<a id="cc-sftp-source"></a>

# SFTP Source Connector for Confluent Cloud

The fully managed SFTP Source connector for Confluent Cloud reads files from an SFTP
directory and streams their contents into Apache Kafka® topics. The connector watches
the directory and ingests each new file as it is written. Each file is parsed
based on one of the following property values used with the
`input.file.parser.format` configuration, which are also selectable in the UI.

* `BINARY`
* `CSV`
* `JSON` (the default)
* `SCHEMALESS_JSON`

Once a file has been read, it is placed into a `finished.path` directory or an `error.path` directory.

#### NOTE
* This Quick Start is for the fully managed Confluent Cloud connector. If you are
  installing the connector locally for Confluent Platform, see [SFTP Source 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 Source connector supports the following features:

* **At least once delivery**: The connector guarantees that records are delivered at least once to the Kafka topic (if the file row parsed is valid).
* **Supports one task**: The connector supports running one task per connector instance.
* **Supported output data formats**: The connector supports Avro, JSON Schema (JSON-SR), Protobuf, JSON (schemaless), Bytes, and String output record value 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).
* **Client-side encryption (CSFLE and CSPE) support**: The connector supports CSFLE and CSPE for sensitive data.
  For more information about CSFLE or CSPE setup, see the [connector configuration](#cc-sftp-source-setup-connection).
* **Secret manager integration**: The connector supports secret manager integration. For `Password` based authentication, the connector can retrieve the following configurations from an integrated secret manager at runtime as needed.

  | **Secret manager managed configuration**   | **Type**   |
  |--------------------------------------------|------------|
  | `sftp.host`                                | `STRING`   |
  | `sftp.port`                                | `INT`      |
  | `sftp.username`                            | `STRING`   |
  | `sftp.password`                            | `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 [SFTP Source Connector](limits.md#cc-sftp-source-limits) limitations.
* If you plan to use one or more Single Message Transformations (SMTs), see [SMT Limitations](single-message-transforms.md#cc-single-message-transforms-limitations).

## Quick Start

Use this quick start to get up and running with the Confluent Cloud SFTP Source
connector. The quick start provides the basics of selecting the connector and
configuring it to get data from an SFTP host.

<a id="cc-sftp-source-prereqs"></a>

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 source 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 Source** connector card.

![SFTP Source Connector Card](images/ccloud-sftp-source-icon.png)

<a id="cc-sftp-source-setup-connection"></a>

#### Step 4: Enter the connector details

#### NOTE
* Make sure you have all your [prerequisites](#cc-sftp-source-prereqs) completed.
* An asterisk ( \* ) designates a required entry.
* The steps provide information about how to use the required configuration
  properties. See [Configuration Properties](#cc-sftp-source-config-properties) for other
  configuration property values and descriptions.

At the **Add SFTP Source Connector** screen, complete the following:

### Topic selection

Select the topic you want to send data to 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**: The host address for the SFTP server. For example,
     `192.168.1.231`.
   - **SFTP Port**: The port number of the SFTP server. Defaults to
     `22`.
   - **Username**: The username the connector uses to connect to the
     host.
   - **Password**: The password for the SFTP connection. A password is not
     required if you’re using TLS.
   - **PEM File**: The PEM file to use for authentication via TLS.
   - **TLS passphrase**: Used to decrypt the private key if the
     private key is encrypted.
2. Click **Continue**.

### Configuration

- **Input path**: The SFTP directory to read files from for
  processing. This directory must exist and be accessible by the user running
  Kafka Connect.
- **Finished path**: The SFTP directory to place files that have been
  successfully processed. This directory must exist and be writable by
  the user running Kafka Connect.
- **Error path**: The SFTP directory to place files in which there are
  errors. This directory must exist and be writable by the user running
  Kafka Connect.
- **Input file pattern (regex)**: A regular expression to check input
  file names against. This expression must match the entire filename.
  This is equivalent to `Matcher.matches()`. Using `.*` accepts all
  files in the directory.
- **Schema generation enabled**: Specifies whether schemas should be
  dynamically generated. Select true or false.

**Output messages**

- **Output message format**: The connector supports Avro, JSON Schema,
  Protobuf, JSON, Bytes, and String output Kafka record value 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).

**Input file parser format**

- **Input file parser format**: The parser to
  use to fetch files from the SFTP directory.

**Data encryption**

- Enable **Client-Side Field Level Encryption**
  for data encryption. Specify a **Service Account** to
  access the Schema Registry and associated encryption rules or keys with that schema. For more
  information on CSFLE or CSPE setup,
  see [Manage encryption for connectors](csfle.md#connect-csfle).

