additional Configs** - **Value Converter Replace Null With Default**: Specifies whether to replace fields that have a default value and that are null to the default value. When set to `true`, the connector uses the default value; otherwise, it uses `null`. Applies to the `JSON` converter. - **Value Converter Schema ID Deserializer**: Sets the class name of the schema ID deserializer for values. The deserializer reads schema IDs from 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`. - **Schema ID For Value Converter**: Sets the schema ID to use for deserialization when using `ConfigSchemaIdDeserializer`. This lets you specify a fixed schema ID for deserializing message values. This property is applicable only when `value.converter.value.schema.id.deserializer` is set to `ConfigSchemaIdDeserializer`. - **Value Converter Schemas Enable**: Includes schema within each of the serialized values. Input messages must contain `schema` and `payload` fields and must not contain additional fields. For plain `JSON` data, set this to `false`. Applies to the `JSON` converter. - **Errors Tolerance**: Use this property to configure the connector’s error handling behavior. #### WARNING Use this property with caution for sink connectors, as it can lead to data loss. If you set this property to `all`, the connector does not fail on errant records, but logs them (and sends to DLQ for sink connectors) and continues processing. If you set this property to `none`, the connector task fails on errant records. - **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. Applies to the `AVRO`, `PROTOBUF`, and `JSON_SR` converters. - **Key Converter Schema ID Deserializer**: Sets the class name of the schema ID deserializer for keys. The deserializer reads schema IDs from message headers. - **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. - **Schema GUID For Key Converter**: Sets the schema GUID to use for deserialization when using `ConfigSchemaIdDeserializer`. This lets you specify a fixed schema GUID for deserializing message keys. This property is applicable only when `key.converter.key.schema.id.deserializer` is set to `ConfigSchemaIdDeserializer`. - **Schema GUID For Value Converter**: Sets the schema GUID to use for deserialization when using `ConfigSchemaIdDeserializer`. This lets you specify a fixed schema GUID for deserializing message values. This property is applicable only when `value.converter.value.schema.id.deserializer` is set to `ConfigSchemaIdDeserializer`. - **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. - **Schema ID For Key Converter**: Sets the schema ID to use for deserialization when using `ConfigSchemaIdDeserializer`. This lets you specify a fixed schema ID for deserializing message keys. This property is applicable only when `key.converter.key.schema.id.deserializer` is set to `ConfigSchemaIdDeserializer`. **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. **Consumer configuration** - **Max poll interval(ms)**: Sets the maximum delay between subsequent consume requests to Kafka. Use this property to improve connector performance in cases when the connector cannot send records to the sink system. The default is 300,000 milliseconds (5 minutes). - **Max poll records**: Sets the maximum number of records to consume from Kafka in a single request. Use this property to improve connector performance in cases when the connector cannot send records to the sink system. The default is 500 records. **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). See [Configuration Properties](#cc-amazon-dynamodb-sink-config-properties) for all property values and definitions. - 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 recommended tasks, enter the number of [tasks](/platform/current/connect/concepts.html#tasks) for the connector to use in the **Tasks** field. 2. Click **Continue**. ### Review and Launch 1. Verify the connection details. 2. Click **Launch**. The status for the connector should go from **Provisioning** to **Running**. #### Step 5: Check the results in DynamoDB Check to verify that the database is being populated. 