karapace. Your Apache Kafka® essentials in one tool.
An open-source implementation of Kafka REST and Schema Registry.
Karapace supports the storing of schemas in a central repository, which clients can access to serialize and deserialize messages. The schemas also maintain their own version histories and can be checked for compatibility between their different respective versions.
Karapace rest provides a RESTful interface to your Apache Kafka cluster, allowing you to perform tasks such as producing and consuming messages and perform administrative cluster work, all the while using the language of the WEB.
- Drop-in replacement both on pre-existing Schema Registry / Kafka Rest Proxy client and server-sides
- Moderate memory consumption
- Asynchronous architecture based on aiohttp
- Supports Avro, JSON Schema, and Protobuf
- Leader/Replica architecture for HA and load balancing
Karapace is compatible with Schema Registry 6.1.1 on API level. When a new version of SR is released, the goal is to support it in a reasonable time. Karapace supports all operations in the API.
There are some caveats regarding the schema normalization, and the error messages being the same as in Schema Registry, which cannot be always fully guaranteed.
To get you up and running with the latest build of Karapace, a docker image is available:
# Fetch the latest build from main branch docker pull ghcr.io/aiven-open/karapace:develop # Fetch the latest release docker pull ghcr.io/aiven-open/karapace:latest
Versions 3.7.1 and earlier are available from the ghcr.io/aiven registry:
docker pull ghcr.io/aiven/karapace:3.7.1
An example setup including configuration and Kafka connection is available as compose example:
docker compose -f ./container/compose.yml up -d
Then you should be able to reach two sets of endpoints:
- Karapace schema registry on http://localhost:8081
- Karapace REST on http://localhost:8082
Each configuration key can be overridden with an environment variable prefixed with KARAPACE_,
exception being configuration keys that actually start with the karapace string. For example, to
override the bootstrap_uri config value, one would use the environment variable
KARAPACE_BOOTSTRAP_URI. Here you can find an example configuration file to give you an idea
what you need to change.
Alternatively you can do a source install using:
pip install .
To register the first version of a schema under the subject "test" using Avro schema:
$ curl -X POST -H "Content-Type: application/vnd.schemaregistry.v1+json" \
--data '{"schema": "{\"type\": \"record\", \"name\": \"Obj\", \"fields\":[{\"name\": \"age\", \"type\": \"int\"}]}"}' \
http://localhost:8081/subjects/test-key/versions
{"id":1}
To register a version of a schema using JSON Schema, one needs to use schemaType property:
$ curl -X POST -H "Content-Type: application/vnd.schemaregistry.v1+json" \
--data '{"schemaType": "JSON", "schema": "{\"type\": \"object\",\"properties\":{\"age\":{\"type\": \"number\"}},\"additionalProperties\":true}"}' \
http://localhost:8081/subjects/test-key-json-schema/versions
{"id":2}
To list all subjects (including the one created just above):
$ curl -X GET http://localhost:8081/subjects ["test-key"]
To list all the versions of a given schema (including the one just created above):
$ curl -X GET http://localhost:8081/subjects/test-key/versions [1]
To fetch back the schema whose global id is 1 (i.e. the one registered above):
$ curl -X GET http://localhost:8081/schemas/ids/1
{"schema":"{\"fields\":[{\"name\":\"age\",\"type\":\"int\"}],\"name\":\"Obj\",\"type\":\"record\"}"}
To get the specific version 1 of the schema just registered run:
$ curl -X GET http://localhost:8081/subjects/test-key/versions/1
{"subject":"test-key","version":1,"id":1,"schema":"{\"fields\":[{\"name\":\"age\",\"type\":\"int\"}],\"name\":\"Obj\",\"type\":\"record\"}"}
To get the latest version of the schema under subject test-key run:
$ curl -X GET http://localhost:8081/subjects/test-key/versions/latest
{"subject":"test-key","version":1,"id":1,"schema":"{\"fields\":[{\"name\":\"age\",\"type\":\"int\"}],\"name\":\"Obj\",\"type\":\"record\"}"}
In order to delete version 10 of the schema registered under subject "test-key" (if it exists):
$ curl -X DELETE http://localhost:8081/subjects/test-key/versions/10 10
To Delete all versions of the schema registered under subject "test-key":
$ curl -X DELETE http://localhost:8081/subjects/test-key [1]
Test the compatibility of a schema with the latest schema under subject "test-key":
$ curl -X POST -H "Content-Type: application/vnd.schemaregistry.v1+json" \
--data '{"schema": "{\"type\": \"int\"}"}' \
http://localhost:8081/compatibility/subjects/test-key/versions/latest
{"is_compatible":true}
NOTE: if the subject's compatibility mode is transitive (BACKWARD_TRANSITIVE, FORWARD_TRANSITIVE or FULL_TRANSITIVE) then the compatibility is checked not only against the latest schema, but also against all previous schemas, as it would be done when trying to register the new schema through the subjects/<subject-key>/versions endpoint.
