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deviceinsight/kafkactl

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kafkactl

Table of Contents

A command-line interface for interaction with Apache Kafka

Features

  • command auto-completion for bash, zsh, fish shell including dynamic completion for e.g. topics or consumer groups.

  • support for avro schemas

  • Configuration of different contexts

  • directly access kafka clusters inside your kubernetes cluster

  • support for consuming and producing protobuf-encoded messages

Installation

You can install the pre-compiled binary or compile from source.

Install the pre-compiled binary

homebrew:

# install kafkactl
brew install kafkactl
# upgrade kafkactl
brew upgrade kafkactl

winget:

winget install kafkactl

deb/rpm:

Download the .deb or .rpm from the releases page and install with dpkg -i and rpm -i respectively.

yay (AUR)

There’s a kafkactl AUR package available for Arch. Install it with your AUR helper of choice (e.g. yay):

yay -S kafkactl

manually:

Download the pre-compiled binaries from the releases page and copy to the desired location.

Compiling from source

go install github.com/deviceinsight/kafkactl/v5@latest

NOTE: make sure that kafkactl is on PATH otherwise auto-completion won’t work.

Configuration

If no config file is found, a default config is generated in $HOME/.config/kafkactl/config.yml. This configuration is suitable to get started with a single node cluster on a local machine.

Create a config file

Create $HOME/.config/kafkactl/config.yml with a definition of contexts that should be available

contexts:
 default:
 brokers:
 - localhost:9092
 remote-cluster:
 brokers:
 - remote-cluster001:9092
 - remote-cluster002:9092
 - remote-cluster003:9092
 # optional: tls config
 tls:
 enabled: true
 ca: my-ca
 cert: my-cert
 certKey: my-key
 # set insecure to true to ignore all tls verification (defaults to false)
 insecure: false
 # optional: sasl support
 sasl:
 enabled: true
 username: admin
 password: admin
 # optional configure sasl mechanism as plaintext, scram-sha256, scram-sha512, oauth (defaults to plaintext)
 mechanism: oauth
 # optional configure sasl version as v0, v1 (defaults to not configured), Refer to: https://github.com/IBM/sarama/issues/3000#issuecomment-2415829478
 version: v0
 # optional tokenProvider configuration (only used for 'sasl.mechanism=oauth')
 tokenprovider:
 # plugin to use as token provider implementation (see plugin section)
 plugin: azure
 # optional: additional options passed to the plugin
 options:
 key: value
 # optional: access clusters running kubernetes
 kubernetes:
 enabled: false
 binary: kubectl #optional
 kubeConfig: ~/.kube/config #optional
 kubeContext: my-cluster
 namespace: my-namespace
 # optional: docker image to use (the tag of the image will be suffixed by `-scratch` or `-ubuntu` depending on command)
 image: private.registry.com/deviceinsight/kafkactl
 # optional: secret for private docker registry
 imagePullSecret: registry-secret
 # optional: secret containing tls certificates (e.g. ca.crt, cert.crt, key.key)
 tlsSecret: tls-secret
 # optional: Username to impersonate for the kubectl command
 asUser: user
 # optional: serviceAccount to use for the pod
 serviceAccount: my-service-account
 # optional: keep pod after exit (can be set to true for debugging)
 keepPod: true
 # optional: labels to add to the pod
 labels:
 key: value
 # optional: annotations to add to the pod
 annotations:
 key: value
 # optional: nodeSelector to add to the pod
 nodeSelector:
 key: value
 # optional: resource limits to add to the pod
 resources:
 requests:
 memory: "64Mi"
 cpu: "250m"
 limits:
 memory: "128Mi"
 cpu: "500m"
 # optional: affinity to add to the pod
 affinity:
 # note: other types of affinity also supported
 nodeAffinity:
 requiredDuringSchedulingIgnoredDuringExecution:
 nodeSelectorTerms:
 - matchExpressions:
 - key: "<key>"
 operator: "<operator>"
 values: [ "<value>" ]
 # optional: tolerations to add to the pod
 tolerations:
 - key: "<key>"
 operator: "<operator>"
 value: "<value>"
 effect: "<effect>"
 # optional: clientID config (defaults to kafkactl-{username})
 clientID: my-client-id
 # optional: kafkaVersion (defaults to 2.5.0)
 kafkaVersion: 1.1.1
 # optional: timeout for admin requests (defaults to 3s)
 requestTimeout: 10s
 # optional: avro configuration
 avro:
 # optional: configure codec for (de)serialization as standard,avro (defaults to standard)
 # see: https://github.com/deviceinsight/kafkactl/issues/123
 jsonCodec: avro
 # optional: schema registry
 schemaRegistry:
 url: localhost:8081
 # optional: timeout for requests (defaults to 5s)
 requestTimeout: 10s
 # optional: basic auth credentials
 username: admin
 password: admin
 # optional: tls config for avro
 tls:
 enabled: true
 ca: my-ca
 cert: my-cert
 certKey: my-key
 # set insecure to true to ignore all tls verification (defaults to false)
 insecure: false
 # optional: default protobuf messages search paths
 protobuf:
 importPaths:
 - "/usr/include/protobuf"
 protoFiles:
 - "someMessage.proto"
 - "otherMessage.proto"
 protosetFiles:
 - "/usr/include/protoset/other.protoset"
 # see: https://pkg.go.dev/google.golang.org/protobuf@v1.36.6/encoding/protojson#MarshalOptions
 marshalOptions:
 allowPartial: true
 useProtoNames: true
 useEnumNumbers: true
 emitUnpopulated: true
 emitDefaultValues: true
 producer:
 # optional: changes the default partitioner
 partitioner: "hash"
 # optional: changes default required acks in produce request
 # see: https://pkg.go.dev/github.com/IBM/sarama?utm_source=godoc#RequiredAcks
 requiredAcks: "WaitForAll"
 # optional: maximum permitted size of a message (defaults to 1000000)
 maxMessageBytes: 1000000
 consumer:
 # optional: isolationLevel (defaults to ReadCommitted)
 isolationLevel: ReadUncommitted

