KafkaKeeper is a lightweight, production-ready Apache Kafka monitoring UI by DataTroops that delivers real-time operational visibility into Apache Kafka clusters with minimal overhead.
Provides a centralized, intuitive dashboard for easy monitoring.
Tracks key Kafka metrics, including:
Brokers
Topics
Partitions
Message production
Message consumption
Helps teams quickly identify bottlenecks and analyze performance trends.
Optimized for simplicity, security, and fast setup.
Free-to-use Apache Kafka monitoring solution for AWS.
Designed to avoid the complexity of heavyweight monitoring platforms.
Highlights
Cluster & Infrastructure Visibility
Multi-cluster management from a single dashboard
Broker health, leader distribution, and partition insights
Topic metadata and replication status
Topic, Message & Consumer Monitoring
Create and manage topics
Dynamic topic configuration updates
Partition and replication factor visibility
Browse messages by offset, timestamp, or partition
Support for JSON, plain text, and hex encoding
Live message streaming mode
Message filtering by key, value, headers, or timestamp
Consumer group state and lag visibility
Partition assignment tracking
Offset and rebalance insights
Security & Access Control
Safe operational boundaries for production clusters
Authentication and authorisation compatibility with Kafka security models
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This product is available free of charge. Free subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier for more details.
KafkaKeeper is offered free of software charges, so you pay only for the underlying AWS compute you select. You choose between two EC2 instance sizes billed by the hour: t3.medium or t3.micro. These are not feature tiers. Both run the same Kafka monitoring software. The difference is the compute capacity behind your deployment. The t3.medium gives you more processing resources per hour, while the t3.micro uses a smaller instance. Your hourly cost scales with the instance size you pick and how long you run it.
Top-of-mind questions for buyers
What compute resources come with each instance option, t3.medium and t3.micro?
Each option maps to an AWS EC2 instance type. The t3.medium provides more vCPU and memory per hour. The t3.micro is a smaller instance with less memory and compute. Both run the same monitoring software, so the choice reflects the compute capacity you need behind your deployment.
Am I charged when my KafkaKeeper instance is stopped or paused?
The software carries no charge, so you pay only for AWS compute. Hourly charges accrue while the instance runs. A stopped instance stops accruing compute-hour charges, though AWS storage fees for attached volumes may still apply. Billing follows your running instance-hours.
Does the price change based on how many Kafka clusters or brokers I monitor?
No. Billing is tied only to the EC2 instance size you run and how long it runs. The number of clusters, brokers, topics, or consumer groups you monitor does not add separate charges. Your cost depends solely on the instance type and running hours.
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An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
KafkaKeeper 1.3.1 is centered around delivering stronger access governance and streamlined user management for organizations operating large-scale Kafka environments.
This release introduces a comprehensive Role-Based Access Control (RBAC) framework, enabling administrators to define custom roles with granular, environment-scoped permissions across Kafka resources. A new Admin Portal provides a centralized experience for managing users, roles, and environments, while permission-aware navigation ensures users only access the resources relevant to their assigned roles.
Alongside RBAC, we've enhanced user management with email-based team invitations, flexible role assignment, configurable invitation expiry, and complete user lifecycle controls. Users can also request elevated permissions directly from the platform, making access management more efficient without compromising security.
Version 1.3.1 reinforces our commitment to building a secure, scalable, and enterprise-ready Kafka operations platform for modern event-driven systems.
Additional details
Usage instructions
Subscribe to the product and launch an EC2 instance using the provided AMI.
Choose an instance type (t3.micro or higher recommended).
Ensure the instance has a public IPv4 address.
Configure the security group using the recommended inbound rules by allowing:
TCP port 80 (HTTP traffic)
TCP port 3001 (Application traffic)
After the instance starts, wait about 2-3 minutes for all services to initialise. Then open your web browser and navigate to:
http://<EC2-Public-IP>
This loads the Kafka UI web interface.
The backend service, PostgreSQL database (Docker), and Nginx reverse proxy are preconfigured and start automatically at boot using systemd.
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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