Get current global backwards compatibility setting value:
$ curl -X GET http://localhost:8081/config
{"compatibilityLevel":"BACKWARD"}
Change compatibility requirements for all subjects where it's not specifically defined otherwise:
$ curl -X PUT -H "Content-Type: application/vnd.schemaregistry.v1+json" \
--data '{"compatibility": "NONE"}' http://localhost:8081/config
{"compatibility":"NONE"}
Change compatibility requirement to FULL for the test-key subject:
$ curl -X PUT -H "Content-Type: application/vnd.schemaregistry.v1+json" \
--data '{"compatibility": "FULL"}' http://localhost:8081/config/test-key
{"compatibility":"FULL"}
List topics:
$ curl "http://localhost:8082/topics"
Get info for one particular topic:
$ curl "http://localhost:8082/topics/my_topic"
Produce a message backed up by schema registry:
$ curl -H "Content-Type: application/vnd.kafka.avro.v2+json" -X POST -d \
'{"value_schema": "{\"namespace\": \"example.avro\", \"type\": \"record\", \"name\": \"simple\", \"fields\": \
[{\"name\": \"name\", \"type\": \"string\"}]}", "records": [{"value": {"name": "name0"}}]}' http://localhost:8082/topics/my_topic
Create a consumer:
$ curl -X POST -H "Content-Type: application/vnd.kafka.v2+json" -H "Accept: application/vnd.kafka.v2+json" \
--data '{"name": "my_consumer", "format": "avro", "auto.offset.reset": "earliest"}' \
http://localhost:8082/consumers/avro_consumers
Subscribe to the topic we previously published to:
$ curl -X POST -H "Content-Type: application/vnd.kafka.v2+json" --data '{"topics":["my_topic"]}' \
http://localhost:8082/consumers/avro_consumers/instances/my_consumer/subscription
Consume previously published message:
$ curl -X GET -H "Accept: application/vnd.kafka.avro.v2+json" \ http://localhost:8082/consumers/avro_consumers/instances/my_consumer/records?timeout=1000
Commit offsets for a particular topic partition:
$ curl -X POST -H "Content-Type: application/vnd.kafka.v2+json" --data '{}' \
http://localhost:8082/consumers/avro_consumers/instances/my_consumer/offsets
Delete consumer:
$ curl -X DELETE -H "Accept: application/vnd.kafka.v2+json" \ http://localhost:8082/consumers/avro_consumers/instances/my_consumer
Karapace natively stores its data in a Kafka topic the name of which you can configure freely but which by default is called _schemas.
Karapace includes a tool to backing up and restoring data. To back up, run:
karapace_schema_backup get --config karapace.config.json --location schemas.log
You can also back up the data by using Kafka's Java console consumer:
./kafka-console-consumer.sh --bootstrap-server brokerhostname:9092 --topic _schemas --from-beginning --property print.key=true --timeout-ms 1000 1> schemas.log
Your backup can be restored with Karapace by running:
karapace_schema_backup restore --config karapace.config.json --location schemas.log
Or Kafka's Java console producer can be used to restore the data to a new Kafka cluster.
