Kafka REST Proxy

The Kafka REST Proxy is part of Confluent Open Source and Confluent Enterprise distributions. The 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

Quickstart

Start by running the REST Proxy and the services it depends on: ZooKeeper, Kafka, and the Schema Registry. You can do this in one command with Confluent CLI:

$ confluent start kafka-rest

Each service reads its configuration from its property files under etc.

Note

To manually start each service in its own terminal, run instead:

$ bin/zookeeper-server-start ./etc/kafka/zookeeper.properties
$ bin/kafka-server-start ./etc/kafka/server.properties
$ bin/kafka-rest-start ./etc/kafka-rest/kafka-rest.properties

# optional, if you want to use Avro data format
$ bin/schema-registry-start ./etc/schema-registry/schema-registry.properties

See the Confluent Platform quickstart for a more detailed explanation of how to get these services up and running.

Produce and Consume JSON Messages

# Produce a message using JSON with the value '{ "foo": "bar" }' to the topic jsontest
$ curl -X POST -H "Content-Type: application/vnd.kafka.json.v2+json" \
      -H "Accept: application/vnd.kafka.v2+json" \
      --data '{"records":[{"value":{"foo":"bar"}}]}' "http://localhost:8082/topics/jsontest"
  {"offsets":[{"partition":0,"offset":0,"error_code":null,"error":null}],"key_schema_id":null,"value_schema_id":null}

# Create a consumer for JSON data, starting at the beginning of the topic's
# log and subscribe to a topic. Then consume some data using the base URL in the first response.
# Finally, close the consumer with a DELETE to make it leave the group and clean up
# its resources.
$ curl -X POST -H "Content-Type: application/vnd.kafka.v2+json" \
      --data '{"name": "my_consumer_instance", "format": "json", "auto.offset.reset": "earliest"}' \
      http://localhost:8082/consumers/my_json_consumer
  {"instance_id":"my_consumer_instance",
  "base_uri":"http://localhost:8082/consumers/my_json_consumer/instances/my_consumer_instance"}

$ curl -X POST -H "Content-Type: application/vnd.kafka.v2+json" --data '{"topics":["jsontest"]}' \
 http://localhost:8082/consumers/my_json_consumer/instances/my_consumer_instance/subscription
 # No content in response

$ curl -X GET -H "Accept: application/vnd.kafka.json.v2+json" \
      http://localhost:8082/consumers/my_json_consumer/instances/my_consumer_instance/records
  [{"key":null,"value":{"foo":"bar"},"partition":0,"offset":0,"topic":"jsontest"}]

$ curl -X DELETE -H "Content-Type: application/vnd.kafka.v2+json" \
      http://localhost:8082/consumers/my_json_consumer/instances/my_consumer_instance
  # No content in response

Produce and Consume Avro Messages

# Produce a message using Avro embedded data, including the schema which will
# be registered with the schema registry and used to validate and serialize
# before storing the data in Kafka
$ curl -X POST -H "Content-Type: application/vnd.kafka.avro.v2+json" \
      -H "Accept: application/vnd.kafka.v2+json" \
      --data '{"value_schema": "{\"type\": \"record\", \"name\": \"User\", \"fields\": [{\"name\": \"name\", \"type\": \"string\"}]}", "records": [{"value": {"name": "testUser"}}]}' \
      "http://localhost:8082/topics/avrotest"

# You should get the following response:
  {"offsets":[{"partition":0,"offset":0,"error_code":null,"error":null}],"key_schema_id":null,"value_schema_id":21}

# Produce a message with Avro key and value.
# Note that if you use Avro values you must also use Avro keys, but the schemas can differ

$ curl -X POST -H "Content-Type: application/vnd.kafka.avro.v2+json" \
      -H "Accept: application/vnd.kafka.v2+json" \
      --data '{"key_schema": "{\"name\":\"user_id\"  ,\"type\": \"int\"   }", "value_schema": "{\"type\": \"record\", \"name\": \"User\", \"fields\": [{\"name\": \"name\", \"type\": \"string\"}]}", "records": [{"key" : 1 , "value": {"name": "testUser"}}]}' \
      "http://localhost:8082/topics/avrokeytest2"

# You should get the following response:
{"offsets":[{"partition":0,"offset":0,"error_code":null,"error":null}],"key_schema_id":2,"value_schema_id":1}

# Create a consumer for Avro data, starting at the beginning of the topic's
# log and subscribe to a topic. Then consume some data from a topic, which is decoded, translated to
# JSON, and included in the response. The schema used for deserialization is
# fetched automatically from the schema registry. Finally, clean up.
$ curl -X POST  -H "Content-Type: application/vnd.kafka.v2+json" \
      --data '{"name": "my_consumer_instance", "format": "avro", "auto.offset.reset": "earliest"}' \
      http://localhost:8082/consumers/my_avro_consumer