### **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).
- **Batch size**: The number of records to return with
  each batch.
- **Timestamp mode**: Determines how the connector sets the timestamp for the ConnectRecord. If set to `FIELD`, the timestamp is read from a field in the value. This field cannot be optional and must be a Timestamp. Specify the field in timestamp.field. If set to `FILE_TIME`, the last modified time of the file is used. If set to `PROCESS_TIME`, the time the record is read is used.
- **Skip lines**: The number of lines to skip at the beginning of the file.
- **Empty poll wait (ms)**: The amount of time to wait if a poll
  returns an empty list of records.
- **Timestamp field**: The field in the value schema that will contain the parsed timestamp for the record. This field cannot be marked as optional and must be a [Timestamp] ([https://kafka.apache.org/0102/javadoc/org/apache/kafka/connect/data/Schema.html](https://kafka.apache.org/0102/javadoc/org/apache/kafka/connect/data/Schema.html))
- **Separator character**: The character that separates each field in the form of an integer. Typically in a CSV this is a ,(44) character. A TSV would use a tab(9) character. If csv.separator.char is defined as a null(0), then the RFC 4180 parser must be utilized by default. This is the equivalent of csv.rfc.4180.parser.enabled = true.
- **Parser timestamp timezone**: The timezone that all of the dates will be parsed with.
- **Quote character**: The character that is used to quote a field. Typically in a CSV this is a `(34)` character. This typically happens when the csv.separator.char character is within the data.
- **Parser timestamp date format**: The date formats that are expected in the file. This is a list of strings that will be used to parse the date fields in order. The most accurate date format should be the first in the list. Take a look at the Java documentation for more info. [https://docs.oracle.com/javase/6/docs/api/java/text/SimpleDateFormat.html](https://docs.oracle.com/javase/6/docs/api/java/text/SimpleDateFormat.html)
- **Escape character**: The character as an integer to use when a special character is encountered. The default escape character is typically a (92)
- **Key schema**: The schema for the key written to Kafka. Set the actual schema, not the schema ID. To generate the schema, use the tool available here: [https://github.com/jcustenborder/kafka-connect-spooldir?tab=readme-ov-file#tip-1](https://github.com/jcustenborder/kafka-connect-spooldir?tab=readme-ov-file#tip-1)
- **Strict quotes**: Sets the strict quotes setting - if true, characters outside the quotes are ignored.
- **Cleanup policy**: Determines how the connector should clean up
  the files that have been processed.
- **Value schema**: The schema for the value written to Kafka. Set the actual schema, not the schema ID. To generate the schema, use the tool available here: [https://github.com/jcustenborder/kafka-connect-spooldir?tab=readme-ov-file#tip-1](https://github.com/jcustenborder/kafka-connect-spooldir?tab=readme-ov-file#tip-1)
- **Ignore leading whitespace**: Sets the ignore leading whitespace setting - if true, white space in front of a quote in a field is ignored.
- **Ignore quotations**: Sets the ignore quotations mode - if true, quotations are ignored.
- **Behavior on error**: Whether the task should halt when it
  encounters an error or continue to next file.
- **Schema generation key fields**: The field(s) to use to build a key schema. This is only used during schema generation.
- **Preserve carriage return?**: Flag to determine if the carriage return at the end of the line should be maintained.
- **File minimum age (ms)**: The amount of time in milliseconds after
  the file was last written to before the file can be
  processed.
- **Schema generation key name**: The name of the generated key schema.
- **Null field Mode**: Indicator to determine how the CSV Reader can determine if a field is null. Valid values are `EMPTY_SEPARATORS`, `EMPTY_QUOTES`, `BOTH`, `NEITHER`. For more information, see [http://opencsv.sourceforge.net/apidocs/com/opencsv/enums/CSVReaderNullFieldIndicator.html](http://opencsv.sourceforge.net/apidocs/com/opencsv/enums/CSVReaderNullFieldIndicator.html). Note that empty quotes or empty delimiter for non-string fields are always treated as null.
- **Schema generation value name**: The name of the generated value schema.
- **Treat first row as header.**: Flag to indicate if the fist row of data contains the header of the file. If true the position of the columns will be determined by the first row to the CSV. The column position will be inferred from the position of the schema supplied in value.schema. If set to true the number of columns must be greater than or equal to the number of fields in the schema.
- **File character set.**: Character set to read wth file with.
- **Pre-validate the CSV file before processing file records.**: Flag to enable validating the integrity of all records in the CSV file before processing any of its records.  For example, if any of the records have a linefeed within an unquoted field, which would incorrectly break the record at that point, then the entire fil will be considered erroneous and no records from that file will be processed. The failed file would be moved to the configured error path. Important: If the number of records in a file is larger than the configured batch size, then portions of the file may be retrieved from the sftp server by the connector more than once.
- **Null field indicator**: Indicator to determine how the CSV Reader can determine if a field is null. Valid values are `EMPTY_SEPARATORS`, `EMPTY_QUOTES`, `BOTH`, `NEITHER`. For more information, see [http://opencsv.sourceforge.net/apidocs/com/opencsv/enums/CSVReaderNullFieldIndicator.html](http://opencsv.sourceforge.net/apidocs/com/opencsv/enums/CSVReaderNullFieldIndicator.html).