You can restore the data from the previous step by running:
./kafka-console-producer.sh --broker-list brokerhostname:9092 --topic _schemas --property parse.key=true < schemas.log
- 50 concurrent connections, 50.000 requests
| Format | Karapace | Confluent |
|---|---|---|
| Avro | 80.95 | 7.22 |
| Binary | 66.32 | 46.99 |
| Json | 60.36 | 53.7 |
- 15 concurrent connections, 50.000 requests
| Format | Karapace | Confluent |
|---|---|---|
| Avro | 25.05 | 18.14 |
| Binary | 21.35 | 15.85 |
| Json | 21.38 | 14.83 |
- 4 concurrent connections, 50.000 requests
| Format | Karapace | Confluent |
|---|---|---|
| Avro | 6.54 | 5.67 |
| Binary | 6.51 | 4.56 |
| Json | 6.86 | 5.32 |
Also, it appears there is quite a bit of variation on subsequent runs, especially for the lower numbers, so once more exact measurements are required, it's advised we increase the total req count to something like 500K
We'll focus on Avro serialization only after this round, as it's the more expensive one, plus it tests the entire stack
A basic push pull test , with 12 connections on the publisher process and 3 connections on the subscriber process, with a 10 minute duration. The publisher has the 100 ms timeout and 100 max_bytes parameters set on each request so both processes have work to do Heap size limit is set to 256M on Rest proxy
Ram consumption, different consumer count, over 300s
| Consumers | Karapace combined | Confluent rest |
|---|---|---|
| 1 | 47 | 200 |
| 10 | 55 | 400 |
| 20 | 83 | 530 |
Once installed, the karapace program should be in your path. It is the
main daemon process that should be run under a service manager such as
systemd to serve clients.
Keys to take special care are the ones needed to configure Kafka and advertised_hostname.
| Parameter | Default Value | Description |
|---|---|---|
http_request_max_size |
1048576 |
The maximum client HTTP request size. This value controls how large (POST) payloads are allowed. When configuration of karapace_rest is set to true and http_request_max_size is not set, Karapace configuration adapts the allowed client max size from the producer_max_request_size. In cases where automatically selected size is not enough the configuration can be overridden by setting a value in configuration. For schema registry operation set the client max size according to expected size of schema payloads if default size is not enough. |
advertised_protocol |
http |
The protocol being advertised to other instances of Karapace that are attached to the same Kafka group. |
advertised_hostname |
socket.gethostname() |
The hostname being advertised to other instances of Karapace that are attached to the same Kafka group. All nodes within the cluster need to have their advertised_hostname's set so that they can all reach each other. |
advertised_port |
None |
The port being advertised to other instances of Karapace that are attached to the same Kafka group. Fallbacks to port if not set. |
bootstrap_uri |
localhost:9092 |
The URI to the Kafka service where to store the schemas and to run coordination among the Karapace instances. |
sasl_bootstrap_uri |
None |
The URI to the Kafka service to use with the Kafka REST API when SASL authorization with REST is used. |
client_id |
sr-1 |
The client_id Karapace will use when coordinating with
other Karapace instances. The instance with the ID that sorts
first alphabetically is chosen as master from the services with
master_eligibility set to true. |
consumer_enable_autocommit |
True |
Enable auto commit on rest proxy consumers |
consumer_request_timeout_ms |
11000 |
Rest proxy consumers timeout for reads that do not limit the max bytes or provide their own timeout |
consumer_request_max_bytes |
67108864 |
Rest proxy consumers maximum bytes to be fetched per request |
consumer_idle_disconnect_timeout |
0 |
Disconnect idle consumers after timeout seconds if not used. Inactivity leads to consumer leaving consumer group and consumer state. 0 (default) means no auto-disconnect. |
fetch_min_bytes |
1 |
Rest proxy consumers minimum bytes to be fetched per request. |
group_id |
schema-registry |
The Kafka group name used for selecting a master service to coordinate the storing of Schemas. |
master_eligibility |
true |
Should the service instance be considered for promotion to the master service. One reason to turn this off would be to have an instance of Karapace running somewhere else for HA purposes but which you wouldn't want to automatically promote to master if the primary instances become unavailable. |
producer_compression_type |
None |
Type of compression to be used by rest proxy producers |
producer_acks |
1 |
Level of consistency desired by each producer message sent on the rest proxy. More on Kafka Producer |
producer_linger_ms |
0 |
Time to wait for grouping together requests. More on Kafka Producer |
producer_max_request_size |
1048576 |
The maximum size of a request in bytes. More on Kafka Producer configs |
security_protocol |
PLAINTEXT |