The config file location is resolved by

  1. checking for a provided commandline argument: --config-file=$PATH_TO_CONFIG

  2. evaluating the environment variable: export KAFKA_CTL_CONFIG=$PATH_TO_CONFIG

  3. checking for a project config file in the working directory (see Project config files)

  4. as default the config file is looked up from one of the following locations:

    • $HOME/.config/kafkactl/config.yml

    • $HOME/.kafkactl/config.yml

    • $APPDATA/kafkactl/config.yml

    • /etc/kafkactl/config.yml

Project config files

In addition to the config file locations above, kafkactl allows to create a config file on project level. A project config file is meant to be placed at the root level of a git repo and declares the kafka configuration for this repository/project.

In order to identify the config file as belonging to kafkactl the following names can be used:

  • kafkactl.yml

  • .kafkactl.yml

During initialization kafkactl starts from the current working directory and recursively looks for a project level config file. The recursive lookup ends at the boundary of a git repository (i.e. if a .git folder is found). This way, kafkactl can be used conveniently anywhere in the git repository.

Current context

The current context can be set via commandline argument --context, environment variable CURRENT_CONTEXT or it can be defined in a file.

If no current context is defined, the first context in the config file is used as current context. Additionally, in this case a file storing the current context is created.

The file is typically stored next to the config file and named current-context.yml. The location of the file can be overridden via environment variable KAFKA_CTL_WRITABLE_CONFIG.

Auto completion

bash

source <(kafkactl completion bash)

To load completions for each session, execute once: Linux:

kafkactl completion bash > /etc/bash_completion.d/kafkactl

MacOS:

kafkactl completion bash > /usr/local/etc/bash_completion.d/kafkactl

zsh

If shell completion is not already enabled in your environment, you will need to enable it. You can execute the following once:

echo "autoload -U compinit; compinit" >> ~/.zshrc

To load completions for each session, execute once:

kafkactl completion zsh > "${fpath[1]}/_kafkactl"

You will need to start a new shell for this setup to take effect.