**Additional Configs**

- **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`.
- **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 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.
- **Key Converter Schema ID Serializer**: The class name of the schema ID serializer for keys. This is used to serialize schema IDs in the message headers.
- **Value Converter Connect Meta Data**: Enables the Connect converter to add its metadata to the output schema. Applies to Avro converters.
- **Value Converter Value Subject Name Strategy**: Determines how to construct the subject name under which the value schema is registered with Schema Registry.
- **Key Converter Key Subject Name Strategy**: Determines how to construct the subject name for key schema registration.
- **Value Converter Schema ID Serializer**: The class name of the schema ID serializer for values. This is used to serialize schema IDs in the message headers.

**Auto-restart policy**

- **Enable Connector Auto-restart**: Enables the auto-restart behavior of the connector and its
  task in the event of user-actionable errors. Defaults to `true`, enabling the connector to
  automatically restart in case of user-actionable errors. Set this property to `false` to
  disable auto-restart for failed connectors. If disabled, you must manually restart the connector.

**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.

1. To change the number of tasks, use the Range Slider to select the
   desired number of tasks.
2. Click **Continue**.

### Review and Launch

1. Verify the connection details by previewing the running configuration.
2. Once you’ve validated that the properties are configured to your
   satisfaction, click **Launch**.

   The status for the connector should go from **Provisioning** to
   **Running**.

#### Step 5: Check for records

Verify that records are being produced in the Kafka topic.

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-source-prereqs) completed.

#### Step 1: List the available connectors

Enter the following command to list available connectors:

```none
confluent connect plugin list
```

#### Step 2: List the connector configuration properties

Enter the following command to show the connector configuration properties:

```none
confluent connect plugin describe <connector-plugin-name>
```

The command output shows the required and optional configuration properties.

<a id="cc-sftp-source-cli-configuration-file"></a>

#### 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": "SftpSource",
  "name": "SftpSourceConnector_0",
  "kafka.api.key": "****************",
  "kafka.api.secret": "*********************************",
  "kafka.topic": "orders",
  "output.data.format": "JSON",
  "input.file.parser.format": "CSV",
  "schema.generation.enable": "true",
  "sftp.host": "192.168.1.231",
  "sftp.username": "connect-user",
  "sftp.password:": "****************",
  "input.path": "/path/to/data",
  "finished.path": "/path/to/finished",
  "error.path": "/path/to/error",
  "input.file.pattern": "csv-sftp-source.csv",
  "tasks.max": "1",
}
```

Note the following property definitions:

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

* `"kafka.auth.mode"`: Identifies the connector authentication mode you want to use. There are two options: `SERVICE_ACCOUNT` or `KAFKA_API_KEY` (the default). To use an API key and secret, specify the configuration properties `kafka.api.key` and `kafka.api.secret`, as shown in the example configuration (above).  To use a [service account](service-account.md#s3-cloud-service-account), specify the **Resource ID** in the property `kafka.service.account.id=<service-account-resource-ID>`. To list the available service account resource IDs, use the following command:
  ```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
  ```

* `"kafka.topic"`: Enter the topic name or a comma-separated list of topic names.
* `"output.data.format"`: The connector supports Avro, JSON Schema (JSON_SR), Protobuf, JSON (schemaless), Bytes, and String output Kafka record value 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).

  #### NOTE
  Note the following relationship between `output.data.format` and the `input.file.parser.format` property.
  * If you use `BINARY` for `input.file.parser.format`, you must use `BYTES` for `output.data.format`.
  * If you use `SCHEMALESS_JSON` for `input.file.parser.format`, you must use `STRING` for `output.data.format`.
  * If you leave this to `JSON` (the default) or use `CSV` for `input.file.parser.format`, you can use any format for `output.data.format`.
* `"input.file.parser.format"`: The parser format used to parse fetched files from the SFTP directory. Defaults to `JSON`. Options are `BINARY`, `CSV`, `JSON`, `SCHEMALESS_JSON`.

  #### IMPORTANT
  * If you use `JSON` (the default) or `CSV` as the `input.file.parser.format`, then you must add the property `schema.generation.enable` and set it to `true`. If you set this property to `false`, you must provide a `key.schema` and a `value.schema`.
  * `key.schema` and `value.schema` properties require the actual schema, not the schema ID. To generate the schema, use the tool
    available [here](https://github.com/jcustenborder/kafka-connect-spooldir?tab=readme-ov-file#tip-1).
    <details id="target-details">
    <summary id="target-summary" style="display: list-item; cursor:pointer; color:#337ab7;">Schema example:
    </summary>
    ```json
    key.schema={\"name\" : \"com.example.users.UserKey\",\"type\" : \"STRUCT\",\"isOptional\" : false,
      \"fieldSchemas\" : {\"id\" : {\"type\" : \"INT64\",\"isOptional\" : false}}}
    value.schema={\"name\" : \"com.example.users.User\",\"type\" : \"STRUCT\",\"isOptional\" : false,
      \"fieldSchemas\" : {\"id\" : {\"type\" : \"INT64\",\"isOptional\" : false},
      \"first_name\" : {\"type\" : \"STRING\",\"isOptional\" : true},\"last_name\" : {\"type\" : \"STRING\",
      \"isOptional\" : true},\"email\" : {\"type\" : \"STRING\",\"isOptional\" : true},
      \"gender\" : {\"type\" : \"STRING\",\"isOptional\" : true},\"ip_address\" : {\"type\" : \"STRING\",
      \"isOptional\" : true},\"last_login\" : {\"type\" : \"STRING\",\"isOptional\" : true},
      \"account_balance\" : {\"name\" : \"org.apache.kafka.connect.data.Decimal\",\"type\" : \"BYTES\",
      \"version\" : 1,\"parameters\" : {\"scale\" : \"2\"},\"isOptional\" : true},
      \"country\" : {\"type\" : \"STRING\",\"isOptional\" : true},\"favorite_color\" : {\"type\" : \"STRING\",
      \"isOptional\" : true}}}
    ```

    </details>
* `"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. The `"sftp.password"` property is not required if a PEM file is used for key based authentication to the host.
* `"input.path"`: Add the SFTP directory from which the connector reads files that will be processed. This directory must exist and be writable by the connector.
* `"finished.path"`: Add the SFTP directory where the connector places files that are successfully processed. This directory must exist and be writable by the connector.
* `"error.path"`: Add the SFTP directory where the connector places files in which there are errors. This directory must exist and be writable by the connector.
* `"input.file.pattern"`: Add a regular expression to check input file names against. This expression must match the entire filename. The equivalent of `Matcher.matches()`. Using `.*` accepts all files in the directory.
* `"tasks.max"`: The connector supports running one [tasks](/platform/current/connect/concepts.html#tasks) per connector.

#### NOTE
To enable CSFLE or CSPE for data encryption, specify the following properties:

* `csfle.enabled`: Flag to indicate whether the connector honors CSFLE or CSPE rules.
* `sr.service.account.id`: A Service Account to access the Schema Registry and associated encryption rules or keys with that schema.

For more information on CSFLE or CSPE setup, see [Manage encryption for connectors](csfle.md#connect-csfle).

**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-source-config-properties) for all property values and
descriptions.

#### Step 4: 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 <file-name>.json
```

