Docs Connect Components Inputs redpanda_common redpanda_common Beta Type: InputOutput Available in: Self-Managed License: This component requires an Enterprise license. To upgrade, go to the Redpanda website. Consumes data from a Redpanda (Kafka) broker, using credentials from a common redpanda configuration block. To avoid duplicating Redpanda cluster credentials in your redpanda_common input, output, or any other components in your data pipeline, you can use a single redpanda configuration block. For more details, see the Pipeline example. Introduced in version 4.39.0. If you need to move topic data between Redpanda clusters or other Apache Kafka clusters, consider using the redpanda input and output instead. Common Advanced # Common configuration fields, showing default values input: label: "" redpanda_common: topics: [] # No default (required) regexp_topics: false consumer_group: "" # No default (optional) auto_replay_nacks: true # All configuration fields, showing default values input: label: "" redpanda_common: topics: [] # No default (required) regexp_topics: false rack_id: "" start_from_oldest: true fetch_max_bytes: 50MiB fetch_min_bytes: 1B fetch_max_partition_bytes: 1MiB consumer_group: "" # No default (optional) commit_period: 5s partition_buffer_bytes: 1MB auto_replay_nacks: true Pipeline example This data pipeline reads data from topic_A and topic_B on a Redpanda cluster, and then writes the data to topic_C on the same cluster. The cluster details are configured within the redpanda configuration block, so you only need to configure them once. This is a useful feature when you have multiple inputs and outputs in the same data pipeline that need to connect to the same cluster. input: redpanda_common: topics: [ topic_A, topic_B ] output: redpanda_common: topic: topic_C key: ${! @id } redpanda: seed_brokers: [ "127.0.0.1:9092" ] tls: enabled: true sasl: - mechanism: SCRAM-SHA-512 password: bar username: foo Consumer groups When you specify a consumer group in your configuration, this input consumes one or more topics and automatically balances the topic partitions across any other connected clients with the same consumer group. Otherwise, topics are consumed in their entirety or with explicit partitions. Delivery guarantees If you choose to use consumer groups, the offsets of records received by Redpanda Connect are committed automatically. In the event of restarts, this input uses the committed offsets to resume data consumption where it left off. Redpanda Connect guarantees at-least-once delivery. Records are only confirmed as delivered when all downstream outputs that a record is routed to have also confirmed delivery. Ordering To preserve the order of topic partitions: Records consumed from each partition are processed and delivered in the order that they are received Only one batch of records of a given partition is processed at a time This approach means that although records from different partitions may be processed in parallel, records from the same partition are processed in sequential order. Delivery errors The order in which records are delivered may be disrupted by delivery errors and any error-handling mechanisms that start up. Redpanda Connect uses at-least-once delivery unless instructed otherwise, and this includes reattempting delivery of data when the ordering of that data is no longer guaranteed. For example, a batch of records is sent to an output broker and only a subset of records are delivered. In this scenario, Redpanda Connect (by default) attempts to deliver the records that failed, even though these delivery failures may have been sent before records that were delivered successfully. Use a fallback output To prevent delivery errors from disrupting the order of records, you must specify a fallback output in your pipeline configuration. When adding a fallback output, it is good practice to set the auto_retry_nacks field to false. This also improves the throughput of your pipeline. For example, the following configuration includes a fallback output. If Redpanda Connect fails to write delivery errors to the foo topic, it then attempts to write them into a dead letter queue topic (foo_dlq), which is retried indefinitely as a way to apply back pressure. output: fallback: - redpanda_common: topic: foo - retry: output: redpanda_common: topic: foo_dlq Batching Records are processed and delivered from each partition in the same batches as they are received from brokers. Batch sizes are dynamically sized in order to optimize throughput, but you can tune them further using the following configuration fields: fetch_max_partition_bytes fetch_max_bytes You can break batches down further using the split processor. Metadata This input adds the following metadata fields to each message: kafka_key kafka_topic kafka_partition kafka_offset kafka_timestamp_ms kafka_timestamp_unix kafka_tombstone_message All record headers Fields topics A list of topics to consume from. Use commas to separate multiple topics in a single element. When a consumer_group is specified, partitions are automatically distributed across consumers of a topic. Otherwise, all partitions are consumed. Alternatively, you can specify explicit partitions to consume by using a colon after the topic name. For example, foo:0 would consume the partition 0 of the topic foo. This syntax supports ranges. For example, foo:0-10 would consume partitions 0 through to 10 inclusive. It is also possible to specify an explicit offset to consume from by adding another colon after the partition. For example, foo:0:10 would consume the partition 0 of the topic foo starting from the offset 10. If the offset is not present (or remains unspecified) then the field start_from_oldest determines which offset to start from. Type: array # Examples topics: - foo - bar topics: - things.* topics: - foo,bar topics: - foo:0 - bar:1 - bar:3 topics: - foo:0,bar:1,bar:3 topics: - foo:0-5 regexp_topics Whether listed topics are interpreted as regular expression patterns for matching multiple topics. When topics are specified with explicit partitions, this field must remain set to false. Type: bool Default: false rack_id A rack specifies where the client is physically located, and changes fetch requests to consume from the closest replica as opposed to the leader replica. Type: string Default: "" start_from_oldest Whether to consume from the oldest available offset. Otherwise, messages are consumed from the latest offset. This setting is applied when creating a new consumer group or the saved offset no longer exists. Type: bool Default: true fetch_max_bytes The maximum number of bytes that a broker tries to send during a fetch. If individual records are larger than the fetch_max_bytes value, brokers will still send them. Type: string Default: 50MiB fetch_min_bytes The minimum number of bytes that a broker tries to send during a fetch. This field is equivalent to the Java setting fetch.min.bytes. Type: string Default: 1B fetch_max_partition_bytes The maximum number of bytes that are consumed from a single partition in a fetch request. This field is equivalent to the Java setting fetch.max.partition.bytes. If a single batch is larger than the fetch_max_partition_bytes value, the batch is still sent so that the client can make progress. Type: string Default: 1MiB consumer_group An optional consumer group. When this value is specified: The partitions of any topics, specified in the topics field, are automatically distributed across consumers sharing a consumer group Partition offsets are automatically committed and resumed under this name Consumer groups are not supported when you specify explicit partitions to consume from in the topics field. Type: string commit_period The period of time between each commit of the current partition offsets. Offsets are always committed during shutdown. Type: string Default: 5s partition_buffer_bytes A buffer size (in bytes) for each consumed partition, which allows the internal queuing of records before they are flushed. Increasing this value may improve throughput but results in higher memory utilization. Each buffer can grow slightly beyond this value. Type: string Default: 1MB auto_replay_nacks Whether to automatically replay messages that are rejected (nacked) at the output level. If the cause of rejections is persistent, leaving this option enabled can result in back pressure. Set auto_replay_nacks to false to delete rejected messages. Disabling auto replays can greatly improve memory efficiency of high throughput streams, as the original shape of the data is discarded immediately upon consumption and mutation. Type: bool Default: true 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 redpanda redpanda_migrator