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Kowl is a developer-friendly UI for managing your Kafka/Redpanda workloads. Kowl gives you a simple, interactive approach for gaining visibility into your topics, masking data, managing consumer groups, and exploring real-time data with time-travel debugging.

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Kowl – A UI for Data Streaming

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Kowl is a web application that helps you manage and debug your Kafka/Redpanda workloads effortlessly.

preview

Features

  • Message viewer: Explore your topics' messages in our message viewer through ad-hoc queries and dynamic filters. Find any message you want using JavaScript functions to filter messages. Supported encodings are: JSON, Avro, Protobuf, XML, MessagePack, Text and Binary (hex view). The used enconding (except Protobuf) is recognized automatically.
  • Consumer groups: List all your active consumer groups along with their active group offsets, edit group offsets (by group, topic or partition) or delete a consumer group.
  • Topic overview: Browse through the list of your Kafka topics, check their configuration, space usage, list all consumers who consume a single topic or watch partition details (such as low and high water marks, message count, ...), embed topic documentation from a git repository and more.
  • Cluster overview: List ACLs, available brokers, their space usage, rack id and other information to get a high level overview of your brokers in your cluster.
  • Schema Registry: List all Avro, Protobuf or JSON schemas within your schema registry.
  • Kafka connect: Manage connectors from multiple connect clusters, patch configs, view their current state or restart tasks.

A roadmap is maintained using milestones.

Getting Started

Prerequisites

  • Redpanda or any Kafka deployment (v1.0.0+) compatible
  • At least one OAuth app for SSO (Kowl business only)
  • Internet connectivity to validate license (Kowl business only)

Installing

We offer pre built docker images for Kowl (Business), a Helm chart and a Terraform module to make the installation as comfortable as possible for you. Please take a look at our dedicated Installation documentation.

Quick Start

Do you just want to test Kowl against one of your Kafka clusters without spending too much time on the test setup? Here are some docker commands that allow you to run it locally against an existing Redpanda or Kafka cluster:

Redpanda/Kafka is running locally

Since Kowl runs in its own container (which has its own network scope), we have to use host.docker.internal as a bootstrap server. That DNS resolves to the host system's ip address. However since the brokers send a list of all brokers' DNS when a client has connected, you have to make sure your advertised listener is connected accordingly, e.g.: PLAINTEXT://host.docker.internal:9092

docker run -p 8080:8080 -e KAFKA_BROKERS=host.docker.internal:9092 quay.io/cloudhut/kowl:master

Docker supports the --network=host option only on Linux. So Linux users use localhost:9092 as an advertised listener and use the host network namespace instead. Kowl will then be run as it would be executed on the host machine.

docker run --network=host -p 8080:8080 -e KAFKA_BROKERS=localhost:9092 quay.io/cloudhut/kowl:master

Kafka is running remotely

Protected via SASL_SSL and trusted certificates (e.g. Confluent Cloud):

docker run -p 8080:8080 -e KAFKA_BROKERS=pkc-4r000.europe-west1.gcp.confluent.cloud:9092 -e KAFKA_TLS_ENABLED=true -e KAFKA_SASL_ENABLED=true -e KAFKA_SASL_USERNAME=xxx -e KAFKA_SASL_PASSWORD=xxx quay.io/cloudhut/kowl:master

I don't have a running Kafka cluster to test against

We maintain a docker-compose file that launches Redpanda and Kowl: /docs/local.

Community

Slack is the main way the community interacts with one another in real time :)

GitHub Issues can be used for issues, questions and feature requests.

Code of conduct code of conduct for the community

Contributing docs

Sponsors

Companies that use Kowl

About

Kowl is a developer-friendly UI for managing your Kafka/Redpanda workloads. Kowl gives you a simple, interactive approach for gaining visibility into your topics, masking data, managing consumer groups, and exploring real-time data with time-travel debugging.

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