For example:

```none
confluent connect cluster create --config-file sftp-source-config.json
```

Example output:

```none
Created connector SftpSourceConnector_0 lcc-do6vzd
```

#### 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   | Trace
+------------+-----------------------------+---------+--------+-------+
lcc-do6vzd   | SftpSourceConnector_0       | RUNNING | source |       |
```

#### Step 6: Check the Kafka topic

Verify that records are being produced at the Kafka topic.

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.

<a id="cc-sftp-source-config-properties"></a>

## Configuration Properties

Use the following configuration properties with the fully managed connector. For
self-managed connector property definitions and other details, see the connector
docs in [Self-managed connectors for Confluent Platform](/platform/current/connect/kafka_connectors.html).

### How should we connect to your data?

`name`
: Sets a name for your connector.
  <br/>
  * 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.
  <br/>
  * 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.
  <br/>
  * 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.
  <br/>
  * Type: string
  * Importance: high

`kafka.api.secret`
: Secret associated with Kafka API key. Required when kafka.auth.mode==KAFKA_API_KEY.
  <br/>
  * Type: password
  * Importance: high

### Which topic do you want to send data to?

`kafka.topic`
: Identifies the topic name to write the data to.
  <br/>
  * Type: string
  * Importance: high

### Schema Config

`schema.context.name`
: Add a schema context name. A schema context represents an independent scope in Schema Registry. It is a separate sub-schema tied to topics in different Kafka clusters that share the same Schema Registry instance. If not used, the connector uses the default schema configured for Schema Registry in your Confluent Cloud environment.
  <br/>
  * Type: string
  * Default: default
  * Importance: medium

### Output messages

`output.data.format`
: Sets the output message format. Valid entries are AVRO, JSON_SR, PROTOBUF, JSON, STRING 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
  <br/>
  * Type: string
  * Importance: high

### Input file parser format

`input.file.parser.format`
: Parser that should be used to parse fetched files from sftp directory
  <br/>
  * Type: string
  * Default: JSON
  * Importance: high

### Authentication method

`authentication.method`
: Select how you want to authenticate with the SFTP server.
  <br/>
  * Type: string
  * Default: Password
  * Importance: high

`secret.manager.enabled`
: Fetch sensitive configuration values from a secret manager.
  <br/>
  * Type: boolean
  * Default: false
  * Importance: high

### Secret manager configuration

`secret.manager`
: Select the secret manager to use for retrieving sensitive data.
  <br/>
  * Type: string
  * Importance: high

`secret.manager.managed.configs`
: Select the configurations to fetch their values from the secret manager.
  <br/>
  * Type: list
  * Importance: high

`secret.manager.provider.integration.id`
: Select an existing provider integration that has access to your secret manager.
  <br/>
  * Type: string
  * Importance: high

### SFTP Details

`sftp.host`
: Host address of the SFTP server.
  <br/>
  * Type: string
  * Importance: high

`sftp.port`
: Port number of the SFTP server.
  <br/>
  * Type: int
  * Default: 22
  * Importance: medium

`sftp.username`
: Username for the SFTP connection.
  <br/>
  * Type: string
  * Importance: high

`sftp.password`
: Password for the SFTP connection (not required if using TLS).
  <br/>
  * Type: password
  * Importance: high

`tls.pemfile`
: PEM file to be used for authentication via TLS.
  <br/>
  * Type: password
  * Importance: high

`tls.passphrase`
: Passphrase that will be used to decrypt the private key if the given private key is encrypted.
  <br/>
  * Type: password
  * Importance: high

### SFTP directory

`input.path`
: The SFTP directory to read files that will be processed.This directory must exist and be writable by the user running Kafka Connect.
  <br/>
  * Type: string
  * Importance: high

`finished.path`
: The SFTP directory to place files that have been successfully processed. This directory must exist and be writable by the user running Kafka Connect.
  <br/>
  * Type: string
  * Importance: high

`error.path`
: The SFTP directory to place files in which there are error(s). This directory must exist and be writable by the user running Kafka Connect.
  <br/>
  * Type: string
  * Importance: high

### File System

`cleanup.policy`
: Determines how the connector should cleanup the files that have been successfully processed. NONE leaves the files in place which could cause them to be reprocessed if the connector is restarted. DELETE removes the file from the filesystem. MOVE will move the file to a finished directory.
  <br/>
  * Type: string
  * Default: MOVE
  * Importance: medium

`input.file.pattern`
: Regular expression to check input file names against. This expression must match the entire filename. The equivalent of Matcher.matches().
  <br/>