Fish

kafkactl completion fish | source

To load completions for each session, execute once:

kafkactl completion fish > ~/.config/fish/completions/kafkactl.fish

Documentation

The documentation for all available commands can be found here:

Running in docker

Assuming your Kafka brokers are accessible under kafka1:9092 and kafka2:9092, you can list topics by running:

docker run --env BROKERS="kafka1:9092 kafka2:9092" deviceinsight/kafkactl:latest get topics

If a more elaborate config is needed, you can mount it as a volume:

docker run -v /absolute/path/to/config.yml:/etc/kafkactl/config.yml deviceinsight/kafkactl get topics

Running in Kubernetes

If your kafka cluster is not directly accessible from your machine, but it is accessible from a kubernetes cluster which in turn is accessible via kubectl from your machine you can configure kubernetes support:

contexts:
 kafka-cluster:
 brokers:
 - broker1:9092
 - broker2:9092
 kubernetes:
 enabled: true
 binary: kubectl #optional
 kubeContext: k8s-cluster
 namespace: k8s-namespace

Instead of directly talking to kafka brokers a kafkactl docker image is deployed as a pod into the kubernetes cluster, and the defined namespace. Standard-Input and Standard-Output are then wired between the pod and your shell running kafkactl.

There are two options:

  1. You can run kafkactl attach with your kubernetes cluster configured. This will use kubectl run to create a pod in the configured kubeContext/namespace which runs an image of kafkactl and gives you a bash into the container. Standard-in is piped to the pod and standard-out, standard-err directly to your shell. You even get auto-completion.

  2. You can run any other kafkactl command with your kubernetes cluster configured. Instead of directly querying the cluster a pod is deployed, and input/output are wired between pod and your shell.

The names of the brokers have to match the service names used to access kafka in your cluster. A command like this should give you this information:

kubectl get svc | grep kafka

a bash available. The second option uses a docker image build from scratch and should therefore be quicker. Which option is more suitable, will depend on your use-case.

Configuration via environment variables

Every key in the config.yml can be overwritten via environment variables. The corresponding environment variable for a key can be found by applying the following rules:

  1. replace . by _

  2. replace - by _

  3. write the key name in ALL CAPS

e.g. the key contexts.default.tls.certKey has the corresponding environment variable CONTEXTS_DEFAULT_TLS_CERTKEY.

NOTE: an array variable can be written using whitespace as delimiter. For example BROKERS can be provided as BROKERS="broker1:9092 broker2:9092 broker3:9092".

If environment variables for the default context should be set, the prefix CONTEXTS_DEFAULT_ can be omitted. So, instead of CONTEXTS_DEFAULT_TLS_CERTKEY one can also set TLS_CERTKEY. See root_test.go for more examples.

Plugins

kafkactl supports plugins to cope with specifics when using Kafka-compatible clusters available from cloud providers such as Azure or AWS.

At the moment, plugins can only be used to implement a tokenProvider for oauth authentication. In the future, plugins might implement additional commands to query data or configuration which is not part of the Kafka-API. One example would be Eventhub consumer groups/offsets for Azure.

See the plugin documentation for additional documentation and usage examples.

Available plugins:

Examples

Consuming messages

Consuming messages from a topic can be done with:

kafkactl consume my-topic

In order to consume starting from the oldest offset use:

kafkactl consume my-topic --from-beginning

The following example prints message key and timestamp as well as partition and offset in yaml format:

kafkactl consume my-topic --print-keys --print-timestamps -o yaml

To print partition in default output format use:

kafkactl consume my-topic --print-partitions

Headers of kafka messages can be printed with the parameter --print-headers e.g.:

kafkactl consume my-topic --print-headers -o yaml

If one is only interested in the last n messages this can be achieved by --tail e.g.:

kafkactl consume my-topic --tail=5

The consumer can be stopped when the latest offset is reached using --exit parameter e.g.:

kafkactl consume my-topic --from-beginning --exit

The consumer can compute the offset it starts from using a timestamp:

kafkactl consume my-topic --from-timestamp 1384216367189
kafkactl consume my-topic --from-timestamp 2014年04月26日T17:24:37.123Z
kafkactl consume my-topic --from-timestamp 2014年04月26日T17:24:37.123
kafkactl consume my-topic --from-timestamp 2009年08月12日T22:15:09Z
kafkactl consume my-topic --from-timestamp 2017年07月19日T03:21:51
kafkactl consume my-topic --from-timestamp 2013年04月01日T22:43
kafkactl consume my-topic --from-timestamp 2014年04月26日

