console
Redpanda Console (previously known as Kowl) is a web application that helps you manage and debug your Kafka/Redpanda workloads effortlessly.
Skills and agents for working on Redpanda Connect, a stream processor that moves data between sources and sinks with hydration, enrichment, and transformation. Includes a schema.Common metadata audit and a code review for pull requests.
Claude Code
> /plugin marketplace add redpanda-data/connect> /plugin install redpanda-connect@redpanda-connect-plugins
Codex
$ npx skills add redpanda-data/connect -a codex
Cursor
$ npx skills add redpanda-data/connect -a cursor
Gemini CLI
$ npx skills add redpanda-data/connect -a gemini-cli
GitHub Copilot
$ copilot plugin marketplace add redpanda-data/connect$ copilot plugin install redpanda-connect@redpanda-connect-plugins
OpenCode
$ npx skills add redpanda-data/connect -a opencode
Windsurf
$ npx skills add redpanda-data/connect -a windsurf
Redpanda Connect is a stream processor that moves data between a wide range of sources and sinks, with support for hydration, enrichment, transformation, and filtering along the way.
That includes a rich set of change-data-capture (CDC) connectors — for Postgres, MySQL, MongoDB, Oracle, MSSQL, and more — so database changes can flow through your pipelines as first-class events.
It uses Bloblang for mapping, runs as a single static binary or container image, and is easy to operate and monitor.
Stream Postgres changes into Apache Iceberg tables on S3, one Iceberg table per source table:
input:
postgres_cdc:
dsn: postgres://user:pass@db.example.com:5432/app?sslmode=require
schema: public
tables: [ orders, customers ]
stream_snapshot: true
output:
iceberg:
catalog:
url: https://glue.us-east-1.amazonaws.com/iceberg
warehouse: "123456789012"
auth:
aws_sigv4:
region: us-east-1
service: glue
namespace: cdc
table: ${! meta("table") }
storage:
aws_s3:
bucket: my-iceberg-warehouse
region: us-east-1
schema_evolution:
enabled: true
table_location: s3://my-iceberg-warehouse/cdc/
Linux:
curl -LO https://github.com/redpanda-data/redpanda/releases/latest/download/rpk-linux-amd64.zip
unzip rpk-linux-amd64.zip -d ~/.local/bin/
macOS (Homebrew):
brew install redpanda-data/tap/redpanda
Docker:
docker pull docker.redpanda.com/redpandadata/connect
See the getting started guide for more options.
rpk connect run ./config.yaml
With Docker:
# From a config file
docker run --rm -v /path/to/your/config.yaml:/connect.yaml docker.redpanda.com/redpandadata/connect run
# With inline overrides
docker run --rm -p 4195:4195 docker.redpanda.com/redpandadata/connect run \
-s "input.type=http_server" \
-s "output.type=kafka" \
-s "output.kafka.addresses=kafka-server:9092" \
-s "output.kafka.topic=redpanda_topic"
The catalog includes AWS (DynamoDB, Kinesis, S3, SQS, SNS), Azure (Blob, Queue, Table), GCP (Pub/Sub, Cloud Storage, BigQuery), Kafka, NATS (JetStream, Streaming), NSQ, MQTT, AMQP 0.91 (RabbitMQ), AMQP 1, Redis, Cassandra, Elasticsearch, HDFS, HTTP (server, client, websockets), MongoDB, and SQL (MySQL, PostgreSQL, ClickHouse, MSSQL) — and a lot more in the components documentation.
Delivery guarantees can be a tricky subject. Redpanda Connect processes and acknowledges messages using an in-process transaction model with no disk-persisted state, so when it's connecting at-least-once sources and sinks it can guarantee at-least-once delivery — even through crashes, disk corruption, or other server faults.
That's the default, with no caveats, which keeps deployment and scaling straightforward.
Two HTTP endpoints are exposed for orchestration probes:
/ping — liveness probe; always returns 200./ready — readiness probe; returns 200 once both input and output are connected, otherwise 503.Redpanda Connect exposes metrics to Statsd, Prometheus, a JSON HTTP endpoint, and other backends.
OpenTelemetry traces are emitted natively, so you can visualize what's happening inside a pipeline end-to-end.
Redpanda Connect ships with tooling for configuration discovery, debugging, and organization — see the configuration guide.
Requires a currently supported Go version:
git clone git@github.com:redpanda-data/connect
cd connect
task build:all
Components that link against external C libraries (for example zmq4) aren't included by default. To pull them in, set the x_benthos_extra build tag:
# With go
go install -tags "x_benthos_extra" github.com/redpanda-data/connect/v4/cmd/redpanda-connect@latest
# With task
TAGS=x_benthos_extra task build:all
This tag may change or be split into more granular tags in future releases. If the required system libraries aren't installed, the build will fail with an error like ld: library not found for -lzmq.
A multi-stage Dockerfile builds a minimal scratch-based image:
task docker:all
docker run --rm \
-v /path/to/your/config.yaml:/config.yaml \
-v /tmp/data:/data \
-p 4195:4195 \
docker.redpanda.com/redpandadata/connect run /config.yaml
Writing your own plugins in Go is straightforward — check out the API docs and the example plugin repository for reference implementations.
Redpanda Connect uses golangci-lint for linting and gofumpt for formatting. You can configure your editor to use gofumpt automatically — instructions are here.
task fmt # format the codebase
task lint # lint the codebase
task test # unit and template tests
Contributions are welcome. Before opening a pull request, please make sure it has been:
task testtask linttask fmtMost integration tests spin up Docker containers, so they're skipped by task test. You can run them individually with:
go test -run "^Test.*Integration.*$" ./internal/impl/<connector directory>/...
Redpanda Console (previously known as Kowl) is a web application that helps you manage and debug your Kafka/Redpanda workloads effortlessly.
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