Default Kafka security protocol needed to communicate with the Kafka cluster. Other options is to use SSL for SSL client certificate authentication. |
sentry |
None |
Used to configure parameters for sentry integration (dsn, tags, ...). Setting the
environment variable SENTRY_DSN will also enable sentry integration. |
ssl_cafile |
/path/to/cafile |
Used when security_protocol is set to SSL, the path to the SSL CA certificate. |
ssl_certfile |
/path/to/certfile |
Used when security_protocol is set to SSL, the path to the SSL certfile. |
ssl_keyfile |
/path/to/keyfile |
Used when security_protocol is set to SSL, the path to the SSL keyfile. |
topic_name |
_schemas |
The name of the Kafka topic where to store the schemas. |
replication_factor |
1 |
The replication factor to be used with the schema topic. |
host |
127.0.0.1 |
Listening host for the Karapace server. Use an empty string to listen to all available networks. |
port |
8081 |
Listening port for the Karapace server. |
server_tls_certfile |
/path/to/certfile |
Filename to a certificate chain for the Karapace server in HTTPS mode. |
server_tls_keyfile |
/path/to/keyfile |
Filename to a private key for the Karapace server in HTTPS mode. |
registry_host |
127.0.0.1 |
Schema Registry host, used by Kafka Rest for schema related requests. If running both in the same process, it should be left to its default value |
registry_port |
8081 |
Schema Registry port, used by Kafka Rest for schema related requests. If running both in the same process, it should be left to its default value |
registry_user |
None |
Schema Registry user for authentication, used by Kafka Rest for schema related requests. |
registry_password |
None |
Schema Registry password for authentication, used by Kafka Rest for schema related requests. |
registry_ca |
/path/to/cafile |
Kafka Registry CA certificate, used by Kafka Rest for Avro related requests. If this is set, Kafka Rest will use HTTPS to connect to the registry. If running both in the same process, it should be left to its default value |
registry_authfile |
/path/to/authfile.json |
Filename to specify users and access control rules for Karapace Schema Registry. If this is set, Schema Segistry requires authentication for most of the endpoints and applies per endpoint authorization rules. |
rest_authorization |
false |
Use REST API's calling authorization credentials to invoke Kafka operations over SASL authentication of sasl_bootstrap_uri to delegate REST proxy authorization to Kafka. If false, then use configured common credentials for all Kafka connections of REST proxy operations. |
rest_base_uri |
None |
Publicly available URI of this instance advertised to the clients using stateful operations such as creating consumers. If not set, then construct URI using advertised_protocol, advertised_hostname, and advertised_port. |
metadata_max_age_ms |
60000 |
Period of time in milliseconds after Kafka metadata is force refreshed. |
karapace_rest |
true |
If the rest part of the app should be included in the starting process
At least one of this and karapace_registry options need to be enabled in order
for the service to start |
karapace_registry |
true |
If the registry part of the app should be included in the starting process
At least one of this and karapace_rest options need to be enabled in order
for the service to start |
protobuf_runtime_directory |
runtime |
Runtime directory for the protoc protobuf schema parser and code generator |
name_strategy |
topic_name |
Name strategy to use when storing schemas from the kafka rest proxy service. You can opt between topic_name , record_name and topic_record_name |
name_strategy_validation |
true |
If enabled, validate that given schema is registered under used name strategy when producing messages from Kafka Rest |
master_election_strategy |
lowest |
Decides on what basis the Karapace cluster master is chosen (only relevant in a multi node setup) |
kafka_schema_reader_strict_mode |
false |
If enabled, causes the Karapace schema-registry service to shutdown when there are invalid schema records in the _schemas topic |
kafka_retriable_errors_silenced |
true |
If enabled, kafka errors which can be retried or custom errors specififed for the service will not be raised, instead, a warning log is emitted. This will denoise issue tracking systems, i.e. sentry |
use_protobuf_formatter |
false |
If protobuf formatter should be used on protobuf schemas in order to normalize schemas. The formatter is used on top and independent of regular normalization and schemas will be persisted in a formatted state. |
log_handler |
stdout |
Select the log handler. Default is standard output. Alternative log handler is systemd. |
log_level |
DEBUG |
Logging level. Default level is debug. |
log_format |
%(name)-20s\t%(threadName)s\t%(levelname)-8s\t%(message)s |
Log format |
To enable HTTP Basic Authentication and user authorization the authorization configuration file is set in the main configuration key registry_authfile of the Karapace.