The from-timestamp parameter supports different timestamp formats. It can either be a number representing the epoch milliseconds or a string with a timestamp in one of the supported date formats.

NOTE: --from-timestamp is not designed to schedule the beginning of consumer’s consumption. The offset corresponding to the timestamp is computed at the beginning of the process. So if you set it to a date in the future, the consumer will start from the latest offset.

The consumer can be stopped when the offset corresponding to a particular timestamp is reached:

kafkactl consume my-topic --from-timestamp 2017年07月19日T03:30:00 --to-timestamp 2017年07月19日T04:30:00

The to-timestamp parameter supports the same formats as from-timestamp.

NOTE: --to-timestamp is not designed to schedule the end of consumer’s consumption. The offset corresponding to the timestamp is computed at the beginning of the process. So if you set it to a date in the future, the consumer will stop at the current latest offset.

The following example prints keys in hex and values in base64:

kafkactl consume my-topic --print-keys --key-encoding=hex --value-encoding=base64

The consumer can convert protobuf messages to JSON in keys (optional) and values:

kafkactl consume my-topic --value-proto-type MyTopicValue --key-proto-type MyTopicKey --proto-file kafkamsg.proto

To join a consumer group and consume messages as a member of the group:

kafkactl consume my-topic --group my-consumer-group

If you want to limit the number of messages that will be read, specify --max-messages:

kafkactl consume my-topic --max-messages 2

Producing messages

Producing messages can be done in multiple ways. If we want to produce a message with key='my-key', value='my-value' to the topic my-topic this can be achieved with one of the following commands:

echo "my-key#my-value" | kafkactl produce my-topic --separator=#
echo "my-value" | kafkactl produce my-topic --key=my-key
kafkactl produce my-topic --key=my-key --value=my-value

If we have a file containing messages where each line contains key and value separated by #, the file can be used as input to produce messages to topic my-topic:

cat myfile | kafkactl produce my-topic --separator=#

The same can be accomplished without piping the file to stdin with the --file parameter:

kafkactl produce my-topic --separator=# --file=myfile

If the messages in the input file need to be split by a different delimiter than \n a custom line separator can be provided:

kafkactl produce my-topic --separator=# --lineSeparator=|| --file=myfile

NOTE: if the file was generated with kafkactl consume --print-keys --print-timestamps my-topic the produce command is able to detect the message timestamp in the input and will ignore it.

It is also possible to produce messages in json format:

# each line in myfile.json is expected to contain a json object with fields key, value
kafkactl produce my-topic --file=myfile.json --input-format=json
cat myfile.json | kafkactl produce my-topic --input-format=json

the number of messages produced per second can be controlled with the --rate parameter:

cat myfile | kafkactl produce my-topic --separator=# --rate=200

It is also possible to specify the partition to insert the message:

kafkactl produce my-topic --key=my-key --value=my-value --partition=2

Additionally, a different partitioning scheme can be used. When a key is provided the default partitioner uses the hash of the key to assign a partition. So the same key will end up in the same partition:

# the following 3 messages will all be inserted to the same partition
kafkactl produce my-topic --key=my-key --value=my-value
kafkactl produce my-topic --key=my-key --value=my-value
kafkactl produce my-topic --key=my-key --value=my-value
# the following 3 messages will probably be inserted to different partitions
kafkactl produce my-topic --key=my-key --value=my-value --partitioner=random
kafkactl produce my-topic --key=my-key --value=my-value --partitioner=random
kafkactl produce my-topic --key=my-key --value=my-value --partitioner=random

