Kafkaesque

A must-have tool for your engineering team if you're using Kafka.

If your engineering team uses Apache Kafka, monitoring your cluster shouldn't mean juggling CLI commands, navigating multiple tools, or setting up heavyweight observability platforms. Getting visibility into brokers, topics, consumer groups, partition health, and consumer lag should be straightforward.

Kafkaesque brings everything together in one focused place. It's a lightweight, read-only Kafka monitoring dashboard, API, and CLI that gives developers and operators a clear picture of their Kafka cluster. Track cluster health, explore topic activity, investigate consumer lag, and configure Slack alerts to catch possible issues before they turn into production incidents. No message production, no Kafka resource modifications, and no unnecessary complexity.

What can you do with Kafkaesque?

• Cluster Health Dashboard: Get an overview of connection status, brokers, topics, partitions, and consumer groups.

• Broker Monitoring: Inspect broker IDs, rack placement, advertised listeners, and effective connection addresses.

• Topic Monitoring: Explore topics, partition counts, replication, and hourly message activity.

• Consumer Group Monitoring: Inspect consumer group states, active members, topic coverage, and aggregate lag.

• Partition-Level Lag: Identify lagging consumers and drill down into individual partition assignments.

• Slack Lag Alerts: Configure alerts using average or maximum partition lag thresholds.

• Alert Lifecycle Management: Receive notifications when lag breaches a threshold and optional follow-up notifications when it recovers.

• Kafka Security Support: Connect using plaintext, TLS, mutual TLS, SASL PLAIN, and SASL SCRAM authentication.

• REST API: Access Kafka monitoring information through an authenticated JSON API.

• Standalone CLI: Inspect Kafka clusters using text or JSON output, with watch mode for continuous monitoring.

Get started with Docker

Kafkaesque ships as a multi-platform Docker image for AMD64 and ARM64.

1. Pull the image

docker pull ghcr.io/nikhil25803/kafkaesque:latest

2. Generate an encryption key

openssl rand -base64 32

3. Create config.yaml

Replace the placeholders with your Kafka and PostgreSQL connection details.

kafka:
  bootstrap_server: kafka.example.com:9092

authentication:
  super_admin_username: admin
  super_admin_email: admin@example.com
  super_admin_password: CHANGE_ME_A1_
  super_admin_recovery: verify
  cookie_secure: false

database:
  url: postgres://kafkaesque:CHANGE_ME@postgres.example.com:5432/kafkaesque?sslmode=require

alerts:
  encryption_key: YOUR_GENERATED_KEY

api:
  host: 0.0.0.0
  port: 8085

4. Run Kafkaesque

docker run --rm --name kafkaesque \
  -p 8085:8085 \
  -v "$PWD/config.yaml:/config.yaml:ro" \
  ghcr.io/nikhil25803/kafkaesque:latest \
  serve --config /config.yaml

5. Open the dashboard

http://localhost:8085/ui

Sign in using the Super Admin credentials configured above and start exploring your Kafka cluster.

Note: You'll need a reachable Kafka cluster and a dedicated PostgreSQL 18+ database before starting the server. For local HTTP testing, cookie_secure: false is appropriate; use secure cookies behind HTTPS in production.

Built for developers who work with Kafka

Kafkaesque is built with Go, Apache Kafka, HTMX, and PostgreSQL. It runs as a single Go application with embedded UI assets and a non-root Docker container.

The guiding principle is simple: make Kafka monitoring accessible without making infrastructure more complicated.

GitHub: https://github.com/nikhil25803/kafkaesque

Project website: https://www.nikhilraj.space/projects/kafkaesque

Kafkaesque is open source, and contributions are always welcome!

Found a bug? Have an idea for a feature? Feel free to raise an issue, suggest improvements, or push fixes. Every contribution, big or small, makes a difference.

I'd love to see the community get involved. Let's collaborate, improve, and make Kafkaesque the best Kafka monitoring tool out there!

Happy monitoring! 🚀