# SFTP Sink Connector for Confluent Cloud The fully managed SFTP Sink connector for Confluent Cloud exports data from Apache Kafka® topics to files in an SFTP directory. The fully managed SFTP Sink connector periodically polls data from Kafka and writes this data to SFTP files. A time-based partitioner is used to split the data of every Kafka partition into chunks. Each chunk of data is represented as a file. The file name encodes the topic, the Kafka partition, and the start offset of this data chunk. The size of each data chunk is determined by the number of records written and by schema compatibility. #### NOTE * This Quick Start is for the fully managed Confluent Cloud connector. If you are installing the connector locally for Confluent Platform, see [SFTP Sink Connector for Confluent Platform](https://docs.confluent.io/kafka-connectors/sftp/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 The SFTP Sink connector supports the following features: * **Exactly once delivery**: Records that are exported using a deterministic partitioner are delivered with exactly-once semantics. * **Partitioner**: The connector supports the `TimeBasedPartitioner` class based on the Kafka class `TimeStamp`. Time-based partitioning options are daily or hourly. * **Supports multiple tasks**: The connector supports running one or more tasks. More tasks may improve performance. * **Supported data formats**: The connector supports Avro, JSON Schema (JSON-SR), Protobuf, JSON (schemaless), and Bytes input data formats. The connector supports Avro and JSON output formats. [Schema Registry](../get-started/schema-registry.md#cloud-sr-config) must be enabled to use a Schema Registry-based format (for example, Avro, JSON Schema, or Protobuf). 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 [SFTP Sink Connector](limits.md#cc-sftp-sink-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). ## Quick Start Use this quick start to get up and running with the Confluent Cloud SFTP Sink connector. The quick start provides the basics of selecting the connector and configuring it to stream events to an SFTP directory. 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). - Access to an SFTP host. - [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). - At least one source Kafka topic must exist in your Confluent Cloud cluster before creating the sink 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 **SFTP Sink** connector card.  #### Step 4: Enter the connector details #### NOTE * Ensure you have all your [prerequisites](#cc-sftp-sink-prereqs) completed. * An asterisk ( \* ) designates a required entry. At the **Add SFTP 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 the SFTP server. Currently, `Password` is the only valid authentication method. - **Use secret manager**: Enable this setting to fetch sensitive configuration values, such as the `Password`, from a secret manager. **Secret manager configuration** - **Secret manager**: Select the secret manager that Confluent Cloud should use to retrieve 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 such as the secret manager. **SFTP Details** - **SFTP Host**: Enter the host address for the SFTP server. For example `192.168.1.231`. - **SFTP Port**: Enter the SFTP host port to use. If no port number is entered, this defaults to `22`. - **Username**: Enter the user name that the connector will use to connect to the host. - **Password**: Enter the password for the user name entered. A password is not required if a PEM file is used for key based authentication to the host. - **PEM File**: If using TLS, upload the PEM file that contains the private key for the SFTP user. - **TLS passphrase**: If the private key is encrypted, enter the passphrase to decrypt the private key. 2. Click **Continue**. ### Configuration #### NOTE Configuration properties that are not shown in the Cloud Console use the default values. See [Configuration Properties](#cc-sftp-sink-config-properties) for all property values and descriptions. - **Input Kafka record value format**: Select the input Kafka record value format (data coming from the Kafka topic). Valid values are AVRO, JSON_SR (JSON Schema), PROTOBUF, JSON (schemaless), or BYTES. 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_SR (JSON Schema), or PROTOBUF). - **Output message format**: Set the output message format for values. Valid entries are AVRO, JSON. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO. Note that the output message format defaults to the value in the Input Message Format field. If either PROTOBUF or JSON_SR is selected as the input message format, you should select one explicitly. - **Time interval**: The time interval that sets how you want your messages grouped in the file system. For example, if you select `Hourly`, messages are grouped into folders for each hour data is streamed to the file system. - **Flush size**: Enter the **Flush size**. This value defaults to 1000. The default value can be raised (and lowered, if running a dedicated cluster). Advanced users may define how the connector flushes records to S3 by clicking the following: ### **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). - **Topic directory**: The top-level directory name to use for stored data. Defaults to `topics` if not used. - **SFTP Working Directory**: The path of the top-level directory where the connector writes to. Defaults to `/home/${sftp.username}`. - **Path format**: Configures the time-based partitioning path created in the file system. The property converts the UNIX timestamp to a date format string. If not used, this property defaults to `'year'=YYYY/'month'=MM/'day'=dd/'hour'=HH` if an Hourly time interval is selected or `'year'=YYYY/'month'=MM/'day'=dd` if a Daily time interval is selected. - **Maximum span of record time (in ms) before scheduled rotation**: Uses `rotate.schedule.interval.ms` to close the file and upload to storage on a regular basis using the current time, rather than the record time. See [Configuration Properties](#cc-sftp-sink-config-properties) for details about the two optional rotation interval properties. - **Compression Type**: The compression type for files. Use `deflate`, `snappy`, or `bzip2` for AVRO output. Use `gzip` for JSON output. - **Maximum span of record time (in ms) before rotation**: The connector’s rotation interval specifies the maximum timespan (in milliseconds) a file can remain open and ready for additional records. In other words, when using `rotate.interval.ms` the timestamp for each file starts with the timestamp of the first record inserted in the file. - **Timestamp field name**: The record field used for the timestamp, which is used with the time-based partitioner. If not used, this defaults to the timestamp when the Kafka record was produced or stored by the Kafka broker. - **Timezone**: A [valid timezone](https://docs.oracle.com/middleware/12212/wcs/tag-ref/MISC/TimeZones.html). Defaults to `UTC` if not used. - **Locale**: The locale to use. Defaults to `en`. **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). - Click **Continue**. ### Sizing Based on the number of topic partitions you select, you will be provided with a recommended number of tasks. One task can handle up to 100 partitions. 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**. #### NOTE This connector does not currently support [Single Message Transformation (SMT)](single-message-transforms.md#cc-single-message-transforms). ### Review and Launch 1. Review the configuration summary and verify the connection details. . 2. Click **Launch**. The status for the connector should go from **Provisioning** to **Running**. #### Step 5: Check for files. Verify that records are being produced on the SFTP host. 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-sftp-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 the required connector properties. ```json { "connector.class": "SftpSink", "topics": "orders", "input.data.format": "JSON", "name": "SftpSinkConnector_0", "kafka.api.key": "****************", "kafka.api.secret": "*********************************", "sftp.host": "192.168.1.231", "sftp.username": "connect-user", "sftp.password:": "****************", "output.data.format": "JSON", "time.interval": "HOURLY", "rotate.schedule.interval.ms": "", "rotate.interval.ms": "", "tasks.max": "1", } ``` Note the following property definitions: * `"connector.class"`: Identifies the connector plugin name. * `"topics"`: Enter the topic name or a comma-separated list of topic names. * `"input.data.format"`: Sets (data coming from the Kafka topic): AVRO, PROTOBUF, JSON_SR (JSON Schema), JSON (schemaless), or BYTES. 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_SR (JSON Schema), or Protobuf). * `"name"`: Sets a name for your new connector. * `"kafka.api.key"` and `"kafka.api.secret"`: These credentials are either the cluster API key and secret *or* the [service account](service-account.md#s3-cloud-service-account) API key and secret. * `"sftp.host"`: Enter the host address for the SFTP server. For example `192.168.1.231`. Note that the port defaults to `22`. To change this, add the property `"sftp.port"`. * `"sftp.username"`: Enter the user name that the connector will use to connect to the host. * `"output.data.format"`: Enter AVRO or JSON (schemaless). 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_SR (JSON Schema), or Protobuf). * `"time.interval"`: Sets how you want your messages grouped in the file system. Options are HOURLY or DAILY. * `"rotate.schedule.interval.ms"` and `"rotate.interval.ms"`: See the [Configuration Properties](#cc-sftp-sink-config-properties) for the property descriptions. * `"tasks.max"`: Enter the maximum number of [tasks](/platform/current/connect/concepts.html#tasks) for the connector to use. More tasks may improve performance. #### NOTE The properties `path.format`, `topics.dir`, and `time.interval` properties can be used to build a directory structure for stored data. For example, you set `time.interval` to HOURLY, `topics.dir` to `json_logs/hourly`, and `path.format` to ``'dt'=YYYY-MM-dd/'hr'=HH`. The result is the directory structure: `filesystem://store-name/json_logs/hourly//dt=2020-02-06/hr=09/`. See the [Configuration Properties](#cc-sftp-sink-config-properties) for property values and definitions. **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-sftp-sink-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 sftp-sink-config.json ``` Example output: ```none Created connector SftpSinkConnector_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 | SftpSinkConnector_0 | RUNNING | sink | | ``` #### Step 5: Check for files. Verify that records are being produced on the SFTP host. 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, JSON or BYTES. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF.
