Amazon S3 Source Connector for Confluent Cloud

The fully-managed Amazon S3 Source connector for Confluent Cloud reads data from files in an S3 bucket. The file names don’t have to be in a specific format. The file format has to be supported (for example, Avro, Bytes, CSV, JSON, or Parquet) for the connector to read from.

Note

Features

The Amazon S3 Source connector provides the following features:

  • At least once delivery: The connector guarantees that records are delivered at least once.

  • Supports multiple tasks: The connector supports running one or more tasks.

  • Client-side field level encryption (CSFLE) support: The connector supports CSFLE for sensitive data. For more information about CSFLE setup, see the connector configuration.

  • Offset management capabilities: The connector supports offset management. For more information, see Manage custom offsets.

  • Supported input data formats: The connector supports Avro, Bytes, CSV, JSON, and Parquet input formats. The supported compression types for Parquet formats are snappy, gzip, and none. Note that the connector can support Parquet input files up to 2GB in size.

  • Provider integration support: The connector supports IAM role-based authorization using Confluent Provider Integration. For more information about provider integration setup, see the IAM roles authentication.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.

Refer to Confluent Cloud connector limitations for additional information.

IAM Policy for S3

The AWS user account accessing the S3 bucket must have the following permissions:

  • ListBucket

  • GetObject

  • ListAllMyBuckets

Note

  • This is the IAM policy for the user account and not a bucket policy.

  • The connector uses GetBucketAcl to verify bucket existence, but this permission is optional. To avoid AccessDenied errors in your CloudTrail logs, you can add the equivalent permission to the connector.

For more information, see Create and attach a policy to an IAM user.

Manage custom offsets

You can manage the offsets for this connector. Offsets provide information on the point in the system from which the connector is accessing data. For more information, see Manage Offsets for Fully-Managed Connectors in Confluent Cloud.

To manage offsets:

To get the current offset, make a GET request that specifies the environment, Kafka cluster, and connector name.

GET /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets
Host: https://api.confluent.cloud

Response:

Successful calls return HTTP 200 with a JSON payload that describes the offset.

{
    "id": "lcc-example123",
    "name": "{connector_name}",
    "offsets": [
        {
          "partition": {
            "taskId": "lcc-example123-0-in_progress"
          },
          "offset": {
            "earliestIncomplete": "2023-08-03T10:24:25Z",
            "completedFiles": "[{\"filePath\":\"topics/abc_0/partition=0/abc_0+0+00000.json\",\"creationTime\":\"2023-08-03T10:24:25Z\"},{\"filePath\":\"topics/abc_1/partition=0/abc_1+0+00000.json\",\"creationTime\":\"2023-08-03T10:34:56Z\"},{\"filePath\":\"topics/abc_3/partition=0/abc_3+0+00000.json\",\"creationTime\":\"2023-08-03T10:48:28Z\"}]",
            "recordNum": "98"
          }
        }
        {
          "partition": {
            "taskId": "lcc-example123-1"
          },
          "offset": {
            "earliestIncomplete": "2023-08-03T10:24:25Z",
            "completedFiles": "[{\"filePath\":\"topics/babc_4/partition=0/babc_4+0+00000.json\",\"creationTime\":\"2023-08-03T10:33:04Z\"},{\"filePath\":\"topics/abc_2/partition=0/abc_2+0+00000.json\",\"creationTime\":\"2023-08-03T10:46:06Z\"},{\"filePath\":\"topics/weird/partition=0/weird+0+00000 copy.json\",\"creationTime\":\"2023-08-03T10:51:09Z\"}]",
            "recordNum": "99"
          }
        }
        {
          "partition": {
            "taskId": "lcc-example123-0"
          },
          "offset": {
            "earliestIncomplete": "2023-08-03T10:24:25Z",
            "completedFiles": "[{\"filePath\":\"topics/abc_0/partition=0/abc_0+0+00000.json\",\"creationTime\":\"2023-08-03T10:24:25Z\"},{\"filePath\":\"topics/abc_1/partition=0/abc_1+0+00000.json\",\"creationTime\":\"2023-08-03T10:34:56Z\"},{\"filePath\":\"topics/abc_3/partition=0/abc_3+0+00000.json\",\"creationTime\":\"2023-08-03T10:48:28Z\"},{\"filePath\":\"topics/abc_5/partition=0/abc_5+0+00000.json\",\"creationTime\":\"2023-08-03T10:59:06Z\"}]",
            "recordNum": "99"
          }
        }
        {
          "partition": {
            "taskId": "lcc-example123-1-in_progress"
          },
          "offset": {
            "earliestIncomplete": "2023-08-03T10:24:25Z",
            "completedFiles": "[{\"filePath\":\"topics/babc_4/partition=0/babc_4+0+00000.json\",\"creationTime\":\"2023-08-03T10:33:04Z\"},{\"filePath\":\"topics/abc_2/partition=0/abc_2+0+00000.json\",\"creationTime\":\"2023-08-03T10:46:06Z\"}]",
            "recordNum": "98"
          }
        }
    ],
    "metadata": {
        "observed_at": "2024-03-28T17:57:48.139635200Z"
    }
}

Responses include the following information:

  • The position of latest offset.