Message headers can also be written:

kafkactl produce my-topic --key=my-key --value=my-value --header key1:value1 --header key2:value\:2

The following example writes the key from base64 and value from hex:

kafkactl produce my-topic --key=dGVzdC1rZXk= --key-encoding=base64 --value=0000000000000000 --value-encoding=hex

You can control how many replica acknowledgements are needed for a response:

kafkactl produce my-topic --key=my-key --value=my-value --required-acks=WaitForAll

Producing null values (tombstone record) is also possible:

 kafkactl produce my-topic --null-value

Producing protobuf message converted from JSON:

kafkactl produce my-topic --key='{"keyField":123}' --key-proto-type MyKeyMessage --value='{"valueField":"value"}' --value-proto-type MyValueMessage --proto-file kafkamsg.proto

A more complex protobuf message converted from a multi-line JSON string can be produced using a file input with custom separators.

For example, if you have the following protobuf definition (complex.proto):

syntax = "proto3";
import "google/protobuf/timestamp.proto";
message ComplexMessage {
 CustomerInfo customer_info = 1;
 DeviceInfo device_info = 2;
}
message CustomerInfo {
 string customer_id = 1;
 string name = 2;
}
message DeviceInfo {
 string serial = 1;
 google.protobuf.Timestamp last_update = 2;
}

And you have the following file (complex-msg.txt) that contains the key and value of the message:

msg-key##
{
 "customer_info": {
 "customer_id": "12345",
 "name": "Bob"
 },
 "device_info": {
 "serial": "abcde",
 "last_update": "2024-03-02T07:01:02.000Z"
 }
}
+++

The command to produce the protobuf message using sample protobuf definition and input file would be:

kafkactl produce my-topic --value-proto-type=ComplexMessage --proto-file=complex.proto --lineSeparator='+++' --separator='##' --file=complex-msg.txt

Avro support

In order to enable avro support you just have to add the schema registry to your configuration:

contexts:
 localhost:
 schemaRegistry:
 url: localhost:8081

Producing to an avro topic

kafkactl will lookup the topic in the schema registry in order to determine if key or value needs to be avro encoded. If producing with the latest schemaVersion is sufficient, no additional configuration is needed an kafkactl handles this automatically.

If however one needs to produce an older schemaVersion this can be achieved by providing the parameters keySchemaVersion, valueSchemaVersion.

Example
# create a topic
kafkactl create topic avro_topic
# add a schema for the topic value
curl -X POST -H "Content-Type: application/vnd.schemaregistry.v1+json" \
--data '{"schema": "{\"type\": \"record\", \"name\": \"LongList\", \"fields\" : [{\"name\": \"next\", \"type\": [\"null\", \"LongList\"], \"default\": null}]}"}' \
http://localhost:8081/subjects/avro_topic-value/versions
# produce a message
kafkactl produce avro_topic --value {\"next\":{\"LongList\":{}}}
# consume the message
kafkactl consume avro_topic --from-beginning --print-schema -o yaml

Consuming from an avro topic

As for producing kafkactl will also lookup the topic in the schema registry to determine if key or value needs to be decoded with an avro schema.

The consume command handles this automatically and no configuration is needed.

An additional parameter print-schema can be provided to display the schema used for decoding.

Protobuf support

kafkactl can consume and produce protobuf-encoded messages. In order to enable protobuf serialization/deserialization you should add flag --value-proto-type and optionally --key-proto-type (if keys encoded in protobuf format) with type name. Protobuf-encoded messages are mapped with pbjson.

kafkactl will search messages in following order:

  1. Protoset files specified in --protoset-file flag

  2. Protoset files specified in context.protobuf.protosetFiles config value

  3. Proto files specified in --proto-file flag

  4. Proto files specified in context.protobuf.protoFiles config value

Proto files may require some dependencies in import sections. To specify additional lookup paths use --proto-import-path flag or context.protobuf.importPaths config value.

If provided message types was not found kafkactl will return error.

Note that if you want to use raw proto files protoc installation don’t need to be installed.