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 Complete the following steps to set up and run the connector using the Confluent CLI. #### NOTE Make sure you have all your [prerequisites](#cc-amazon-dynamodb-sink-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 required and optional connector properties. ```none { "name": "DynamoDbSinkConnector_0", "config": { "topics": "pageviews", "input.data.format": "AVRO", "connector.class": "DynamoDbSink", "name": "DynamoDbSinkConnector_0", "kafka.auth.mode": "KAFKA_API_KEY", "kafka.api.key": "", "kafka.api.secret": "", "aws.access.key.id": "********************", "aws.secret.access.key": "****************************************", "aws.dynamodb.pk.hash": "value.userid", "aws.dynamodb.pk.sort": "value.pageid", "table.name.format": "kafka-${topic}", "tasks.max": "1" } } ``` Note the following property definitions: * `"name"`: Sets a name for your new connector. * `"connector.class"`: Identifies the connector plugin name. * `"topics"`: Identifies the topic name or a comma-separated list of topic names. * `"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 ``` * `"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_SR (JSON Schema), or Protobuf). * `"aws.dynamodb.pk.hash"`: Defines how the DynamoDB table hash key is extracted from the records. By default, the Kafka partition number where the record is generated is used as the hash key. The hash key can be created from other record references. See [DynamoDB hash keys and sort keys](#cc-amazon-dynamodb-sink-hash-sort) for examples. Note that the maximum size of a partition using the default configuration is limited to 10 GB (defined by Amazon DynamoDB). * `"aws.dynamodb.pk.sort"`: Defines how the DynamoDB table sort key is extracted from the records. By default, the record offset is used as the sort key. If no sort key is required, use an empty string for this property `""`. The sort key can be created from other record references. See [DynamoDB hash keys and sort keys](#cc-amazon-dynamodb-sink-hash-sort) for examples. #### NOTE You cannot set this property to an empty string (“”) in the Confluent Cloud console. To use an empty string, use the Confluent CLI. Alternatively, you can enter a single space (” “) in the console, which results in the same behavior. * `"table.name.format"`: The property is optional and defaults to the name of the Kafka topic. To create a table name format use the syntax `${topic}`. For example, `kafka_${topic}` for the topic `orders` maps to the table name `kafka_orders`. * `"tasks.max"`: Maximum number of tasks the connector can run. See Confluent Cloud [connector limitations](limits.md#cc-amazon-redshift-sink-limits) for additional task information. **SMTs**: For details about adding SMTs using the Confluent CLI, see the [Single Message Transformations](single-message-transforms.md#cc-single-message-transforms) documentation. For a list of SMTs that are not supported with this connector, see [Unsupported transformations](single-message-transforms.md#cc-single-message-transforms-unsupported-transforms). See [Configuration Properties](#cc-amazon-dynamodb-sink-config-properties) for all property values and definitions. #### Step 4: Load the configuration 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 dynamodb-sink-config.json ``` Example output: ```none Created connector DynamoDbSinkConnector_0 lcc-ix4dl ``` #### Step 5: 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 +-----------+-------------------------+---------+------+ lcc-ix4dl | DynamoDbSinkConnector_0 | RUNNING | sink ``` #### Step 6: Check the results in Redshift. Check to verify that the database is being populated. 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). ### Which topics do you want to get data from? `topics.regex` : A regular expression that matches the names of the topics to consume from. This is useful when you want to consume from multiple topics that match a certain pattern without having to list them all individually.
* Type: string * Importance: low `topics` : Identifies the topic name or a comma-separated list of topic names.
* Type: list * Importance: high `errors.deadletterqueue.topic.name` : The name of the topic to be used as the dead letter queue (DLQ) for messages that result in an error when processed by this sink connector, or its transformations or converters. Defaults to ‘dlq-${connector}’ if not set. The DLQ topic will be created automatically if it does not exist. You can provide `${connector}` in the value to use it as a placeholder for the logical cluster ID.
* Type: string * Default: dlq-${connector} * Importance: low ### 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, 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 `input.key.format` : Sets the input Kafka record key format. Valid entries are AVRO, BYTES, JSON, JSON_SR, PROTOBUF, or STRING. 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: BYTES * Valid Values: AVRO, BYTES, JSON, JSON_SR, PROTOBUF, STRING * 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, 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 ### Authentication method `authentication.method` : Select how you want to authenticate with AWS.
* Type: string * Default: Access Keys * Importance: high `secret.manager.enabled` : Fetch sensitive configuration values from a secret manager.
* Type: boolean * Default: false * Importance: high ### Secret manager configuration `secret.manager` : Select the secret manager to use for retrieving sensitive data.