* Type: string * Default: JSON * Importance: high ### 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 the SFTP server.
* Type: string * Default: Password * 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 ### SFTP Details `sftp.host` : Host address of the SFTP server.
* Type: string * Importance: high `sftp.port` : Port number of the SFTP server.
* Type: int * Default: 22 * Importance: medium `sftp.username` : Username for the SFTP connection.
* Type: string * Importance: high `sftp.password` : Password for the SFTP connection (not required if using TLS).
* Type: password * Importance: high `tls.pemfile` : PEM file to be used for authentication via TLS.
* Type: password * Importance: high `tls.passphrase` : Passphrase that will be used to decrypt the private key if the given private key is encrypted.
* Type: password * Importance: high `sftp.working.dir` : Path of the top level directory where the connector should write to (defaults to /home/${sftp.username}).
* Type: string * Default: /home/${sftp.username} * Importance: medium ### Output messages `output.data.format` : Set the output message format for values. Valid entries are AVRO, JSON. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO. Note that the output message format defaults to the value in the Input Message Format field. If either PROTOBUF or JSON_SR is selected as the input message format, you should select one explicitly. If no value for this property is provided, the value specified for the ‘input.data.format’ property is used.
* Type: string * Importance: high ### Organize my data by… `topics.dir` : Top-level directory where ingested data is stored.
* Type: string * Default: topics * Importance: high `path.format` : This configuration is used to set the format of the data directories when partitioning with TimeBasedPartitioner. The format set in this configuration converts the Unix timestamp to a valid directory string. To organize files like this example, filesystem://store-name/json_logs/daily//dt=2020-02-06/hr=09/, use the properties: topics.dir=json_logs/daily, path.format=’dt’=YYYY-MM-dd/’hr’=HH, and time.interval=HOURLY.
* Type: string * Default: ‘year’=YYYY/’month’=MM/’day’=dd/’hour’=HH * Importance: high `time.interval` : Partitioning interval of data, according to the time ingested to storage.
* Type: string * Importance: high `rotate.schedule.interval.ms` : Scheduled rotation uses rotate.schedule.interval.ms to close the file and upload to storage on a regular basis using the current time, rather than the record time. Setting rotate.schedule.interval.ms is nondeterministic and will invalidate exactly-once guarantees.
* Type: int * Default: -1 * Importance: medium `rotate.interval.ms` : The connector’s rotation interval specifies the maximum timespan (in milliseconds) a file can remain open and ready for additional records. In other words, when using rotate.interval.ms, the timestamp for each file starts with the timestamp of the first record inserted in the file. The connector closes and uploads a file to the blob store when the next record’s timestamp does not fit into the file’s rotate.interval time span from the first record’s timestamp. If the connector has no more records to process, the connector may keep the file open until the connector can process another record (which can be a long time). If no value for this property is provided, the value specified for the ‘time.interval’ property is used.
