Confluent REST Proxy¶
The Confluent REST Proxy provides a RESTful interface to a Kafka cluster, making it easy to produce and consume messages, view the state of the cluster, and perform administrative actions without using the native Kafka protocol or clients.
Some example use cases are:
- Reporting data to Kafka from any frontend app built in any language not supported by official Confluent clients
- Ingesting messages into a stream processing framework that doesn’t yet support Kafka
- Scripting administrative actions
There is a plugin available for Confluent REST Proxy that helps authenticate incoming requests and propagates the authenticated principal to requests to Kafka. This enables Confluent REST Proxy clients to utilize the multi-tenant security features of the Kafka broker. For more information, see Confluent Security Plugins.
Eventually, the REST Proxy should be able to expose all of the functionality of the Java producers, consumers, and command-line tools. Here is the list of what is currently supported:
- Metadata - Most metadata about the cluster -- brokers, topics,
partitions, and configs -- can be read using
GETrequests for the corresponding URLs.
- Producers - Instead of exposing producer objects, the API accepts produce
requests targeted at specific topics or partitions and routes them all through
a small pool of producers.
- Producer configuration - Producer instances are shared, so configs cannot
be set on a per-request basis. However, you can adjust settings globally by
passing new producer settings in the REST Proxy configuration. For example,
you might pass in the
compression.typeoption to enable site-wide compression to reduce storage and network overhead.
- Producer configuration - Producer instances are shared, so configs cannot be set on a per-request basis. However, you can adjust settings globally by passing new producer settings in the REST Proxy configuration. For example, you might pass in the
- Consumers - The REST Proxy uses either the high level consumer (v1 api) or the
new 0.9 consumer (v2 api) to implement consumer-groups that can read from topics.
Consumers are stateful and therefore tied to specific REST Proxy instances. Offset
commit can be either automatic or explicitly requested by the user. Currently limited to
one thread per consumer; use multiple consumers for higher throughput.
- Consumer configuration - Although consumer instances are not shared, they do share the underlying server resources. Therefore, limited configuration options are exposed via the API. However, you can adjust settings globally by passing consumer settings in the REST Proxy configuration.
- Data Formats - The REST Proxy can read and write data using JSON, raw bytes encoded with base64 or using JSON-encoded Avro. With Avro, schemas are registered and validated against Schema Registry.
- REST Proxy Clusters and Load Balancing - The REST Proxy is designed to support multiple instances running together to spread load and can safely be run behind various load balancing mechanisms (e.g. round robin DNS, discovery services, load balancers) as long as instances are configured correctly.
- Simple Consumer - The high-level consumer should generally be preferred. However, it is occasionally useful to use low-level read operations, for example to retrieve messages at specific offsets.
Just as important, here's a list of features that aren't yet supported:
- Admin operations - We plan to expose these, but must do so carefully, with an eye toward security.
- Multi-topic Produce Requests - Currently each produce request may only address a single topic or topic-partition. Most use cases do not require multi-topic produce requests, they introduce additional complexity into the API, and clients can easily split data across multiple requests if necessary
- Most Producer/Consumer Overrides in Requests - Only a few key overrides are exposed in the API (but global overrides can be set by the administrator). The reason is two-fold. First, proxies are multi-tenant and therefore most user-requested overrides need additional restrictions to ensure they do not impact other users. Second, tying the API too much to the implementation restricts future API improvements; this is especially important with the new upcoming consumer implementation.
See the installation instructions for the Confluent Platform. Before starting the REST Proxy you must start Kafka and Schema Registry. The Confluent Platform quickstart explains how to start these services locally for testing.
Starting the Kafka REST Proxy service is simple once its dependencies are running:
# Start the REST Proxy. The default settings automatically work with the # default settings for local ZooKeeper and Kafka nodes. $ <path-to-confluent>/bin/kafka-rest-start etc/kafka-rest/kafka-rest.properties
If you installed Debian or RPM packages, you can simply run
as it will be on your
kafka-rest.properties file contains
configuration settings. The default configuration
included with the REST Proxy includes convenient defaults for a local testing setup
and should be modified for a production deployment. By default the server starts bound to port
8082, does not specify a unique instance ID (required to safely run multiple
proxies concurrently), and expects ZooKeeper to be available at
localhost:2181 and Schema Registry at
If you started the service in the background, you can use the following command to stop it:
To build a development version, you may need a development versions of common, rest-utils, and schema-registry. After installing these, you can build the Kafka REST Proxy with Maven. All the standard lifecycle phases work. During development, use
$ mvn compile
$ mvn test
to run the unit and integration tests, and
$ mvn exec:java
to run an instance of the proxy against a local Kafka cluster (using the default configuration included with Kafka).
To create a packaged version, optionally skipping the tests:
$ mvn package [-DskipTests]
This will produce a version ready for production in
target/kafka-rest-$VERSION-package containing a directory layout similar
to the packaged binary versions. You can also produce a standalone fat jar using the
$ mvn package -P standalone [-DskipTests]
target/kafka-rest-$VERSION-standalone.jar, which includes all the
dependencies as well.