Also note that protoset files must be compiled with included imports:

protoc -o kafkamsg.protoset --include_imports kafkamsg.proto

Example

Assume you have following proto schema in kafkamsg.proto:

syntax = "proto3";
import "google/protobuf/timestamp.proto";
message TopicMessage {
 google.protobuf.Timestamp produced_at = 1;
 int64 num = 2;
}
message TopicKey {
 float fvalue = 1;
}

"well-known" google/protobuf types are included so no additional proto files needed.

To produce message run

kafkactl produce <topic> --key '{"fvalue":1.2}' --key-proto-type TopicKey --value '{"producedAt":"2021-12-01T14:10:12Z","num":"1"}' --value-proto-type TopicValue --proto-file kafkamsg.proto

or with protoset

kafkactl produce <topic> --key '{"fvalue":1.2}' --key-proto-type TopicKey --value '{"producedAt":"2021-12-01T14:10:12Z","num":"1"}' --value-proto-type TopicValue --protoset-file kafkamsg.protoset

To consume messages run

kafkactl consume <topic> --key-proto-type TopicKey --value-proto-type TopicValue --proto-file kafkamsg.proto

or with protoset

kafkactl consume <topic> --key-proto-type TopicKey --value-proto-type TopicValue --protoset-file kafkamsg.protoset

Topic management

List topics

In order to get a list of topics the get topics command can be used:

kafkactl get topics
kafkactl list topics

Describe topic

A detailed description of a topic can be obtained with describe topic:

kafkactl describe topic my-topic

Per default only overwritten config entries are printed. To print all config entries including defaults use:

kafkactl describe topic my-topic --all-configs

To print only partition details of partitions with messages use:

kafkactl describe topic my-topic --skip-empty

Create topic

The create topic allows you to create one or multiple topics.

Basic usage:

kafkactl create topic my-topic

The partition count can be specified with:

kafkactl create topic my-topic --partitions 32

The replication factor can be specified with:

kafkactl create topic my-topic --replication-factor 3

Configs can also be provided:

kafkactl create topic my-topic --config retention.ms=3600000 --config=cleanup.policy=compact

The topic configuration can also be taken from an existing topic using the following:

kafkactl describe topic my-topic -o json > my-topic-config.json
kafkactl create topic my-topic-clone --file my-topic-config.json

Altering topics

Using the alter topic command allows you to change the partition count, replication factor and topic-level configurations of an existing topic.

The partition count can be increased with:

kafkactl alter topic my-topic --partitions 32

The replication factor can be altered with:

kafkactl alter topic my-topic --replication-factor 2

broker balanced. If you need more control over the assigned replicas use alter partition directly.

The topic configs can be edited by supplying key value pairs as follows:

kafkactl alter topic my-topic --config retention.ms=3600000 --config cleanup.policy=compact

Altering partitions

The assigned replicas of a partition can directly be altered with:

# set brokers 102,103 as replicas for partition 3 of topic my-topic
kafkactl alter partition my-topic 3 -r 102,103

Clone topic

New topic may be created from existing topic as follows:

kafkactl clone topic source-topic target-topic

Source topic must exist, target topic must not exist. kafkactl clones partitions count, replication factor and config entries.

Delete Records from a topics

Command to be used to delete records from partition, which have an offset smaller than the provided offset.

# delete records with offset < 123 from partition 0 and offset < 456 from partition 1
kafkactl delete records my-topic --offset 0=123 --offset 1=456

Consumer group management

List Consumer groups

In order to get a list of consumer groups the get consumer-groups command can be used:

# all available consumer groups
kafkactl get consumer-groups
# only consumer groups for a single topic
kafkactl get consumer-groups --topic my-topic
# using command alias
kafkactl get cg

To get detailed information about the consumer group use describe consumer-group. If the parameter --partitions is provided details will be printed for each partition otherwise the partitions are aggregated to the clients.