* Type: string * Importance: high `secret.manager.managed.configs` : Select the configurations to fetch their values from the secret manager.
* Type: list * Importance: high `secret.manager.provider.integration.id` : Select an existing provider integration that has access to your secret manager.
* Type: string * Importance: high ### AWS credentials `aws.access.key.id` : * Type: password * Importance: high `aws.secret.access.key` : * Type: password * Importance: high `provider.integration.id` : Select an existing integration that has access to your resource. In case you need to integrate a new IAM role, use provider integration
* Type: string * Importance: high ### DynamoDB Parameters `aws.dynamodb.pk.hash` : * Type: string * Default: partition * Importance: high `aws.dynamodb.pk.sort` : * Type: string * Default: offset * Importance: high `table.name.format` : A format string for the destination table name, which may contain ‘${topic}’ as a placeholder for the originating topic name.
For example, `kafka_${topic}` for the topic ‘orders’ will map to the table name ‘kafka_orders’.
* Type: string * Default: ${topic} * Importance: medium `behavior.on.null.values` : How to handle records with a non-null key and a null value (i.e. Kafka tombstone records). Use option ‘UPSERT’ to upsert the tombstone records along with the key, option ‘IGNORE’ to skip processing of the tombstone records and option ‘DELETE’ to delete the corresponding tombstone record in DynamoDB table.
* Type: string * Default: UPSERT * Importance: medium `aws.dynamodb.instant.flush` : When set to true, the connector flushes the data immediately to DynamoDB. Note: This setting is strictly for low throughput workloads and not for high throughput workloads. If enabled, it will affect the DynamoDB API calls for the user.
* Type: boolean * Default: false * Importance: medium ### 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 ### Additional Configs `consumer.override.auto.offset.reset` : Defines the behavior of the consumer when there is no committed position (which occurs when the group is first initialized) or when an offset is out of range. You can choose either to reset the position to the “earliest” offset (the default) or the “latest” offset. You can also select “none” if you would rather set the initial offset yourself and you are willing to handle out of range errors manually. More details: [https://docs.confluent.io/platform/current/installation/configuration/consumer-configs.html#auto-offset-reset](https://docs.confluent.io/platform/current/installation/configuration/consumer-configs.html#auto-offset-reset)
* Type: string * Importance: low `consumer.override.isolation.level` : Controls how to read messages written transactionally. If set to read_committed, consumer.poll() will only return transactional messages which have been committed. If set to read_uncommitted (the default), consumer.poll() will return all messages, even transactional messages which have been aborted. Non-transactional messages will be returned unconditionally in either mode. More details: [https://docs.confluent.io/platform/current/installation/configuration/consumer-configs.html#isolation-level](https://docs.confluent.io/platform/current/installation/configuration/consumer-configs.html#isolation-level)
* Type: string * Importance: low `header.converter` : The converter class for the headers. This is used to serialize and deserialize the headers of the messages.
* Type: string * Importance: low `key.converter.use.schema.guid` : The schema GUID to use for deserialization when using ConfigSchemaIdDeserializer. This allows you to specify a fixed schema GUID to be used for deserializing message keys. Only applicable when key.converter.key.schema.id.deserializer is set to ConfigSchemaIdDeserializer.
* Type: string * Importance: low `key.converter.use.schema.id` : The schema ID to use for deserialization when using ConfigSchemaIdDeserializer. This allows you to specify a fixed schema ID to be used for deserializing message keys. Only applicable when key.converter.key.schema.id.deserializer is set to ConfigSchemaIdDeserializer.
* Type: int * Importance: low `value.converter.allow.optional.map.keys` : Allow optional string map key when converting from Connect Schema to Avro Schema. Applicable for Avro Converters.
* Type: boolean * Importance: low `value.converter.auto.register.schemas` : Specify if the Serializer should attempt to register the Schema.
* Type: boolean * Importance: low `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 `value.converter.enhanced.avro.schema.support` : Enable enhanced schema support to preserve package information and Enums. Applicable for Avro Converters.