  • The observed time of the offset in the metadata portion of the payload. The observed_at time indicates a snapshot in time for when the API retrieved the offset. A running connector is always updating its offsets. Use observed_at to get a sense for the gap between real time and the time at which the request was made. By default, offsets are observed every minute. Calling GET repeatedly will fetch more recently observed offsets.

  • Information about the connector.

You can approach offset updates in two ways:

  • Modify the earliestIncomplete time to reset the offsets so that next scan will source the files with creationTime equal to or after the new earliestIncomplete.

    If you use this approach, consider this:

    • If earliestIncomplete is set to a later time, the connector starts sourcing the files with creationTime equal to or after the earliestIncomplete and skips records.

    • If earliestIncomplete is set to an earlier time, the connector might produce duplicate records because it starts sourcing every record from files with a creationTime equal to or after the earlier time.

  • If you want to skip processing a file or files, add the files to completedFiles.

To update the offset, make a POST request that specifies the environment, Kafka cluster, and connector name. Include a JSON payload that specifies new offset and a patch type.

POST /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets/request
Host: https://api.confluent.cloud

 {
     "type": "PATCH",
     "offsets": [
         {
             "partition": {
                 "taskId": "lcc-devc3m1zkj-0"
             },
             "offset": {
                 "completedFiles": "[{\"filePath\":\"source/file_0\",\"creationTime\":\"2024-03-06T17:30:28.391Z\"},{\"filePath\":\"source/file_7\",\"creationTime\":\"2024-03-06T17:30:28.395Z\"},{\"filePath\":\"source/file_9\",\"creationTime\":\"2024-03-06T17:30:28.409Z\"},{\"filePath\":\"source/file_1\",\"creationTime\":\"2024-03-06T17:30:28.681Z\"},{\"filePath\":\"source/file_8\",\"creationTime\":\"2024-03-06T17:30:28.681Z\"},{\"filePath\":\"source/file_6\",\"creationTime\":\"2024-03-06T17:30:28.715Z\"},{\"filePath\":\"source/file_30\",\"creationTime\":\"2024-03-06T17:30:28.969Z\"},{\"filePath\":\"source/file_39\",\"creationTime\":\"2024-03-06T17:30:28.970Z\"},{\"filePath\":\"source/file_37\",\"creationTime\":\"2024-03-06T17:30:28.993Z\"},{\"filePath\":\"source/file_36\",\"creationTime\":\"2024-03-06T17:30:29.265Z\"},{\"filePath\":\"source/file_31\",\"creationTime\":\"2024-03-06T17:30:29.268Z\"},{\"filePath\":\"source/file_38\",\"creationTime\":\"2024-03-06T17:30:29.278Z\"},{\"filePath\":\"source/file_25\",\"creationTime\":\"2024-03-06T17:30:29.549Z\"},{\"filePath\":\"source/file_22\",\"creationTime\":\"2024-03-06T17:30:29.551Z\"},{\"filePath\":\"source/file_13\",\"creationTime\":\"2024-03-06T17:30:29.552Z\"},{\"filePath\":\"source/file_47\",\"creationTime\":\"2024-03-06T17:30:30.015Z\"},{\"filePath\":\"source/file_14\",\"creationTime\":\"2024-03-06T17:30:30.020Z\"},{\"filePath\":\"source/file_40\",\"creationTime\":\"2024-03-06T17:30:30.028Z\"},{\"filePath\":\"source/file_15\",\"creationTime\":\"2024-03-06T17:30:30.305Z\"}]",
                 "earliestIncomplete": "2024-03-06T17:30:28.391Z",
                 "recordNum": "0"
             }
         }
     ]
 }

Considerations:

  • You can only make one offset change at a time for a given connector.

  • This is an asynchronous request. To check the status of this request, you must use the check offset status API. For more information, see Get the status of an offset request.

  • For source connectors, the connector attempts to read from the position defined by the requested offsets.

Response:

Successful calls return HTTP 202 Accepted with a JSON payload that describes the offset.

