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IoT Ingest & Control with Zilla

Seamlessly connect IoT clients to Apache Kafka at scale

Streamline your IoT deployment by turning Kafka into a fully-fledged MQTT broker with Zilla. Enable your MQTT clients to directly consume and produce Kafka data streams without any coding, integration pipelines or dedicated MQTT brokers.

Why IoT Needs Kafka & Zilla

MQTT is a data transport protocol that is the de-facto standard for IoT. It is lightweight, scalable, and resilient, but it is not designed for data integration and processing — Apache Kafka though, is! Zilla brings these two technologies together enabling business value to be extracted in near real-time from large volumes of IoT data.

MSK public access use cases
Data Integration

Apache Kafka can distribute large volumes of data across a range of applications and services. With Kafka, IoT data can be made readily available to microservices, databases and analytics platforms.

Stream Processing

Apache Kafka has a rich ecosystem of stream processing solutions. When IoT data lands in Kafka, it can be processed, enriched, and propagated through data streaming pipelines powered by Kafka Streams, ksqlDB, Apache Flink, etc.

Data Governace

Ensuring safe and proper use of business data is critical for upholding consistent security policies and complying with regulations. Publishing IoT data streams into Kafka enables the use of data governance tools and practices designed specifically for streaming.

Unified Analytics

Kafka can tie together IoT data with both historical and real-time data from across applications and services. This in turn supports a centralized analytics plane that can span an entire deployment.

Apache Kafka can distribute large volumes of data across a range of applications and services. With Kafka, IoT data can be made readily available to microservices, databases and analytics platforms.

Apache Kafka has a rich ecosystem of stream processing solutions. When IoT data lands in Kafka, it can be processed, enriched, and propagated through data streaming pipelines powered by Kafka Streams, ksqlDB, Apache Flink, etc.

Ensuring safe and proper use of business data is critical for upholding consistent security policies and complying with regulations. Publishing IoT data streams into Kafka enables the use of data governance tools and practices designed specifically for streaming.

Kafka can tie together IoT data with both historical and real-time data from across applications and services. This in turn supports a centralized analytics plane that can span an entire deployment.

Reference Architecture

No MQTT broker. No Kafka Connect. No Custom Code.

Zilla is a multi-protocol edge and service proxy that can mediate between MQTT and Kafka wire protocols. When deployed in front of Kafka, Zilla persists MQTT messages and client state across pre-configured Kafka topics. Once theses messages are in Kafka, they become readily available to Kafka clients, consumers, and stream processing pipelines. Zilla works bi-directionally, so data can also be forwarded from Kafka producers back to MQTT clients.

Zilla is stateless, therefore easy to scale. It can be deployed behind a load balancer and run as as a standalone process or as part of a Kubernetes cluster. Zilla also handles connection offloading ensuring that Kafka is never directly exposed to an IoT-scale number of clients.

For observability, Zilla exposes metrics via OpenTelemetry, while message validation is supported via AsyncAPI and Schema Registry.

Feature Highlights

Kafka Native
Zilla natively supports the MQTT and Kafka wire protocols and uses advanced protocol mediation to integrate the two. No client libraries, coding, or Kafka Connect required.
MQTT Native (v3.1.1 & v5.0)
Full support for MQTT publishing and subscribing to Kafka with features such as QOS 0/1/2, Last Will and Testament, Retained Messages, etc. No MQTT broker required.
Stateless Design
Zilla is stateless and easily auto-scales on Kubernetes.
Observability & Logging
Zilla supports OpenTelemetry for exporting metrics and logs. Prometheus metrics and Stdout logging are also available.
Schema Registry
Zilla integrates with Karapace and Schema Registry for Kafka data governance.
AsyncAPI
The AsyncAPI specification can be used for both for Zilla configuration and for MQTT message validation.

How Zilla Compares

While different ways exist of interfacing MQTT clients to Kafka, they are either functionally compromised, operationally compex, or both!

    Confluent MQTT Proxy
    HiveMQ
    Waterstream
    Kafka Connect
    No MQTT Broker Required
    MQTT 
    Publish
    MQTT 
    Subscribe
    AsyncAPI 
    Support
    Open
    Source

    Ready to Get Started?

    Zilla is available in open source and as a partner-certified, commercially supported offering.

    Recommended Resources

    API-First Kafka Integration
    Maximized
    Kafka Investment
    Kafka's performance & resilience benefits extended across the application stack.
    Offloaded
    DevOps
    Heavy Kafka integration middleware replaced by a single, stateless API layer.
    Increased Developer Agility
    Developers across teams accessing event-streams via their own APIs of choice.
    Streamlined
    Security Footprint
    Centralized authorization & authentication of all non-Kafka clients.
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