  * Type: string
  * Importance: high

`behavior.on.error`
: Should the task halt when it encounters an error or continue to the next file.
  <br/>
  * Type: string
  * Default: FAIL
  * Importance: high

`file.minimum.age.ms`
: The amount of time in milliseconds after the file was last written to before the file can be processed. For default 0, connector processes all files irrespective of age
  <br/>
  * Type: long
  * Default: 0
  * Importance: low

### Connection details

`batch.size`
: The number of records that should be returned with each batch.
  <br/>
  * Type: int
  * Default: 1000
  * Importance: low

`empty.poll.wait.ms`
: The amount of time to wait if a poll returns an empty list of records.
  <br/>
  * Type: long
  * Default: 250
  * Importance: low

### Schema

`key.schema`
: The schema for the key written to Kafka. Set the actual schema, not the schema ID. To generate the schema, use the tool available here: [https://github.com/jcustenborder/kafka-connect-spooldir?tab=readme-ov-file#tip-1](https://github.com/jcustenborder/kafka-connect-spooldir?tab=readme-ov-file#tip-1)
  <br/>
  * Type: string
  * Importance: high

`value.schema`
: The schema for the value written to Kafka. Set the actual schema, not the schema ID. To generate the schema, use the tool available here: [https://github.com/jcustenborder/kafka-connect-spooldir?tab=readme-ov-file#tip-1](https://github.com/jcustenborder/kafka-connect-spooldir?tab=readme-ov-file#tip-1)
  <br/>
  * Type: string
  * Importance: high

### Schema Generation

`schema.generation.enabled`
: Flag to determine if schemas should be dynamically generated. If set  to true, key.schema and value.schema can be omitted, but schema.generation.key.name and schema.generation.value.name must be set.
  <br/>
  * Type: boolean
  * Importance: medium

`schema.generation.key.fields`
: The field(s) to use to build a key schema. This is only used during schema generation.
  <br/>
  * Type: list
  * Importance: medium

`schema.generation.key.name`
: The name of the generated key schema.
  <br/>
  * Type: string
  * Importance: medium

`schema.generation.value.name`
: The name of the generated value schema.
  <br/>
  * Type: string
  * Importance: medium

### Timestamps

`timestamp.mode`
: Determines how the connector will set the timestamp for the ConnectRecord. If set to FIELD then the timestamp will be read from a field in the value. This field cannot be optional and must be a Timestamp. Specify the field in timestamp.field. If set to FILE_TIME then the last modified time of the file will be used. If set to PROCESS_TIME the time the record is read will be used.
  <br/>
  * Type: string
  * Importance: medium

`timestamp.field`
: The field in the value schema that will contain the parsed timestamp for the record. This field cannot be marked as optional and must be a [Timestamp] ([https://kafka.apache.org/0102/javadoc/org/apache/kafka/connect/data/Schema.html](https://kafka.apache.org/0102/javadoc/org/apache/kafka/connect/data/Schema.html))
  <br/>
  * Type: string
  * Importance: medium

`parser.timestamp.timezone`
: The timezone that all of the dates will be parsed with.
  <br/>
  * Type: string
  * Importance: low

`parser.timestamp.date.formats`
: The date formats that are expected in the file. This is a list of strings that will be used to parse the date fields in order. The most accurate date format should be the first in the list. Take a look at the Java documentation for more info. [https://docs.oracle.com/javase/6/docs/api/java/text/SimpleDateFormat.html](https://docs.oracle.com/javase/6/docs/api/java/text/SimpleDateFormat.html)
  <br/>
  * Type: list
  * Importance: low

### CSV Parsing

`csv.skip.lines`
: Number of lines to skip in the beginning of the file.
  <br/>
  * Type: int
  * Default: 0
  * Importance: low

`csv.separator.char`
: The character that separates each field in the form of an integer. Typically in a CSV this is a ,(44) character. A TSV would use a tab(9) character. If csv.separator.char is defined as a null(0), then the RFC 4180 parser must be utilized by default. This is the equivalent of csv.rfc.4180.parser.enabled = true.
  <br/>
  * Type: int
  * Default: 44
  * Importance: low

`csv.quote.char`
: The character that is used to quote a field. Typically in a CSV this is a “(34) character. This typically happens when the csv.separator.char character is within the data.
  <br/>
  * Type: int
  * Default: 34
  * Importance: low

`csv.escape.char`
: The character as an integer to use when a special character is encountered. The default escape character is typically a (92)
  <br/>
  * Type: int
  * Default: 92
  * Importance: low

`csv.strict.quotes`
: Sets the strict quotes setting - if true, characters outside the quotes are ignored.
  <br/>
  * Type: string
  * Default: false
  * Importance: low

`csv.ignore.leading.whitespace`
: Sets the ignore leading whitespace setting - if true, white space in front of a quote in a field is ignored.
  <br/>
  * Type: string
  * Importance: low

`csv.ignore.quotations`
: Sets the ignore quotations mode - if true, quotations are ignored.
  <br/>
  * Type: string