{
    "id": "lcc-example123",
    "name": "{connector_name}",
    "offsets": [
        {
            "partition": {
                "taskId": "lcc-example123-0"
            },
            "offset": {
                "completedFiles": "[{\"filePath\":\"source/file_0\",\"creationTime\":\"2024-03-06T17:30:28.391Z\"},{\"filePath\":\"source/file_7\",\"creationTime\":\"2024-03-06T17:30:28.395Z\"},{\"filePath\":\"source/file_9\",\"creationTime\":\"2024-03-06T17:30:28.409Z\"},{\"filePath\":\"source/file_1\",\"creationTime\":\"2024-03-06T17:30:28.681Z\"},{\"filePath\":\"source/file_8\",\"creationTime\":\"2024-03-06T17:30:28.681Z\"},{\"filePath\":\"source/file_6\",\"creationTime\":\"2024-03-06T17:30:28.715Z\"},{\"filePath\":\"source/file_30\",\"creationTime\":\"2024-03-06T17:30:28.969Z\"},{\"filePath\":\"source/file_39\",\"creationTime\":\"2024-03-06T17:30:28.970Z\"},{\"filePath\":\"source/file_37\",\"creationTime\":\"2024-03-06T17:30:28.993Z\"},{\"filePath\":\"source/file_36\",\"creationTime\":\"2024-03-06T17:30:29.265Z\"},{\"filePath\":\"source/file_31\",\"creationTime\":\"2024-03-06T17:30:29.268Z\"},{\"filePath\":\"source/file_38\",\"creationTime\":\"2024-03-06T17:30:29.278Z\"},{\"filePath\":\"source/file_25\",\"creationTime\":\"2024-03-06T17:30:29.549Z\"},{\"filePath\":\"source/file_22\",\"creationTime\":\"2024-03-06T17:30:29.551Z\"},{\"filePath\":\"source/file_13\",\"creationTime\":\"2024-03-06T17:30:29.552Z\"},{\"filePath\":\"source/file_47\",\"creationTime\":\"2024-03-06T17:30:30.015Z\"},{\"filePath\":\"source/file_14\",\"creationTime\":\"2024-03-06T17:30:30.020Z\"},{\"filePath\":\"source/file_40\",\"creationTime\":\"2024-03-06T17:30:30.028Z\"},{\"filePath\":\"source/file_15\",\"creationTime\":\"2024-03-06T17:30:30.305Z\"}]",
                "earliestIncomplete": "2024-03-06T17:30:28.391Z",
                "recordNum": "0"
            }
        }
    ],
    "requested_at": "2024-03-28T17:58:45.606796307Z",
    "type": "PATCH"
}

Responses include the following information:

  • The requested position of the offsets in the source.

  • The time of the request to update the offset.

  • Information about the connector.

To delete the offset, make a POST request that specifies the environment, Kafka cluster, and connector name. Include a JSON payload that specifies the delete type.

 POST /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets/request
 Host: https://api.confluent.cloud

{
  "type": "DELETE"
}

Considerations:

  • Delete requests delete the offset for the provided partition and reset to the base state. A delete request is as if you created a fresh new connector.

  • This is an asynchronous request. To check the status of this request, you must use the check offset status API. For more information, see Get the status of an offset request.

  • Do not issue delete and patch requests at the same time.

  • For source connectors, the connector attempts to read from the position defined in the base state.

Response:

Successful calls return HTTP 202 Accepted with a JSON payload that describes the result.

{
  "id": "lcc-example123",
  "name": "{connector_name}",
  "offsets": [],
  "requested_at": "2024-03-28T17:59:45.606796307Z",
  "type": "DELETE"
}

Responses include the following information:

  • Empty offsets.

  • The time of the request to delete the offset.

  • Information about Kafka cluster and connector.

  • The type of request.

To get the status of a previous offset request, make a GET request that specifies the environment, Kafka cluster, and connector name.

GET /connect/v1/environments/{environment_id}/clusters/{kafka_cluster_id}/connectors/{connector_name}/offsets/request/status
Host: https://api.confluent.cloud

Considerations:

  • The status endpoint always shows the status of the most recent PATCH/DELETE operation.

Response:

Successful calls return HTTP 200 with a JSON payload that describes the result. The following is an example of an applied patch.