* Type: int * Importance: high `flush.size` : Number of records written to storage before invoking file commits.
* Type: int * Default: 1000 * Valid Values: [1000,…] for non-dedicated clusters and [1,…] for dedicated clusters * Importance: high `timestamp.field` : Sets the field that contains the timestamp used for the TimeBasedPartitioner
* Type: string * Default: “” * Importance: high `timezone` : Sets the timezone used by the TimeBasedPartitioner.
* Type: string * Default: UTC * Importance: high `locale` : Sets the locale to use with TimeBasedPartitioner.
* Type: string * Default: en * Importance: high `compression.codec` : Compression type for files. ‘deflate’, ‘snappy’ and ‘bzip2’ can be used when the output format is AVRO; ‘gzip’ can be used when the output format is JSON.
* Type: string * Importance: high ### Consumer configuration `max.poll.interval.ms` : The maximum delay between subsequent consume requests to Kafka. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 300000 milliseconds (5 minutes).
* Type: long * Default: 300000 (5 minutes) * Valid Values: [60000,…,1800000] for non-dedicated clusters and [60000,…] for dedicated clusters * Importance: low `max.poll.records` : The maximum number of records to consume from Kafka in a single request. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 500 records.
* Type: long * Default: 500 * Valid Values: [1,…,500] for non-dedicated clusters and [1,…] for dedicated clusters * Importance: low ### Number of tasks for this connector `tasks.max` : Maximum number of tasks for the connector.
* Type: int * Valid Values: [1,…] * Importance: high ### 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 `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 ## Frequently asked questions Find answers to frequently asked questions about the SFTP Sink connector for Confluent Cloud. ### How do I configure SSH key-based authentication? The connector supports SSH key-based authentication using PEM-formatted private keys. The Cloud Console currently shows only password authentication, but you can configure key-based authentication using the Confluent CLI or API. * **Use PEM format**: The connector requires private keys in PEM format. If your key is in OpenSSH format, convert it using: ```bash openssl rsa -in ssh_host_rsa_key -outform pem -passin pass:mypassword > ssh_host_rsa_key.pem ``` * **Format the key for configuration**: When adding the PEM key to the connector configuration: * Replace newlines with `\r\n` in the key content * Use the `awk` command to format the key: ```bash RSA_PRIVATE_KEY=$(awk '{printf "%s\\r\\n", $0}' ssh_host_rsa_key.pem) ``` * **Configure passphrase**: You must provide a passphrase using the `tls.passphrase` property, even if your private key is not encrypted. This is a known limitation. If your key is unencrypted, you can provide any non-empty value for `tls.passphrase`. * **Authentication properties**: Use either password-based or key-based authentication, not both. For password authentication, use `sftp.password`. For key-based authentication, use `tls.pemfile` and `tls.passphrase`. * **Verify key permissions**: Ensure the SFTP server accepts the public key corresponding to your private key. ### Why is my data not appearing in SFTP files? If the connector is running but data is not being written to SFTP files, this is typically related to file rotation settings or consumer lag. * **Check file rotation settings**: Files are only created and uploaded when one of the following conditions is met: * `flush.size` - Number of records reaches this threshold. * `rotate.interval.ms` - Time interval based on record timestamps is met. * `rotate.schedule.interval.ms` - Time interval based on wall clock time is met. If none of these conditions are met, the connector keeps the file open and data remains buffered. * **Verify flush size configuration**: The default `flush.size` is 1000 records. If you have low throughput: * On dedicated clusters, lower `flush.size` to a smaller value to trigger more frequent file creation. * On non-dedicated clusters, maintain `flush.size` above 1000 and use `rotate.schedule.interval.ms` to create files on a schedule. * **Review consumer lag**: Consumer poll timeouts or rebalancing can prevent data from being flushed. Check connector logs for warnings such as `Consumer poll timeout` and `Rebalancing occurred` and temporarily reduce `flush.size` or `rotate.interval.ms` to write smaller files more frequently. ### Why do files appear incomplete or empty on