Describe Consumer group

# describe a consumer group
kafkactl describe consumer-group my-group
# show partition details only for partitions with lag
kafkactl describe consumer-group my-group --only-with-lag
# show details only for a single topic
kafkactl describe consumer-group my-group --topic my-topic
# using command alias
kafkactl describe cg my-group

Create consumer groups

A consumer-group can be created as follows:

# create group with offset for all partitions set to oldest
kafkactl create consumer-group my-group --topic my-topic --oldest
# create group with offset for all partitions set to newest
kafkactl create consumer-group my-group --topic my-topic --newest
# create group with offset for a single partition set to specific offset
kafkactl create consumer-group my-group --topic my-topic --partition 5 --offset 100
# create group for multiple topics with offset for all partitions set to oldest
kafkactl create consumer-group my-group --topic my-topic-a --topic my-topic-b --oldest

Clone consumer group

A consumer group may be created as clone of another consumer group as follows:

kafkactl clone consumer-group source-group target-group

Source group must exist and have committed offsets. Target group must not exist or don’t have committed offsets. kafkactl clones topic assignment and partition offsets.

Reset consumer group offsets

in order to ensure the reset does what it is expected, per default only the results are printed without actually executing it. Use the additional parameter --execute to perform the reset.

# reset offset of for all partitions to oldest offset
kafkactl reset offset my-group --topic my-topic --oldest
# reset offset of for all partitions to newest offset
kafkactl reset offset my-group --topic my-topic --newest
# reset offset for a single partition to specific offset
kafkactl reset offset my-group --topic my-topic --partition 5 --offset 100
# reset offset to newest for all topics in the group
kafkactl reset offset my-group --all-topics --newest
# reset offset of for all partitions on multiple topics to oldest offset
kafkactl reset offset my-group --topic my-topic-a --topic my-topic-b --oldest
# reset offset to offset at a given timestamp(epoch)/datetime
kafkactl reset offset my-group --topic my-topic-a --to-datetime 2014年04月26日T17:24:37.123Z
# reset offset to offset at a given timestamp(epoch)/datetime
kafkactl reset offset my-group --topic my-topic-a --to-datetime 1697726906352

Delete consumer group offsets

In order to delete a consumer group offset use delete offset

# delete offset for all partitions of topic my-topic
kafkactl delete offset my-group --topic my-topic
# delete offset for partition 1 of topic my-topic
kafkactl delete offset my-group --topic my-topic --partition 1

Delete consumer groups

In order to delete a consumer group or a list of consumer groups use delete consumer-group

# delete consumer group my-group
kafkactl delete consumer-group my-group

ACL Management

Available ACL operations are documented here.

Create a new ACL

# create an acl that allows topic read for a user 'consumer'
kafkactl create acl --topic my-topic --operation read --principal User:consumer --allow
# create an acl that denies topic write for a user 'consumer' coming from a specific host
kafkactl create acl --topic my-topic --operation write --host 1.2.3.4 --principal User:consumer --deny
# allow multiple operations
kafkactl create acl --topic my-topic --operation read --operation describe --principal User:consumer --allow
# allow on all topics with prefix common prefix
kafkactl create acl --topic my-prefix --pattern prefixed --operation read --principal User:consumer --allow

List ACLs

# list all acl
kafkactl get acl
# list all acl (alias command)
kafkactl get access-control-list
# filter only topic resources
kafkactl get acl --topics
# filter only consumer group resources with operation read
kafkactl get acl --groups --operation read
# filter specific topic and user
kafkactl get acl --resource-name my-topic --principal User:myUser
# filter specific topic and host
kafkactl get acl --resource-name my-topic --host my-host

Delete ACLs

# delete all topic read acls
kafkactl delete acl --topics --operation read --pattern any
# delete all topic acls for any operation
kafkactl delete acl --topics --operation any --pattern any
# delete all cluster acls for any operation
kafkactl delete acl --cluster --operation any --pattern any
# delete all consumer-group acls with operation describe, patternType prefixed and permissionType allow
kafkactl delete acl --groups --operation describe --pattern prefixed --allow
# delete all topic acls for a principal
kafkactl delete acl --topics --operation any --pattern any --prinicipal User:myUser
# delete all topic acls for a host
kafkactl delete acl --topics --operation any --pattern any --host my-host

Broker Management

Getting Brokers

To get the list of brokers of a kafka cluster use get brokers

# get the list of brokers
kafkactl get brokers

Describe Broker

To view configs for a single broker use describe broker

# describe broker
kafkactl describe broker 1

Per default only dynamic configs are shown. To view all configs use --all-configs

kafkactl describe broker 1 --all-configs

Additionally, only default configs can be shown with:

kafkactl describe broker default

Altering brokers

Using the alter broker command allows you to change dynamic broker configurations for individual brokers or cluster-wide defaults.