Karapace Schema Registry authorization file is an optional JSON configuration, which contains a list of authorized users in users and a list of access control rules in permissions.
Each user entry contains following attributes:
| Parameter | Description |
|---|---|
username |
A string |
algorithm |
One of supported hashing algorithms, scrypt, sha1, sha256, or sha512 |
salt |
Salt used for hashing the password |
password_hash |
Hash string of the password calculated using given algorithm and salt. |
Password hashing can be done using karapace_mkpasswd tool, if installed, or by invoking directly with python -m karapace.auth. The tool generates JSON entry with these fields.
$ karapace_mkpasswd -u user -a sha512 secret
{
"username": "user",
"algorithm": "sha512",
"salt": "iuLouaExTeg9ypqTxqP-dw",
"password_hash": "R6ghYSXdLGsq6hkQcg8wT4xkD4QToxBhlp7NerTnyB077M+mD2qiN7ZxXCDb4aE+5lExu5P11UpMPYAcVYxSQA=="
}
Each access control rule contains following attributes:
| Parameter | Description |
|---|---|
username |
A string to match against authenticated user |
operation |
Exact value of Read or Write. Write implies also read permissions. Write includes all mutable operations, e.g. deleting schema versions |
resource |
A regular expression used to match against accessed resource. |
Supported resource authorization:
| Resource | Description |
|---|---|
Config: |
Controls authorization to global schema registry configuration. |
Subject:<subject_name> |
Controls authorization to subject. The <subject_name> is a regular expression to match against the accessed subject. |
{
"users": [
{
"username": "admin",
"algorithm": "scrypt",
"salt": "<put salt for randomized hashing here>",
"password_hash": "<put hashed password here>"
},
{
"username": "plainuser",
"algorithm": "sha256",
"salt": "<put salt for randomized hashing here>",
"password_hash": "<put hashed password here>"
}
],
"permissions": [
{
"username": "admin",
"operation": "Write",
"resource": ".*"
},
{
"username": "plainuser",
"operation": "Read",
"resource": "Subject:general.*"
},
{
"username": "plainuser",
"operation": "Read",
"resource": "Config:"
}
]
}
The principal used by the Karapace Schema Registry has to have adequate access to the schemas topic (see the topic_name configuration option above).
In addition to what is required to access the topic, as described in the Confluent Schema Registry documentation, the unique, single-member consumer group
used by consumers in the schema registry needs Describe and Read permissions on the group.
These unique (per instance of the schema registry) consumer group names are prefixed by karapace-autogenerated-, followed by a random string.
The Karapace REST proxy supports passing OAuth2 credentials to the underlying Kafka service (defined in the sasl_bootstrap_uri configuration parameter). The JSON Web Token (JWT) is extracted from the Authorization HTTP header if the authorization scheme is Bearer,
eg. Authorization: Bearer $JWT. If a Bearer token is present, the Kafka clients managed by Karapace will be created to use the SASL OAUTHBEARER mechanism and the JWT will be passed along. The Karapace REST proxy does not verify the token, that is done by
the underlying Kafka service itself, if it's configured accordingly.
Authorization is also done by Kafka itself, typically using the sub claim (although it's configurable) from the JWT as the username, checked against the configured ACLs.
OAuth2 and Bearer token usage is dependent on the rest_authorization configuration parameter being true.
The REST proxy process manages a set of producer and consumer clients, which are identified by the OAuth2 JWT token. These are periodically cleaned up if they are idle, as well as before the JWT token expires (the clean up currently runs every 5 minutes).
Before a client refreshes its OAuth2 JWT token, it is expected to remove currently running consumers (eg. after committing their offsets) and producers using the current token.