  {"instance_id":"my_consumer_instance","base_uri":"http://localhost:8082/consumers/my_avro_consumer/instances/my_consumer_instance"}

$ curl -X POST -H "Content-Type: application/vnd.kafka.v2+json" --data '{"topics":["avrotest"]}' \
 http://localhost:8082/consumers/my_avro_consumer/instances/my_consumer_instance/subscription
 # No content in response

$ curl -X GET -H "Accept: application/vnd.kafka.avro.v2+json" \
      http://localhost:8082/consumers/my_avro_consumer/instances/my_consumer_instance/records
  [{"key":null,"value":{"name":"testUser"},"partition":0,"offset":1,"topic":"avrotest"}]


$ curl -X DELETE -H "Content-Type: application/vnd.kafka.v2+json" \
      http://localhost:8082/consumers/my_avro_consumer/instances/my_consumer_instance
# No content in response

Produce and Consume Binary Messages

# Produce a message using binary embedded data with value "Kafka" to the topic binarytest
$ curl -X POST -H "Content-Type: application/vnd.kafka.binary.v2+json" \
      -H "Accept: application/vnd.kafka.v2+json" \
      --data '{"records":[{"value":"S2Fma2E="}]}' "http://localhost:8082/topics/binarytest"
  {"offsets":[{"partition":0,"offset":0,"error_code":null,"error":null}],"key_schema_id":null,"value_schema_id":null}

# Create a consumer for binary data, starting at the beginning of the topic's
# log. Then consume some data from a topic using the base URL in the first response.
# Finally, close the consumer with a DELETE to make it leave the group and clean up
# its resources.
$ curl -X POST -H "Content-Type: application/vnd.kafka.v2+json" \
      --data '{"name": "my_consumer_instance", "format": "binary", "auto.offset.reset": "earliest"}' \
      http://localhost:8082/consumers/my_binary_consumer

  {"instance_id":"my_consumer_instance","base_uri":"http://localhost:8082/consumers/my_binary_consumer/instances/my_consumer_instance"}

$ curl -X POST -H "Content-Type: application/vnd.kafka.v2+json" --data '{"topics":["binarytest"]}' \
 http://localhost:8082/consumers/my_binary_consumer/instances/my_consumer_instance/subscription
 # No content in response

$ curl -X GET -H "Accept: application/vnd.kafka.binary.v2+json" \
      http://localhost:8082/consumers/my_binary_consumer/instances/my_consumer_instance/records

  [{"key":null,"value":"S2Fma2E=","partition":0,"offset":0,"topic":"binarytest"}]

$ curl -X DELETE -H "Content-Type: application/vnd.kafka.v2+json" \
      http://localhost:8082/consumers/my_binary_consumer/instances/my_consumer_instance
  # No content in response

Inspect Topic Metadata

# Get a list of topics
$ curl "http://localhost:8082/topics"
  ["__consumer_offsets","_schemas","avrotest","binarytest","jsontest"]

# Get info about one topic
$ curl "http://localhost:8082/topics/avrotest"
  {"name":"avrotest","configs":{},"partitions":[{"partition":0,"leader":0,"replicas":[{"broker":0,"leader":true,"in_sync":true}]}]}

# Get info about a topic's partitions
$ curl "http://localhost:8082/topics/avrotest/partitions"
  [{"partition":0,"leader":0,"replicas":[{"broker":0,"leader":true,"in_sync":true}]}]

Features

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 GET requests 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.type option to enable site-wide compression to reduce storage and network overhead.
  • 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 the 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.

Installation

See the installation instructions for the Confluent Platform. Before starting the REST Proxy you must start Kafka and the schema registry. The Confluent Platform quickstart explains how to start these services locally for testing.

Deployment

Starting the Kafka REST Proxy service is simple once its dependencies are running:

$ cd confluent-3.2.0/

# Start the REST Proxy. The default settings automatically work with the
# default settings for local ZooKeeper and Kafka nodes.
$ bin/kafka-rest-start etc/kafka-rest/kafka-rest.properties

If you installed Debian or RPM packages, you can simply run kafka-rest-start as it will be on your PATH. The 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 the Schema Registry at http://localhost:8081.

If you started the service in the background, you can use the following command to stop it:

$ bin/kafka-rest-stop

Development

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

to build,

$ 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 standalone profile:

$ mvn package -P standalone [-DskipTests]

generating target/kafka-rest-$VERSION-standalone.jar, which includes all the dependencies as well.

Requirements

  • Kafka 1.0.0-cp1
  • Required for Avro support: Schema Registry 3.0.0 recommended, 1.0 minimum

License

The REST Proxy is licensed under the Apache 2 license.