{
   "request": {
      "id": "lcc-example123",
      "name": "{connector_name}",
      "offsets": [
          {
              "partition": {
                  "taskId": "lcc-example123-0"
              },
              "offset": {
                  "completedFiles": "[{\"filePath\":\"source/file_0\",\"creationTime\":\"2024-03-06T17:30:28.391Z\"},{\"filePath\":\"source/file_7\",\"creationTime\":\"2024-03-06T17:30:28.395Z\"},{\"filePath\":\"source/file_9\",\"creationTime\":\"2024-03-06T17:30:28.409Z\"},{\"filePath\":\"source/file_1\",\"creationTime\":\"2024-03-06T17:30:28.681Z\"},{\"filePath\":\"source/file_8\",\"creationTime\":\"2024-03-06T17:30:28.681Z\"},{\"filePath\":\"source/file_6\",\"creationTime\":\"2024-03-06T17:30:28.715Z\"},{\"filePath\":\"source/file_30\",\"creationTime\":\"2024-03-06T17:30:28.969Z\"},{\"filePath\":\"source/file_39\",\"creationTime\":\"2024-03-06T17:30:28.970Z\"},{\"filePath\":\"source/file_37\",\"creationTime\":\"2024-03-06T17:30:28.993Z\"},{\"filePath\":\"source/file_36\",\"creationTime\":\"2024-03-06T17:30:29.265Z\"},{\"filePath\":\"source/file_31\",\"creationTime\":\"2024-03-06T17:30:29.268Z\"},{\"filePath\":\"source/file_38\",\"creationTime\":\"2024-03-06T17:30:29.278Z\"},{\"filePath\":\"source/file_25\",\"creationTime\":\"2024-03-06T17:30:29.549Z\"},{\"filePath\":\"source/file_22\",\"creationTime\":\"2024-03-06T17:30:29.551Z\"},{\"filePath\":\"source/file_13\",\"creationTime\":\"2024-03-06T17:30:29.552Z\"},{\"filePath\":\"source/file_47\",\"creationTime\":\"2024-03-06T17:30:30.015Z\"},{\"filePath\":\"source/file_14\",\"creationTime\":\"2024-03-06T17:30:30.020Z\"},{\"filePath\":\"source/file_40\",\"creationTime\":\"2024-03-06T17:30:30.028Z\"},{\"filePath\":\"source/file_15\",\"creationTime\":\"2024-03-06T17:30:30.305Z\"}]",
                  "earliestIncomplete": "2024-03-06T17:30:28.391Z",
                  "recordNum": "0"
              }
          }
      ],
      "requested_at": "2024-03-28T17:58:45.606796307Z",
      "type": "PATCH"
   },
   "status": {
      "phase": "APPLIED",
      "message": "The Connect framework-managed offsets for this connector have been altered successfully. However, if this connector manages offsets externally, they will need to be manually altered in the system that the connector uses."
   },
   "previous_offsets": [
       {
           "partition": {
               "taskId": "lcc-example123-0"
           },
           "offset": {
               "completedFiles": "[{\"filePath\":\"source/file_31\",\"creationTime\":\"2024-03-06T17:30:29.268Z\"},{\"filePath\":\"source/file_38\",\"creationTime\":\"2024-03-06T17:30:29.278Z\"},{\"filePath\":\"source/file_25\",\"creationTime\":\"2024-03-06T17:30:29.549Z\"},{\"filePath\":\"source/file_22\",\"creationTime\":\"2024-03-06T17:30:29.551Z\"},{\"filePath\":\"source/file_13\",\"creationTime\":\"2024-03-06T17:30:29.552Z\"},{\"filePath\":\"source/file_47\",\"creationTime\":\"2024-03-06T17:30:30.015Z\"},{\"filePath\":\"source/file_14\",\"creationTime\":\"2024-03-06T17:30:30.020Z\"},{\"filePath\":\"source/file_40\",\"creationTime\":\"2024-03-06T17:30:30.028Z\"},{\"filePath\":\"source/file_15\",\"creationTime\":\"2024-03-06T17:30:30.305Z\"},{\"filePath\":\"source/file_49\",\"creationTime\":\"2024-03-06T17:30:30.313Z\"},{\"filePath\":\"source/file_12\",\"creationTime\":\"2024-03-06T17:30:30.326Z\"},{\"filePath\":\"source/file_23\",\"creationTime\":\"2024-03-06T17:30:30.600Z\"},{\"filePath\":\"source/file_24\",\"creationTime\":\"2024-03-06T17:30:30.613Z\"},{\"filePath\":\"source/file_48\",\"creationTime\":\"2024-03-06T17:30:30.639Z\"},{\"filePath\":\"source/file_46\",\"creationTime\":\"2024-03-06T17:30:30.899Z\"},{\"filePath\":\"source/file_41\",\"creationTime\":\"2024-03-06T17:30:30.926Z\"},{\"filePath\":\"source/file_3\",\"creationTime\":\"2024-03-06T17:30:30.927Z\"},{\"filePath\":\"source/file_4\",\"creationTime\":\"2024-03-06T17:30:31.198Z\"},{\"filePath\":\"source/file_5\",\"creationTime\":\"2024-03-06T17:30:31.220Z\"},{\"filePath\":\"source/file_2\",\"creationTime\":\"2024-03-06T17:30:31.225Z\"}]",
               "earliestIncomplete": "2024-03-06T17:30:29.268Z",
               "recordNum": "0"
           }
       }
   ],
   "applied_at": "2024-03-28T17:58:48.079141883Z"
}

Responses include the following information:

  • The original request, including the time it was made.

  • The status of the request: applied, pending, or failed.

  • The time you issued the status request.

  • The previous offsets. These are the offsets that the connector last updated prior to updating the offsets. Use these to try to restore the state of your connector if a patch update causes your connector to fail or to return a connector to its previous state after rolling back.

JSON payload

The table below offers a description of the unique fields in the JSON payload for managing offsets of the object store connectors, including the following connectors:

  • Amazon S3 Source connector

  • Azure Blob Storage Source connector

  • Google Cloud Storage (GCS) Source connector

Field

Definition

Required/Optional

taskId

Represents the partition in the following format: connector-name-<taskid>[-in-progress]

  • connector-name is the name of the connector.

  • taskid is the task id.

  • in-progress is conditional and only appears if a file is currently being sourced. After the file is processed, the file appears listed in completedFiles.

Required

earliestIncomplete

The position of the latest offset. When a connectors starts or restarts, the connector reads the files with a creation time equal to or after earliestIncomplete offset. These files are sorted by creation time then filename.

Required

completedFiles

List of sourced files.

Required

recordNum

Number of records sourced.

Required

Quick Start

Use this quick start to get up and running with the Confluent Cloud Amazon S3 Source connector. The quick start provides the basics of selecting the connector and configuring it to get files from an Amazon S3 bucket.

Prerequisites

  • Kafka cluster credentials. The following lists the different ways you can provide credentials.

    • Enter an existing service account resource ID.

    • Create a Confluent Cloud service account for the connector. Make sure to review the ACL entries required in the service account documentation. Some connectors have specific ACL requirements.

    • Create a Confluent Cloud API key and secret. To create a key and secret, you can use confluent api-key create or you can autogenerate the API key and secret directly in the Cloud Console when setting up the connector.