* Type: boolean * Importance: low `value.converter.enhanced.protobuf.schema.support` : Enable enhanced schema support to preserve package information. Applicable for Protobuf Converters.
* Type: boolean * Importance: low `value.converter.flatten.unions` : Whether to flatten unions (oneofs). Applicable for Protobuf Converters.
* Type: boolean * Importance: low `value.converter.generate.index.for.unions` : Whether to generate an index suffix for unions. Applicable for Protobuf Converters.
* Type: boolean * Importance: low `value.converter.generate.struct.for.nulls` : Whether to generate a struct variable for null values. Applicable for Protobuf Converters.
* Type: boolean * Importance: low `value.converter.int.for.enums` : Whether to represent enums as integers. Applicable for Protobuf Converters.
* Type: boolean * Importance: low `value.converter.latest.compatibility.strict` : Verify latest subject version is backward compatible when use.latest.version is true.
* Type: boolean * Importance: low `value.converter.object.additional.properties` : Whether to allow additional properties for object schemas. Applicable for JSON_SR Converters.
* Type: boolean * Importance: low `value.converter.optional.for.nullables` : Whether nullable fields should be specified with an optional label. Applicable for Protobuf Converters.
* Type: boolean * Importance: low `value.converter.optional.for.proto2` : Whether proto2 optionals are supported. Applicable for Protobuf Converters.
* Type: boolean * Importance: low `value.converter.scrub.invalid.names` : Whether to scrub invalid names by replacing invalid characters with valid characters. Applicable for Avro and Protobuf Converters.
* Type: boolean * Importance: low `value.converter.use.latest.version` : Use latest version of schema in subject for serialization when auto.register.schemas is false.
* Type: boolean * Importance: low `value.converter.use.optional.for.nonrequired` : Whether to set non-required properties to be optional. Applicable for JSON_SR Converters.
* Type: boolean * Importance: low `value.converter.use.schema.guid` : The schema GUID to use for deserialization when using ConfigSchemaIdDeserializer. This allows you to specify a fixed schema GUID to be used for deserializing message values. Only applicable when value.converter.value.schema.id.deserializer is set to ConfigSchemaIdDeserializer.
* Type: string * Importance: low `value.converter.use.schema.id` : The schema ID to use for deserialization when using ConfigSchemaIdDeserializer. This allows you to specify a fixed schema ID to be used for deserializing message values. Only applicable when value.converter.value.schema.id.deserializer is set to ConfigSchemaIdDeserializer.
* Type: int * Importance: low `value.converter.wrapper.for.nullables` : Whether nullable fields should use primitive wrapper messages. Applicable for Protobuf Converters.
* Type: boolean * Importance: low `value.converter.wrapper.for.raw.primitives` : Whether a wrapper message should be interpreted as a raw primitive at root level. Applicable for Protobuf 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: all * Importance: low `key.converter.key.schema.id.deserializer` : The class name of the schema ID deserializer for keys. This is used to deserialize schema IDs from the message headers.
* Type: string * Default: io.confluent.kafka.serializers.schema.id.DualSchemaIdDeserializer * Importance: low `key.converter.key.subject.name.strategy` : How to construct the subject name for key schema registration.
* Type: string * Default: TopicNameStrategy * Importance: low `key.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 Key Converter.
* Type: boolean * Default: true * Importance: low `key.converter.schemas.enable` : Include schemas within each of the serialized keys. Input message keys must contain schema and payload fields and may not contain additional fields. For plain JSON data, set this to false. Applicable for JSON Key Converter.
* Type: boolean * Default: false * 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.flatten.singleton.unions` : Whether to flatten singleton unions. Applicable for Avro and JSON_SR Converters.
* Type: boolean * Default: false * 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.deserializer` : The class name of the schema ID deserializer for values. This is used to deserialize schema IDs from the message headers.
