Docs Cloud Develop Managed Connectors GCS Sink Connector Create a GCS Sink Connector The Google Cloud Storage (GCS) Sink connector stores Redpanda messages in a Google Cloud Storage bucket. Prerequisites Before you can create a GCS Sink connector in the Redpanda Cloud, you must: Create a Google Cloud account. Create a service account that will be used to connect to the GCS service. Create a service account key and download it. Create a custom role, which must have the following permissions: storage.objects.create to create items in the GCS bucket storage.objects.delete to overwrite items in the GCS bucket Create a GCS bucket to which to send data. Grant permissions to the bucket your created for your service account. Use the role created in step 4. Limitations The GCS Sink connector has the following limitations: You can use only the STRING and BYTES input formats for CSV output format. You can use only the PARQUET format when your messages contain schema. Create a GCS Sink connector To create the GCS Sink connector: In Redpanda Cloud, click Connectors in the navigation menu, and then click Create Connector. Select Export to Google Cloud Storage. On the Create Connector page, specify the following required connector configuration options: Property name Property key Description Topics to export topics Comma-separated list of the cluster topics you want to replicate to GCS. Topics regex topics.regex Java regular expression of topics to replicate. For example: specify .* to replicate all available topics in the cluster. Applicable only when Use regular expressions is selected. GCS Credentials JSON gcs.credentials.json JSON object with GCS credentials. GCS bucket name gcs.bucket.name Name of an existing GCS bucket to store output files in. Kafka message key format key.converter Format of the key in the Redpanda topic. Use BYTES for no conversion. Kafka message value format value.converter Format of the value in the Redpanda topic. Use BYTES for no conversion. GCS file format format.output.type Format of the files created in GCS: CSV (the default), JSON, JSONL AVRO, or PARQUET. You can use the CSV format output only with BYTES and STRING. Avro codec avro.codec The Avro compression codec to be used for Avro output files. Available values: null (the default), deflate, snappy, and bzip2. Max Tasks tasks.max Maximum number of tasks to use for this connector. The default is 1. Each task replicates exclusive set of partitions assigned to it. Connector name name Globally-unique name to use for this connector. Click Next. Review the connector properties specified, then click Create. Advanced GCS Sink connector configuration In most instances, the preceding basic configuration properties are sufficient. If you require any additional property settings, then specify any of the following optional advanced connector configuration properties by selecting Show advanced options on the Create Connector page: Property name Property key Description File name template file.name.template The template for file names on GCS. Supports {{ variable }} placeholders for substituting variables. Supported placeholders are: topic partition start_offset (the offset of the first record in the file) timestamp:unit=yyyy|MM|dd|HH (the timestamp of the record) key (when used, other placeholders are not substituted) File name prefix file.name.prefix The prefix to be added to the name of each file put in GCS. Output fields format.output.fields Fields to place into output files. Supported values are: 'key', 'value', 'offset', 'timestamp', and 'headers'. Value field encoding format.output.fields.value.encoding The type of encoding to be used for the value field. Supported values are: 'none' and 'base64'. Envelope for primitives format.output.envelope Specifies whether or not to enable additional JSON object wrapping of the actual value. Output file compression file.compression.type The compression type to be used for files put into GCS. Supported values are: 'none', 'gzip', 'snappy', and 'zstd'. Max records per file file.max.records The maximum number of records to put in a single file. Must be a non-negative number. 0 is interpreted as "unlimited", which is the default. In this case files are only flushed after file.flush.interval.ms. File flush interval milliseconds file.flush.interval.ms The time interval to periodically flush files and commit offsets. Value specified must be a non-negative number. Default is 60 seconds. 0 indicates that it is disabled. In this case, files are only flushed after reaching file.max.records record size. GCS bucket check gcs.bucket.check If set to true, the connector will attempt to put a test file to the GCS bucket to validate access. Default is true. GCS retry backoff initial delay milliseconds gcs.retry.backoff.initial.delay.ms Initial retry delay in milliseconds. The default value is 1000. GCS retry backoff max delay milliseconds gcs.retry.backoff.max.delay.ms Maximum retry delay in milliseconds. The default value is 32000. GCS retry backoff delay multiplier gcs.retry.backoff.delay.multiplier Retry delay multiplier. The default value is 2.0. GCS retry backoff max attempts gcs.retry.backoff.max.attempts Retry max attempts. The default value is 6. GCS retry backoff total timeout milliseconds gcs.retry.backoff.total.timeout.ms Retry total timeout in milliseconds. The default value is 50000. Retry back-off kafka.retry.backoff.ms Retry backoff in milliseconds. In case of transient exceptions, useful for performing recovery. Maximum value is 86400000 (24 hours). Error tolerance errors.tolerance Error tolerance response during connector operation. Default value is none and signals that any error will result in an immediate connector task failure. Value of all changes the behavior to skip over problematic records. Dead letter queue topic name errors.deadletterqueue.topic.name The name of the topic to be used as the dead letter queue (DLQ) for messages that result in an error when processed by this sink connector, its transformations, or converters. The topic name is blank by default, which means that no messages are recorded in the DLQ. Dead letter queue topic replication factor errors.deadletterqueue.topic .replication.factor Replication factor used to create the dead letter queue topic when it doesn’t already exist. Enable error context headers errors.deadletterqueue.context .headers.enable When true, adds a header containing error context to the messages written to the dead letter queue. To avoid clashing with headers from the original record, all error context header keys, start with __connect.errors. Map data Use the appropriate key or value converter (input data format) for your data as follows: JSON (org.apache.kafka.connect.json.JsonConverter) when your messages are JSON-encoded. Select Message JSON contains schema, with the schema and payload fields. AVRO (io.confluent.connect.avro.AvroConverter) when your messages contain AVRO-encoded messages, with schema stored in the Schema Registry. STRING (org.apache.kafka.connect.storage.StringConverter) when your messages contain textual data. BYTES (org.apache.kafka.connect.converters.ByteArrayConverter) when your messages contain arbitrary data. You can also select the output data format for your GCS files as follows: CSV to produce data in the CSV format. For CSV only, you can set STRING and BYTES input formats. JSON to produce data in the JSON format as an array of record objects. JSONL to produce data in the JSON format, each message as a separate JSON, one per line. PARQUET to produce data in the PARQUET format when your messages contain schema. AVRO to produce data in the AVRO format when your messages contain schema. Test the connection After the connector is created, check the GCS bucket for a new file. Files should appear after the file flush interval (default is 60 seconds). Troubleshoot If there are any connection issues, an error message is returned. Depending on the GCS bucket check property value, the error results in a failed connector (GCS bucket check = true) or a failed task (GCS bucket check = false). Select Show Logs to view error details. Additional errors and corrective actions follow. Message Action Failed to read credentials from JSON string The credentials given as JSON file in the GCS credentials JSON property are incorrect. Copy a valid key from the Google Cloud service account. The specified bucket does not exist Create the bucket if the bucket does not exist, or correct the bucket name if the bucket exists, but the specified GCS bucket name value is incorrect. No files in the GCS bucket Be sure to wait until the connector performs the first file flush (default is 60 seconds). Back to top × Simple online edits For simple changes, such as fixing a typo, you can edit the content directly on GitHub. Edit on GitHub Or, open an issue to let us know about something that you want us to change. Open an issue Contribution guide For extensive content updates, or if you prefer to work locally, read our contribution guide . Was this helpful? thumb_up thumb_down group Ask in the community mail Share your feedback group_add Make a contribution Google BigQuery Sink Connector HTTP Source Connector