Using the Confluent Cloud Console

Step 1: Launch your Confluent Cloud cluster

To create and launch a Kafka cluster in Confluent Cloud, see Create a kafka cluster in Confluent Cloud.

Step 2: Add a connector

In the left navigation menu, click Connectors. If you already have connectors in your cluster, click + Add connector.

Step 3: Select your connector

Click the Amazon S3 Source connector card.

Amazon S3 Source connector card

Step 4: Enter the connector details

Note

  • Make sure you have all your prerequisites completed.

  • An asterisk ( * ) designates a required entry.

At the Add Amazon S3 Source Connector screen, complete the following:

  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. 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.

  1. Click Continue.

  1. Under AWS credentials, select how you want to authenticate with AWS:

    • If you select Access Keys, enter your AWS credentials in the Amazon Access Key ID and Amazon Secret Access Key fields to connect to Amazon S3. For information about how to set these up, see Access Keys.

    • If you select IAM Roles, choose an existing integration name under Provider integration name dropdown that has access to your resource. For more information, see Manage Provider Integration for Fully-Managed Connectors in Confluent Cloud.

  2. Enter the following S3 Bucket details:

    • S3 bucket name: S3 bucket name.

    • AWS Region: Set to the AWS region where your S3 bucket resides.

    • S3 Path-style Access: Whether to use S3 path-style access. For more information, see the AWS Path-style access documentation.

  3. Click Continue.

  1. Configure the following:

    • (Optional) 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 setup, see Manage CSFLE for connectors.

    • Select an Input Message Format. Supports Avro, Bytes, CSV, JSON, and Parquet format. A valid schema must be available in Schema Registry to use a schema-based message format, like Avro.

    • Select an Output Message Format. Defaults to the file format selected for the input message format. Supports Avro, Bytes, JSON, JSON Schema, Protobuf, and String. A valid schema must be available in Schema Registry if using a schema-based format.

    • Enter the Topic Name Regex Patterns: A comma-separated list of pairs in the format <kafka topic>:<regex>. The connector uses this list to map file paths to Kafka topics. For example, the property topic1:.*\.json sources all files ending in .json to a Kafka topic named topic1. You can specify multiple of these <kafka topic>:<regex> mappings to send different sets of files to different topics. Any files that aren’t mapped by a regex are ignored. The connector sends files that match multiple mappings to the first topic in the list that maps the file.

    Storage

    • Topics directory. Top-level directory name where data to be ingested is stored. Defaults to topics.

      Note

      If you enter a blank space instead of accepting the default option topics, the connector reads all the data specified under the Amazon S3 bucket.

    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?.

    Auto-restart policy

    • Enable Connector Auto-restart: Control 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. In such cases, you would need to manually restart the connector.

    Data polling policy

    • S3 poll interval in milliseconds (ms). Defaults to 60000 ms (one minute).

    • Max records per poll. The maximum amount of records to return each time the connector polls storage. Defaults to 200. The maximum value supported is 10000 and the minimum value is 1.

    How should we connect to your S3 bucket?

    • Number of Retries on S3 Errors: The number of times a single S3 API call should be retried in the case that it fails with a retriable error (such as a throttling exception). Once this limit is exceeded, the Kafka Connect poll itself may retry (based upon the Kafka Connect-based retry configuration).

    • Retry Backoff on S3 Errors (ms): How long to wait in milliseconds before attempting the first retry of a failed S3 request. Upon a failure, this connector may wait up to twice as long as the previous wait, up to the maximum number of retries. This avoids retrying in a tight loop under failure scenarios.

    • S3 Accelerated Endpoint: Use an S3 accelerated endpoint.

    • Send S3 Expect Continue Request: Enable/disable use of the HTTP/1.1 handshake using EXPECT: 100-CONTINUE during a multi- part upload. If true, the client waits for a 100 (CONTINUE) response before sending the request body. If false, the client uploads the entire request body without checking if the server is willing to accept the request.

    • S3 Server Side Encryption Algorithm: The S3 server-side encryption algorithm.

    • S3 Server Side Encryption Customer-Provided Key (SSE-C): The S3 Server-Side Encryption customer-provided key (SSE-C).

    Storage

    • Task Batch Size: The number of files assigned to each task at a time. Defaults to 10. The maximum value supported is 2000 and the minimum value is 1.

    • File Discovery Starting Timestamp: A Unix timestamp–that is, seconds since Jan 1, 1970 UTC–in epoch milliseconds that denotes where to start processing files. Any file encountered with a creation time earlier than this will be ignored. Note that this configuration property should only be used when there are no stored offsets for a connector–that is, this parameter is intended for new connectors to start from a specific timestamp rather than reading all the files in a bucket.

    • Directory Delimiter Character: The pattern to use as the delimiter character for directories. Defaults to /.

    • Behavior on Errors: Error handling behavior setting for storage connectors. Must be configured to one of the following: IGNORE or FAIL.

    • Byte Array Line Separator: String inserted between records when using ByteArrayFormat. Defaults to \\n and may contain escape sequences like \\n. An input record that contains the line separator looks like multiple records in the storage object input.

    • Enable Embedded JSON Schema: Enable reading of JSON messages with schema embedded.