* Type: string * Default: io.confluent.kafka.serializers.schema.id.DualSchemaIdDeserializer * 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 ## FAQs Find answers to frequently asked questions about the Amazon DynamoDB Sink connector for Confluent Cloud. ### Hash keys, sort keys, and table configuration #### Why do I see `Please make sure that the target record matches the KeySchema for the hashKey and sortKey` errors? This error occurs when the connector cannot find the values for the configured hash key or sort key in the Kafka record. ##### Common causes * Incorrect `aws.dynamodb.pk.hash` or `aws.dynamodb.pk.sort` configuration. * Field names not matching the Kafka record schema. * Sort key configured when not needed. ##### Resolution Verify that the hash key and sort key field references match fields in your Kafka record. If no sort key is needed, set `aws.dynamodb.pk.sort` to an empty string (`""`) using the CLI or API. In the Confluent Cloud console, enter a single space (`" "`) as a workaround since empty strings are not supported in the UI. See the [DynamoDB hash keys and sort keys]() section in this document for examples. #### How do I configure the connector without a sort key? Set `aws.dynamodb.pk.sort` to an empty string (`""`) using the Confluent CLI or Connect API. The Confluent Cloud console does not support empty strings directly. As a workaround, enter a single space (`" "`) in the console, which produces the same behavior. See the [DynamoDB hash keys and sort keys]() section for configuration examples. ### Throughput and performance #### Why do I see `Hit provisioning capacity, will retry indefinitely` errors? This error indicates the connector is writing records faster than the DynamoDB table’s provisioned write capacity allows. When the connector auto-creates a table, it provisions 10 write capacity units by default, which may be insufficient for high-throughput workloads. ##### Resolution Increase the write capacity units for your DynamoDB table. Alternatively, enable Amazon DynamoDB Auto Scaling to automatically adjust capacity based on workload. See the [Managing Throughput]() section in this document. #### Why does my connector have high latency for low-volume topics? The connector batches records before writing to DynamoDB. Each batch can contain up to 25 records. For low-volume topics, the connector may wait to accumulate records before sending a batch, resulting in higher end-to-end latency (potentially 60-90 seconds or more). This batching behavior is expected due to DynamoDB’s batch write constraints. To flush records immediately rather than waiting for a full batch, set the `aws.dynamodb.instant.flush` configuration property to `true`. ### IAM permissions and authentication #### What IAM permissions are required for the connector? The connector requires the following minimum IAM permissions: `CreateTable`, `BatchWriteItem`, `Scan`, and `DescribeTable`. See the [DynamoDB IAM policy]() section in this document for a sample IAM policy. If using Provider Integration for IAM role-based authorization, ensure the IAM role has these permissions. #### Why does my connector fail with authentication or permission errors? ##### Common causes * Missing or incorrect AWS access key and secret. * IAM user lacking required DynamoDB permissions. * IAM role misconfiguration when using Provider Integration. ##### Resolution Verify AWS credentials. Ensure the IAM user or role has the minimum required permissions (`CreateTable`, `BatchWriteItem`, `Scan`, `DescribeTable`). Test permissions by manually writing to the DynamoDB table using the same credentials. ### Data format #### What data formats does the connector support? The connector supports Avro, JSON Schema (JSON_SR), Protobuf, and JSON input formats. Schema Registry must be enabled when using schema-based formats (Avro, JSON_SR, Protobuf). #### Why does my connector fail with schema compatibility errors? ##### Common causes * Unsupported schema types (such as Avro “oneOf” unions). * Schema mismatches between the Kafka record and DynamoDB table structure. ##### Resolution Ensure your Kafka record schema uses types compatible with the connector. If using complex union types, consider restructuring the schema or splitting data into separate topics with simpler schemas. ## 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. [](https://docs.confluent.io/platform/current/tutorials/examples/cloud-etl/docs/index.html) * Try [Confluent Cloud on AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-g5ujul6iovvcy?trk=14575e70-1766-4f20-8083-0c2757a1ec75&sc_channel=el) with $1000 of free usage for 30 days, and pay as you go. No credit card is required.