  * Default: false
  * Importance: low

`csv.keep.carriage.return`
: Flag to determine if the carriage return at the end of the line should be maintained.
  <br/>
  * Type: string
  * Default: false
  * Importance: low

`csv.null.field.mode`
: Indicator to determine how the CSV Reader can determine if a field is null. Valid values are EMPTY_SEPARATORS, EMPTY_QUOTES, BOTH, NEITHER. For more information see [http://opencsv.sourceforge.net/apidocs/com/opencsv/enums/CSVReaderNullFieldIndicator.html](http://opencsv.sourceforge.net/apidocs/com/opencsv/enums/CSVReaderNullFieldIndicator.html). NOTE: Empty quotes or empty delimiter for non-string fields are always treated as null.
  <br/>
  * Type: string
  * Default: BOTH
  * Importance: low

`csv.first.row.as.header`
: Flag to indicate if the fist row of data contains the header of the file. If true the position of the columns will be determined by the first row to the CSV. The column position will be inferred from the position of the schema supplied in value.schema. If set to true the number of columns must be greater than or equal to the number of fields in the schema.
  <br/>
  * Type: string
  * Importance: medium

`csv.file.charset`
: Character set to read wth file with.
  <br/>
  * Type: string
  * Default: UTF-8
  * Importance: low

`ui.csv.pre.validate.file.enabled`
: Flag to enable validating the integrity of all records in the CSV file before processing any of its records.  For example, if any of the records have a linefeed within an unquoted field, which would incorrectly break the record at that point, then the entire fil will  be considered erroneous and no records from that file will be processed.  The failed file would be moved to the configured error path.  Important: If the number of records in a file is larger than the configured batch size, then portions of the file may be retrieved from the sftp server by the connector more than once.
  <br/>
  * Type: string
  * Default: NO
  * Valid Values: NO, YES
  * Importance: low

`csv.null.field.indicator`
: DEPRECATED: The config has been deprecated in favor of Null Field Mode.
  <br/>
  * Type: string
  * Default: NEITHER
  * Importance: low

### Number of tasks for this connector

`tasks.max`
: Maximum number of tasks for the connector.
  <br/>
  * Type: int
  * Valid Values: [1,…,1]
  * Importance: high

### Additional Configs

`header.converter`
: The converter class for the headers. This is used to serialize and deserialize the headers of the messages.
  <br/>
  * Type: string
  * Importance: low

`producer.override.compression.type`
: The compression type for all data generated by the producer. Valid values are none, gzip, snappy, lz4, and zstd.
  <br/>
  * Type: string
  * Importance: low

`producer.override.linger.ms`
: The producer groups together any records that arrive in between request transmissions into a single batched request. More details can be found in the documentation: [https://docs.confluent.io/platform/current/installation/configuration/producer-configs.html#linger-ms](https://docs.confluent.io/platform/current/installation/configuration/producer-configs.html#linger-ms).
  <br/>
  * Type: long
  * Valid Values: [100,…,1000]
  * 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.
  <br/>
  * Type: boolean
  * Importance: low

`value.converter.auto.register.schemas`
: Specify if the Serializer should attempt to register the Schema.
  <br/>
  * 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.
  <br/>
  * Type: boolean
  * Importance: low

`value.converter.enhanced.avro.schema.support`
: Enable enhanced schema support to preserve package information and Enums. Applicable for Avro Converters.
  <br/>
  * Type: boolean
  * Importance: low

`value.converter.enhanced.protobuf.schema.support`
: Enable enhanced schema support to preserve package information. Applicable for Protobuf Converters.
  <br/>
  * Type: boolean
  * Importance: low

`value.converter.flatten.unions`
: Whether to flatten unions (oneofs). Applicable for Protobuf Converters.
  <br/>
  * Type: boolean
  * Importance: low

`value.converter.generate.index.for.unions`
: Whether to generate an index suffix for unions. Applicable for Protobuf Converters.
  <br/>
  * Type: boolean
  * Importance: low

`value.converter.generate.struct.for.nulls`
: Whether to generate a struct variable for null values. Applicable for Protobuf Converters.
  <br/>
  * Type: boolean
  * Importance: low

`value.converter.int.for.enums`
: Whether to represent enums as integers. Applicable for Protobuf Converters.
  <br/>
  * Type: boolean
  * Importance: low

`value.converter.latest.compatibility.strict`
: Verify latest subject version is backward compatible when use.latest.version is true.
  <br/>
  * Type: boolean
  * Importance: low

`value.converter.object.additional.properties`
: Whether to allow additional properties for object schemas. Applicable for JSON_SR Converters.
  <br/>
  * Type: boolean
  * Importance: low

`value.converter.optional.for.nullables`
: Whether nullable fields should be specified with an optional label. Applicable for Protobuf Converters.
  <br/>
  * Type: boolean