    • CSV - Separator character: The character that separates each field in the form of an integer. Typically in a CSV file, this is a , (44) character. A TSV file would use a tab (9) character. Applicable only if input.data.format is set to CSV.

    • CSV - Treat first row as header: A flag to indicate if the first row of data contains the header of the file. Applicable only if input.data.format is set to CSV.

    • CSV - Null field indicator: Indicator to determine how the CSV Reader can determine if a field is null. For more information, see the Enum CSVReaderNullFieldIndicator class. Applicable only if input.data.format is set to CSV .

    • CSV - Value schema: The schema for the value written to Kafka. A default schema will be auto-generated if no value schema is provided. Applicable only if input.data.format is set to CSV.

    • CSV - File character set: The character set to read the file with. Applicable only if input.data.format is set to CSV.

    • CSV - Skip lines: The number of lines to skip in the beginning of the file. Applicable only if input.data.format is set to CSV.

    • CSV - Escape character: The character as an integer to use when a special character is encountered. The default escape character is typically a \\ (92). Applicable only if input.data.format is set to CSV.

    • CSV - Quote character: The character that is used to quote a field. Typically in a CSV file, this is a \" (34) character. This happens when the csv.separator.char is within the data. Applicable only if input.data.format is set to CSV.

    • CSV - Ignore leading whitespace: This property sets the ignore leading whitespace setting. If true, the white space in front of a quote in a field is ignored. Applicable only if input.data.format is set to CSV.

    • CSV - Ignore quotations: This property sets the ignore quotations mode. If true, quotations are ignored. Applicable only if input.data.format is set to CSV.

    • CSV - Use strict quotes: This property sets the strict quotes setting. If true, characters outside the quotes are ignored. Applicable only if input.data.format is set to CSV.

    Transforms

    For all property values and definitions, see Configuration Properties.

  2. Click Continue.

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.

  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 the Kafka topic.

After the connector is running, verify that records are populating the Kafka topic.

Note

The S3 Source connector loads and filters all object names in the bucket before it starts sourcing records. When starting up, the connector may display RUNNING but not show any throughput. This is because bucket loading is not finished. For buckets with a large amount of objects, bucket loading can take several minutes to complete.

Creating more top-level folders will help process files with less delays and scale better in the long term.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples section.

Using the Confluent CLI

Complete the following steps to set up and run the connector using the Confluent CLI.

Note

Make sure you have all your prerequisites completed.

Step 1: List the available connectors

Enter the following command to list available connectors:

confluent connect plugin list

Step 2: List the connector configuration properties

Enter the following command to show the connector configuration properties:

confluent connect plugin describe <connector-plugin-name>

The command output shows the required and optional configuration properties.

Step 3: Create the connector configuration file

Create a JSON file that contains the connector configuration properties. The following example shows the required connector properties.

{
  "connector.class": "S3Source",
  "name": "S3SourceConnector_0",
  "topic.regex.list": "topic1:.*\.json",
  "topics.dir": " ",
  "kafka.auth.mode": "SERVICE_ACCOUNT",
  "kafka.service.account.id": "<service-account-resource-ID>",
  "input.data.format": "JSON",
  "output.data.format": "BYTES",
  "aws.access.key.id": "<access-key>",
  "aws.secret.access.id": "<secret-access-id>",
  "s3.bucket.name": "<bucket-name>",
  "tasks.max": "1",
}

Note the following required property definitions:

  • "connector.class": Identifies the connector plugin name.

  • "name": Sets a name for your new connector.

  • "topic.regex.list": A comma-separated list of pairs in the format <kafka topic>:<regex>. The connector uses this list to map file paths to Kafka topics. For example, the property topic1:.*\.json sources all files ending in .json to a Kafka topic named topic1. You can specify multiple of these <kafka topic>:<regex> mappings to send different sets of files to different topics. Any files that aren’t mapped by a regex are ignored. The connector sends files that match multiple mappings to the first topic in the list that maps the file.

    Note

    For more information about accepted regular expressions, see Google RE2 syntax.

  • "topics.dir": (Optional) If this property is not used, the default folder where the connector reads data from is topics. If you set this property to a blank space (as shown in the example configuration), the connector reads all data in the S3 bucket.

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

    confluent iam service-account list

    For example:

    confluent iam service-account list

   Id     | Resource ID |       Name        |    Description
+---------+-------------+-------------------+-------------------
   123456 | sa-l1r23m   | sa-1              | Service account 1
   789101 | sa-l4d56p   | sa-2              | Service account 2

  • "input.data.format": Supports Avro, Bytes, CSV, JSON, and Parquet format. A valid schema must be available in Schema Registry to use a schema-based message format, like Avro.

  • "output.data.format": Sets the output Kafka record value format. Options are Avro, Bytes, JSON, JSON Schema, Protobuf, and String. A valid schema must be available in Schema Registry if using a schema-based format.

  • "value.schema": The schema for the value written to Kafka. A default schema will be auto-generated if no value schema is provided. Applicable only if input.data.format is set to CSV.

    For example:

    {
   "type": "STRUCT",
   "fieldSchemas": {
     "age": {"type": "INT64"},
     "firstname": {"type": "STRING"},
     "lastname": {"type": "STRING"}
   }
 }

  • "tasks.max": The total number of tasks to run in parallel. More tasks may improve performance.