the SFTP server? Files may appear incomplete or empty on the SFTP server while the connector is actively writing to them. This is expected behavior during normal operation. * The SFTP protocol does not support atomic writes. Files appear on the SFTP server as soon as the connector opens them for writing, even though they may not contain data yet. * A file is only complete and ready for consumption when: * The connector has closed the file handle. * One of the rotation conditions has been met (`flush.size`, `rotate.interval.ms`, or `rotate.schedule.interval.ms`). * The file is no longer being modified. * **Recommendations**: * Do not process files that are currently being modified. * Monitor file modification timestamps to determine when files are finalized. * If your downstream process reads files too quickly, consider using a delay or file watcher that checks for stable file sizes. * The connector writes to the `sftp.working.dir` location. Monitor this directory for file completion. ### How do I lower `flush.size` below `1000`?\`\` The `flush.size` configuration controls how many records are written to a file before it is committed and uploaded. The minimum value depends on your cluster type. * **For dedicated clusters**: You can set `flush.size` to any value starting from `1`: ```json { "flush.size": "100" } ``` * **For non-dedicated clusters**: The minimum `flush.size` is `1000`. You cannot lower this value on Basic or Standard clusters. This limitation exists because lower `flush.size` values can increase the number of files created and the frequency of commits, which can impact cluster performance. Dedicated clusters have resources allocated specifically for your workload, allowing for more flexible configuration. If you have low message throughput and need more frequent file creation: * Use `rotate.schedule.interval.ms` to create files at regular time intervals regardless of record count. * Use `rotate.interval.ms` to create files based on the time span of record timestamps. * Consider upgrading to a dedicated cluster. ### How do I resolve authentication failures? Authentication failures occur due to incorrect credentials or configuration issues. Follow these troubleshooting steps: * **Validate credentials**: Ensure your SFTP username and password (or PEM key) are correct by testing manually: ```bash sftp -i your_key.pem username@sftp.host ``` * **Check PEM key format**: Ensure your private key is properly formatted in PEM format. The key should start with `-----BEGIN RSA PRIVATE KEY-----` or `-----BEGIN PRIVATE KEY-----`. * **Verify passphrase requirement**: When using `tls.pemfile`, you must provide a value for `tls.passphrase`, even if the key is unencrypted. If your key is unencrypted, provide any non-empty string as the passphrase value. * **Review connector configuration**: Ensure you’re using the correct property names: * Use `tls.pemfile` for the PEM key content. * Use `tls.passphrase` for the passphrase. This is required when using `tls.pemfile`. * Use `sftp.password` only for password-based authentication. * Do not mix password-based and key-based authentication properties. * **Verify SFTP server configuration**: Ensure the SFTP server: * Accepts connections from the connector’s IP address. * Has the correct public key in the `authorized_keys` file for key-based authentication. * Allows the authentication method you’re using. * **Check SFTP server logs**: Review server-side authentication logs to identify specific rejection reasons. ### How do I handle directory permission errors? Directory permission errors occur when the connector cannot access or write to the configured SFTP directory. * **Verify directory permissions**: Ensure the SFTP user has read, write, and execute permissions on `sftp.working.dir`. * **Verify directory exists**: Ensure the `sftp.working.dir` directory exists on the SFTP server before starting the connector. The connector does not create this directory automatically. * **Test directory access**: Manually connect to the SFTP server with the same credentials and verify you can run the following commands: ```bash sftp username@sftp.host cd /path/to/working/dir put test_file.txt ``` * **Check path syntax**: Ensure the directory path is an absolute path starting with `/`. * **Review SFTP server configuration**: Check if SFTP servers have `chroot` restrictions or directory-level access controls that may prevent the connector from accessing certain paths. ## 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)