  * Importance: low

`value.converter.optional.for.proto2`
: Whether proto2 optionals are supported. Applicable for Protobuf Converters.
  <br/>
  * Type: boolean
  * Importance: low

`value.converter.use.latest.version`
: Use latest version of schema in subject for serialization when auto.register.schemas is false.
  <br/>
  * Type: boolean
  * Importance: low

`value.converter.use.optional.for.nonrequired`
: Whether to set non-required properties to be optional. Applicable for JSON_SR Converters.
  <br/>
  * Type: boolean
  * Importance: low

`value.converter.wrapper.for.nullables`
: Whether nullable fields should use primitive wrapper messages. Applicable for Protobuf Converters.
  <br/>
  * 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.
  <br/>
  * 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.
  <br/>
  * Type: string
  * Default: none
  * Importance: low

`key.converter.key.schema.id.serializer`
: The class name of the schema ID serializer for keys. This is used to serialize schema IDs in the message headers.
  <br/>
  * Type: string
  * Default: io.confluent.kafka.serializers.schema.id.PrefixSchemaIdSerializer
  * Importance: low

`key.converter.key.subject.name.strategy`
: How to construct the subject name for key schema registration.
  <br/>
  * 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:
  <br/>
  BASE64 to serialize DECIMAL logical types as base64 encoded binary data and
  <br/>
  NUMERIC to serialize Connect DECIMAL logical type values in JSON/JSON_SR as a number representing the decimal value.
  <br/>
  * Type: string
  * Default: BASE64
  * Importance: low

`value.converter.flatten.singleton.unions`
: Whether to flatten singleton unions. Applicable for Avro and JSON_SR Converters.
  <br/>
  * 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.
  <br/>
  * Type: string
  * Default: DefaultReferenceSubjectNameStrategy
  * Importance: low

`value.converter.value.schema.id.serializer`
: The class name of the schema ID serializer for values. This is used to serialize schema IDs in the message headers.
  <br/>
  * Type: string
  * Default: io.confluent.kafka.serializers.schema.id.PrefixSchemaIdSerializer
  * Importance: low

`value.converter.value.subject.name.strategy`
: Determines how to construct the subject name under which the value schema is registered with Schema Registry.
  <br/>
  * Type: string
  * Default: TopicNameStrategy
  * Importance: low

### Auto-restart policy

`auto.restart.on.user.error`
: Enable connector to automatically restart on user-actionable errors.
  <br/>
  * Type: boolean
  * Default: true
  * Importance: medium

## Frequently asked questions

Find answers to frequently asked questions about the SFTP Source connector for Confluent Cloud.

### Why are files with parsing errors not moved to `error.path`?

If files containing parsing errors are being deleted from `input.path` instead of being moved to `error.path`,
verify the following:

* **Check CSV format validity**: Ensure your CSV files are properly formatted. Common issues include:
  * Unterminated quoted fields with missing closing quotes
  * Mismatched number of columns across rows
  * Invalid characters or encoding issues
* **Verify error path configuration**: Confirm that the `error.path` directory exists on your SFTP server
  and the connector has write permissions to this directory.
* **Review error setting**: Set the `behavior.on.error` property to `IGNORE` or `FAIL` depending on your requirements.
  When set to `IGNORE`, the connector skips records that fail to parse and moves the file to `error.path`.
* **Check file-level and record-level errors**: The connector moves files to `error.path` when entire files cannot
  be processed. Individual record parsing failures within a valid file structure may behave
  differently depending on your configuration.

### How do I configure SSH key-based authentication?

The connector supports SSH key-based authentication using PEM-formatted private keys.
Follow these steps to configure authentication correctly:

* **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.
* **Verify key permissions**: Ensure the SFTP server accepts the public key corresponding to your private key.

Note that the connector does not support `known_hosts` configuration. Host key verification is handled internally by the connector.

### What are the requirements for `schema.generation.enable`?

Schema generation configuration is required when using `CSV` or `JSON` as `input.file.parser.format`. This is because these formats require a schema to parse the data correctly.
You can provide the required schema information using the following options:

* Option 1: Set `schema.generation.enable` to `true` to allow the connector to automatically
  generate schemas from your input files.
  ```json
  {
    "input.file.parser.format": "CSV",
    "schema.generation.enable": "true"
  }
  ```
* Option 2: If you set `schema.generation.enable` to `false`, provide both
  `key.schema` and `value.schema` properties with the complete schema definition along with the schema IDs.