  • Transforms and Predicates: See the Single Message Transforms (SMT) documentation for details.

Note

(Optional) To enable CSFLE for data encryption, specify the following properties:

  • csfle.enabled: Flag to indicate whether the connector honors CSFLE 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 setup, see Manage CSFLE for connectors.

For configuration property values and descriptions, see Configuration Properties.

Step 4: Load the properties file and create the connector

Enter the following command to load the configuration and start the connector:

confluent connect cluster create --config-file <file-name>.json

For example:

confluent connect cluster create --config-file s3-source-config.json

Example output:

Created connector S3SourceConnector_0 lcc-ix4dl

Step 5: Check the connector status

Enter the following command to check the connector status:

confluent connect cluster list

Example output:

ID          |       Name            | Status  | Type
+-----------+-----------------------+---------+------+
lcc-ix4dl   | S3SourceConnector_0   | RUNNING | source

Step 6. Check the Kafka topic.

After the connector is running, verify that records are populating the Kafka topic.

Note

The S3 Source connector loads and filters all object names in the bucket before it starts sourcing records. When starting up, the connector may display RUNNING but not show any throughput. This is because bucket loading is not finished. For buckets with a large amount of objects, bucket loading can take several minutes to complete.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect Usage Examples 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.

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

Which topic(s) do you want to send data to?

topic.regex.list

A list of topics along with a regex expression of the files which are to be sent to that topic. For example: “my-topic:.*” will send all files to “my-topic”, while a list containing only the expression “special-topic:.*.json” will send only files starting with “.json” to “special-topic”, and all other files not matching any patterns will be ignored and not sourced. Files that match multiple mappings will be sent to the first topic in the list that maps the file. The topic.regex.list property matches the full path (for example, folder/file.txt), not just the filename.

  • Type: list

  • Importance: high

Kafka Cluster credentials

kafka.auth.mode

Kafka Authentication mode. It can be one of KAFKA_API_KEY or SERVICE_ACCOUNT. It defaults to KAFKA_API_KEY mode.

  • Type: string

  • Default: KAFKA_API_KEY

  • Valid Values: KAFKA_API_KEY, SERVICE_ACCOUNT

  • Importance: high

kafka.api.key

Kafka API Key. Required when kafka.auth.mode==KAFKA_API_KEY.

  • Type: password

  • Importance: high

kafka.service.account.id

The Service Account that will be used to generate the API keys to communicate with Kafka Cluster.

  • Type: string

  • Importance: high

kafka.api.secret

Secret associated with Kafka API key. Required when kafka.auth.mode==KAFKA_API_KEY.

  • Type: password

  • Importance: high

Schema Config

schema.context.name

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 and output messages

input.data.format

Sets the input message format. Valid entries are AVRO, JSON, or BYTES. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO.

  • Type: string

  • Valid Values: AVRO, BYTES, CSV, JSON, PARQUET

  • Importance: high

output.data.format

Set the output message format for values. Valid entries are AVRO, JSON, JSON_SR, PROTOBUF, 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. If no value for this property is provided, the value specified for the ‘input.data.format’ property is used.

  • Type: string

  • Valid Values: AVRO, BYTES, JSON, JSON_SR, PROTOBUF, STRING

  • Importance: high

AWS credentials

authentication.method

Select how you want to authenticate with AWS.

  • Type: string

  • Default: Access Keys

  • Importance: high

aws.access.key.id

The AWS Access Key used to connect to Amazon S3.

  • Type: password

  • Importance: high

provider.integration.id

Select an existing integration that has access to your resource. In case you need to integrate a new IAM role, use provider integration

  • Type: string

  • Importance: high

aws.secret.access.key

The AWS Secret Key used to connect to Amazon S3.

  • Type: password

  • Importance: high

How should we connect to your S3 bucket?

s3.bucket.name

  • Type: string

  • Importance: high

s3.region

Set to the AWS region where your S3 bucket resides.

  • Type: string

  • Importance: high

s3.part.retries

The number of times a single S3 API call should be retried in the case that it fails with a “retriable” error (such as a throttling exception). Once this limit is exceeded, the Kafka Connect poll itself may retry (based upon the Kafka Connect-based retry configuration).

  • Type: int

  • Default: 3

  • Importance: medium

s3.retry.backoff.ms

How long to wait in milliseconds before attempting the first retry of a failed S3 request. Upon a failure, this connector may wait up to twice as long as the previous wait, up to the maximum number of retries. This avoids retrying in a tight loop under failure scenarios.

  • Type: int

  • Default: 200

  • Importance: medium

ui.s3.wan.mode

Use an S3 accelerated endpoint.

  • Type: string

  • Default: NO

  • Valid Values: NO, YES

  • Importance: medium

ui.s3.path.style.access

Whether to use s3 path-style access.

  • Type: string

  • Default: NO

  • Valid Values: NO, YES

  • Importance: medium

s3.http.send.expect.continue

Enable/disable use of the HTTP/1.1 handshake using EXPECT: 100-CONTINUE during multi-part upload. If true, the client waits for a 100 (CONTINUE) response before sending the request body. If false, the client uploads the entire request body without checking if the server is willing to accept the request.