To alter a configuration for a specific broker:

kafkactl alter broker 101 --config background.threads=8

To alter a cluster-wide default configuration (affects brokers without individual overrides):

kafkactl alter broker default --config background.threads=8

Multiple configurations can be altered simultaneously:

kafkactl alter broker 101 --config background.threads=8 --config log.cleaner.threads=2

SCRAM User Management

kafkactl provides comprehensive SCRAM (Salted Challenge Response Authentication Mechanism) user management capabilities for Kafka clusters that support SCRAM authentication. This allows you to create, modify, and manage user credentials directly through kafkactl.

Requirements

  • Kafka 2.7.0+ (for SCRAM user management APIs)

  • Admin privileges on the Kafka cluster

  • SCRAM-enabled listeners configured on Kafka brokers

Supported Mechanisms

  • SCRAM-SHA-256 (default)

  • SCRAM-SHA-512

Create SCRAM Users

Create a new SCRAM user with default settings:

# Create user with SCRAM-SHA-256 (default mechanism)
kafkactl create user myuser --password mypassword
# Create user with specific mechanism
kafkactl create user myuser --password mypassword --mechanism SCRAM-SHA-512
# Create user with custom iterations (default: 4096)
kafkactl create user myuser --password mypassword --iterations 8192
# Create user with custom base64-encoded salt
kafkactl create user myuser --password mypassword --salt "c2FsdA=="

Alter SCRAM Users

Update existing user credentials:

# Update user password (keeps existing mechanism)
kafkactl alter user myuser --password newpassword
# Update user with different mechanism
kafkactl alter user myuser --password newpassword --mechanism SCRAM-SHA-512
# Update with custom iterations
kafkactl alter user myuser --password newpassword --iterations 16384

Delete SCRAM Users

Remove SCRAM credentials by mechanism:

# Delete SCRAM-SHA-256 credentials (default)
kafkactl delete user myuser --mechanism SCRAM-SHA-256
# Delete SCRAM-SHA-512 credentials
kafkactl delete user myuser --mechanism SCRAM-SHA-512
# Note: A user may have multiple mechanisms, delete each separately

List SCRAM Users

Get all SCRAM users and their mechanisms:

# List all users (table format)
kafkactl get users
# List users in JSON format
kafkactl get users -o json
# List users in YAML format
kafkactl get users -o yaml

Describe SCRAM User

Get detailed information about a specific user:

# Describe user (table format)
kafkactl describe user myuser
# Describe user in JSON format
kafkactl describe user myuser -o json
# Describe user in YAML format
kafkactl describe user myuser -o yaml

Security Considerations

  • Salt Generation: kafkactl automatically generates cryptographically secure random salts unless custom salts are provided

  • Password Security: Passwords are transmitted securely to Kafka and never stored by kafkactl

  • Mechanism Support: Users can have credentials for multiple SCRAM mechanisms simultaneously

  • Admin Privileges: SCRAM user management requires admin-level access to the Kafka cluster

Multi-Mechanism Users

A single user can have credentials for multiple SCRAM mechanisms:

# Create user with SCRAM-SHA-256
kafkactl create user myuser --password mypassword --mechanism SCRAM-SHA-256
# Add SCRAM-SHA-512 credentials to the same user
kafkactl create user myuser --password mypassword --mechanism SCRAM-SHA-512
# User now has both mechanisms
kafkactl describe user myuser

Development

In order to see linter errors before commit, add the following pre-commit hook:

pip install --user pre-commit
pre-commit install

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