* Option 3: Use the [schema generation tool](https://github.com/jcustenborder/kafka-connect-spooldir?tab=readme-ov-file#tip-1)
  to create the required schema structure.

When using CSV format with schema generation enabled:

* Set `csv.first.row.as.header` to `true` to use the first row as column names.
* Verify that the `csv.separator.char` matches your file’s delimiter.

### Why is the connector consuming files but not producing to Kafka topics?

If the connector successfully reads files from `input.path` but no data appears in Kafka topics, check the following:

* **Verify format compatibility**: Ensure the `input.file.parser.format` and `output.data.format` are compatible:
  * `BINARY` input requires `BYTES` output.
  * `SCHEMALESS_JSON` input requires `STRING` output.
  * `JSON` or `CSV` input can use any output format.
* **Check schema configuration**: For `JSON` or `CSV` input formats, check that schema generation is properly configured:
  * Verify `schema.generation.enable` is set to `true`.
  * Confirm valid `key.schema` and `value.schema` are provided.
* **Review file parsing errors**: Check connector logs for parsing errors that may prevent data from being produced.
* **Confirm Schema Registry configuration**: If using schema-based formats, ensure:
  * Confluent Cloud Schema Registry is enabled for your environment.
  * The connector has proper credentials to access Schema Registry.
* **Validate file patterns**: Ensure `input.file.pattern` matches your file names. Use `.*` to accept all files in the directory.

### Why does the same filename get processed only once?

The connector reads and processes each unique filename only once from a specific SFTP directory.
This is the expected behavior to prevent duplicate processing.

If a new file with the same name is placed in `input.path` after the original file was processed, the connector will not process it again.

To reprocess files with the same name, consider the following options:

* **Trigger an automatic reprocess**: The connector can reprocess a file with the same name if:
  * The connector restarts and the file is still residing in the `input.path` directory.
  * The cleanup policy is not set to `NONE`.
* **Use unique filenames**: Include timestamps or sequence numbers in your file naming convention. For example, `data_20260304_001.csv`.
* **Archive processed files**: Move processed files to a different location and ensure new files have distinct names.
* **Use a new connector instance**: Deploy a different connector instance with a new name. Since metadata is often tracked per-connector, a new instance will see the file as new.

### How do I resolve authentication failures?

Authentication failures occur due to key format or configuration issues. Follow these troubleshooting steps:

* **Validate 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-----`.
* **Check key conversion**: If you receive a `JSchException: invalid privatekey` error, your key may not be in
  the correct format. Convert it using:
  ```bash
  openssl rsa -in your_key -outform pem > your_key.pem
  ```
* **Verify newline formatting**: When adding the key to JSON configuration, ensure newlines are properly escaped as `\r\n`:
  ```bash
  awk '{printf "%s\\r\\n", $0}' your_key.pem
  ```
* **Test credentials manually**: Verify that your username and key work by testing SFTP access manually:
  ```bash
  sftp -i your_key.pem username@sftp.host
  ```
* **Review connector configuration**: Ensure you’re using the correct property names:
  * Use `tls.pemfile` for the PEM key content, do not use `tls.private.key` in Confluent Cloud.
  * Use `tls.passphrase` if your key is encrypted.
  * Use `sftp.password` only for password-based authentication.
* **Check SFTP server logs**: Review server-side authentication logs to identify specific rejection reasons,
  such as key format issues or permission problems.

### How do I handle directory permission errors?

Directory permission errors occur when the connector cannot access or write to the configured SFTP directories.
To resolve these issues:

* **Verify directory permissions**: Ensure the SFTP user has read, write, and execute permissions for:
  * `input.path` - read and execute permissions required.
  * `finished.path` - read, write, and execute permissions required.
  * `error.path` - read, write, and execute permissions required.
* **Create directories in advance**: Create the `input.path`, `finished.path`, `error.path` directories manually before starting the connector.
  The connector does not create these directories automatically.
* **Test directory access**: Manually connect to the SFTP server with the same credentials and verify you can run
  the following commands:
  ```bash
  cd /path/to/data
  touch test_file.txt
  mv test_file.txt /path/to/finished/
  ```
* **Check path syntax**: Ensure directory paths are absolute paths starting with `/` and do not contain trailing slashes.
* **Review SFTP server configuration**: Check for SFTP servers having `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.

[![image](images/topology.png)](https://docs.confluent.io/platform/current/tutorials/examples/cloud-etl/docs/index.html)