If specified as a rest parameter for the POST /subjects/{subject}/versions?normalize=true endpoint and the POST subjects/{subject}?normalize=true endpoint,
Karapace uses a schema normalization algorithm to ensure that the schema is stored in a canonical form.
This normalization process is done so that schemas semantically equivalent are stored in the same way and should be considered equal.
Normalization is currently only supported for Protobuf schemas. Karapace does not support all normalization features implemented by Confluent Schema Registry. Currently the normalization process is done only for the ordering of the optional fields in the schema. Use the feature with the assumption that it will be extended in the future and so two schemas that are semantically equivalent could be considered different by the normalization process in different future versions of Karapace. The safe choice, when using a normalization process, is always to consider as different two schemas that are semantically equivalent while the problem is when two semantically different schemas are considered equivalent. In that view the future extension of the normalization process isn't considered a breaking change but rather an extension of the normalization process.
To unistall Karapace from the system you can follow the instructions described below. We would love to hear your reasons for uninstalling though. Please file an issue if you experience any problems or email us with feedback
If you installed Karapace via Docker, you would need to first stop and remove the images like described:
First obtain the container IDs related to Karapace, you should have one for the registry itself and another one for the rest interface:
docker ps | grep karapace
After this, you can stop each of the containers with:
docker stop <CONTAINER_ID>
If you don't need or want to have the Karapace images around you can now proceed to delete them using:
docker rm <CONTAINER_ID>
Karapace is installed pip install ., it can be uninstalled with the following pip command:
pip uninstall karapace
Execute make (GNU, usually gmake on BSD and Mac) to set up a venv
and install the required software for development. Use make unit-tests and
make integration-tests to execute the respective test suite, or simply
make test to execute both. You can set PYTEST_ARGS to customize the
execution (e.g. PYTEST_ARGS=--maxfail=1 make test).
Karapace currently depends on various system software to be installed. The installation of these is automated for some operation systems, but not all. At the time of writing Java, the Protobuf Compiler, and the Snappy shared library are required to work with Karapace. You need to install them manually if your operating system is not supported by the automatic installation scripts. Note that the scripts are going to ask before installing any of these on your system.
Note that Karapace requires a Protobuf Compiler older than 3.20.0, because
3.20.0 introduces various breaking changes. The tests are going to fail if the
Protobuf Compiler is newer than that. However, you can work around this locally
by running pip install --upgrade protobuf in your venv. We are going to fix
this soon.
Note that the integration tests are currently not working on Mac. You can use
Docker, just be sure to set VENV_DIR to a directory outside the working
directory so that the container is not overwriting files from the host (e.g.
docker run --env VENV_DIR=/tmp/venv ...).
Note that the runtime directory MUST exist and that Karapace is going to
fail if it does not. The runtime directory is also not cleaned between test
runs, and left over data might result in failing tests. Use the make test
targets that correctly clean the runtime directory without deleting it, but
keep this in mind whenever you are not using make (e.g. running tests from
your IDE).
Use pipx or brew to install pre-commit and use the global installation,
there is also no dependency on it.
Karapace is licensed under the Apache license, version 2.0. Full license text is
available in the LICENSE file.
Please note that the project explicitly does not require a CLA (Contributor License Agreement) from its contributors.
Bug reports and patches are very welcome, please post them as GitHub issues and pull requests at https://github.com/Aiven-Open/karapace . Any possible vulnerabilities or other serious issues should be reported directly to the maintainers <[email protected]>.
Apache Kafka is either a registered trademark or trademark of the Apache Software Foundation in the United States and/or other countries. Kafka Rest and Schema Registry are trademarks and property of their respective owners. All product and service names used in this page are for identification purposes only and do not imply endorsement.
Karapace was created by, and is maintained by, Aiven cloud data hub developers.
The schema storing part of Karapace loans heavily from the ideas of the earlier Schema Registry implementation by Confluent and thanks are in order to them for pioneering the concept.
Recent contributors are listed on the GitHub project page, https://github.com/Aiven-Open/karapace/graphs/contributors
Copyright ⓒ 2021 Aiven Ltd.