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lensesio/fast-data-dev
Kafka Docker for development. Kafka, Zookeeper, Schema Registry, Kafka-Connect, , 20+ connectors
fast-data-dev packages a full Kafka dev stack into one Docker container — KRaft broker, Schema Registry, Kafka Connect with Lenses' Stream Reactor connectors and Debezium, plus a web UI — so you get a working Kafka environment from a single docker run instead of assembling a five-image docker-compose. It's aimed at developers who want to poke at Kafka/Connect locally, not at anyone modeling production topology.
One container gets you a broker, schema registry, and ~20 prebuilt connectors (S3, GCS, Cassandra, ElasticSearch, JDBC, Debezium CDC) already version-matched, which is the tedious part of a manual Kafka setup. Sample data generators (AIS, NYC taxi, telecom) push real-shaped AVRO/JSON into topics on boot, so you have something to query immediately instead of hand-writing producers. Any Kafka/Connect/Schema Registry property is settable via env var through a dot-to-underscore convention, so you're configuring the real components, not a wrapper around them. Supervisord manages each service individually, so you can restart just Connect or just the broker without tearing down the container.
It's a single-node, single-container setup by design, so there's no way to exercise multi-broker behavior, partition rebalancing, or broker failure — fine for smoke-testing a connector, useless for anything resembling production Kafka. The bundled web UI ships a chunk of 2016-era bower-vendored Angular/Angular Material committed straight into the repo rather than built, which signals real frontend debt. Memory requirements are steep for a 'quick local spin-up' — 2GB minimum, 4GB+ recommended, 6GB+ once connectors are loaded. It blends vanilla Apache Kafka with Lenses' own Stream Reactor connectors under an 'optional enterprise support' banner, so parts of the connector surface are a funnel toward Lenses' commercial product rather than neutral tooling.