  • Type: string

  • Default: YES

  • Valid Values: NO, YES

  • Importance: medium

ui.s3.ssea.name

The S3 server-side encryption algorithm.

  • Type: string

  • Default: NONE

  • Valid Values: AES256, AWS:KMS, NONE

  • Importance: medium

s3.sse.customer.key

The S3 Server-Side Encryption customer-provided key (SSE-C).

  • Type: password

  • Importance: medium

Storage

topics.dir

Top-level directory (in the S3 bucket) where data to be ingested is stored.

  • Type: string

  • Default: topics

  • Importance: high

task.batch.size

The number of files assigned to each task at a time

  • Type: int

  • Default: 10

  • Valid Values: [1,…,2000]

  • Importance: high

file.discovery.starting.timestamp

A Unix timestamp (in epoch milliseconds since Jan 1, 1970 UTC) that denotes where to start processing files. The connector ignores any file with a creation time earlier than this timestamp. Note that the connector only uses this configuration property when no offsets are stored for a connector. This parameter allows new connectors to start from a specific timestamp instead of reading all files in a bucket.

  • Type: long

  • Default: 0

  • Importance: high

directory.delim

Directory delimiter pattern.

  • Type: string

  • Default: /

  • Importance: medium

ui.behavior.on.error

Error handling behavior setting for storage connectors. Must be configured to one of the following: IGNORE, FAIL

  • Type: string

  • Default: FAIL

  • Valid Values: FAIL, IGNORE

  • Importance: medium

format.bytearray.separator

String inserted between records for ByteArrayFormat. Defaults to n and may contain escape sequences like n. An input record that contains the line separator looks like multiple records in the storage object input.

  • Type: string

  • Importance: medium

format.json.schema.enable

Enable reading of JSON messages with schema embedded

  • Type: boolean

  • Default: false

  • Importance: medium

csv.separator.char

The character that separates each field in the form of an integer. Typically in a CSV file, this is a , (44) character. A TSV file would use a tab (9) character. Applicable only if input.data.format is set to CSV.

  • Type: int

  • Default: 44

  • Importance: low

csv.first.row.as.header

Flag to indicate if the fist row of data contains the header of the file. Applicable only if input.data.format is set to CSV.

  • Type: boolean

  • Default: true

  • Importance: medium

csv.null.field.indicator

Indicator to determine how the CSV Reader can determine if a field is null. For more information, see http://opencsv.sourceforge.net/apidocs/com/opencsv/enums/CSVReaderNullFieldIndicator.html. Applicable only if input.data.format is set to CSV .

  • Type: string

  • Default: NEITHER

  • Importance: low

value.schema

The schema for the value written to Kafka. A default schema will be auto-generated if no value schema is provided. Applicable only if input.data.format is set to CSV.

  • Type: string

  • Importance: high

csv.file.charset

Character set to read file with. Applicable only if input.data.format is set to CSV

  • Type: string

  • Default: UTF-8

  • Importance: low

csv.skip.lines

The number of lines to skip in the beginning of the file. Applicable only if input.data.format is set to CSV.

  • Type: int

  • Default: 0

  • 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). Applicable only if input.data.format is set to CSV.

  • Type: int

  • Default: 92

  • Importance: low

csv.quote.char

The character that is used to quote a field. Typically in a CSV file, this is a " (34) character. This happens when the csv.separator.char is within the data. Applicable only if input.data.format is set to CSV.

  • Type: int

  • Default: 34

  • Importance: low

csv.ignore.leading.whitespace

Sets the ignore leading whitespace setting. If true, the white space in front of a quote in a field is ignored. Applicable only if input.data.format is set to CSV.

  • Type: boolean

  • Default: true

  • Importance: low

csv.ignore.quotations

Sets the ignore quotations mode. If true, quotations are ignored. Applicable only if input.data.format is set to CSV.

  • Type: boolean

  • Default: false

  • Importance: low

csv.strict.quotes

Sets the strict quotes setting. If true, characters outside the quotes are ignored. Applicable only if input.data.format is set to CSV.

  • Type: boolean

  • Default: false

  • Importance: low

Data polling policy

s3.poll.interval.ms

Frequency in milliseconds to poll for new or removed folders. This may result in updated task configurations starting to poll for data in added folders or stopping polling for data in removed folders

  • Type: long

  • Default: 60000 (1 minute)

  • Valid Values: [1000,…]

  • Importance: medium

record.batch.max.size

The maximum amount of records to return each time storage is polled.

  • Type: int

  • Default: 200

  • Valid Values: [1,…,10000]

  • Importance: medium

Number of tasks for this connector

tasks.max

The total number of tasks to run in parallel.

  • Type: int

  • Valid Values: [1,…,1000]

  • Importance: high

Additional Configs

header.converter

The converter class for the headers. This is used to serialize and deserialize the headers of the messages.

  • 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.

  • 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.

  • 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.

  • 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.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: none

  • 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.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

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. This example also shows how to use Confluent CLI to manage your resources in Confluent Cloud.

    ../_images/topology.png

  • Try Confluent Cloud on AWS Marketplace with $1000 of free usage for 30 days, and pay as you go. No credit card is required.