When and Where to Adopt MQTT in Your Tech Stack

Introduction

In today’s world of connected devices, real-time insights, and edge computing, efficient communication protocols are more important than ever. Enter MQTT – Message Queuing Telemetry Transport – a lightweight, publish/subscribe protocol built for unreliable networks and resource-constrained devices.

Originally developed for oil pipeline telemetry, MQTT has become a go-to solution in IoT, computer vision, and real-time monitoring systems. If you’re an engineer working with distributed systems or device fleets, understanding when and where to use MQTT can make your architecture more responsive, efficient, and scalable.

When Is MQTT the Right Fit?

You should consider using MQTT when your application requires:

• Low bandwidth consumption: MQTT minimizes network overhead and is ideal for use over constrained or lossy networks (like mobile or LoRa).

• Real-time, event-driven messaging: Its asynchronous pub/sub model enables near-instant communication between devices and services.

• Battery and CPU efficiency: Its lightweight footprint makes it ideal for edge devices and sensors with limited resources.

• Scalable device-to-cloud or device-to-device communication: The decoupled nature of MQTT makes it easy to scale up with thousands of devices.

• Offline resilience: MQTT supports retained messages and Quality of Service (QoS) levels to ensure reliable delivery, even in intermittent conditions.

Where Does MQTT Fit in Your Tech Stack?

To apply MQTT effectively, it's important to know where it belongs in your architecture:

1. Device Layer (Edge)

Edge devices like sensors, microcontrollers, gateways, or AI cameras publish messages to the broker. These are usually the originators of telemetry, events, or alerts.

2. Messaging Layer (Broker)

The MQTT broker (e.g. Mosquitto, EMQX, HiveMQ, AWS IoT Core) is the backbone of the system, managing message routing between publishers and subscribers. It enables decoupling and one-to-many communication.

3. Application Layer (Subscribers)

Microservices, cloud functions, or real-time dashboards subscribe to topics of interest to act on incoming data – whether that’s triggering automation, logging metrics, or running AI inference.

4. Data & Analytics Layer

Messages from MQTT are often bridged to Kafka, databases, or time-series platforms (like InfluxDB) for storage, batch processing, or historical analysis.

5. Cloud Integration Layer

MQTT can be used to feed cloud platforms like AWS, Azure, or GCP, where it integrates with REST APIs, machine learning services, or enterprise workflows.

Think of MQTT as your real-time pipe for device communications, positioned between the edge and backend services.

MQTT vs HTTP vs Kafka – A Quick Comparison

• MQTT vs HTTP: HTTP is great for web apps but isn’t optimized for real-time, bi-directional communication. MQTT maintains persistent connections and is built for pushing data, making it better for event-driven systems.

• MQTT vs Kafka: Kafka is ideal for durable, high-volume event streams, but it’s heavyweight. MQTT, in contrast, is perfect for lightweight, frequent updates from edge devices. Many modern systems use MQTT at the edge and Kafka in the cloud to get the best of both.

Use Cases Across Industries

🚗 EV Charging Infrastructure

Each charging station can publish telemetry like energy usage, status, and fault alerts to a central broker. Cloud services subscribe to this data for monitoring, billing, or command/control operations. MQTT handles intermittent 4G/5G connections and low-latency updates with ease.

🎥 Edge Computer Vision

Cameras running real-time object detection publish events (e.g., “unauthorized entry detected”) via MQTT. Central systems can subscribe to take immediate action – sending alerts, activating gates, or storing snapshots. This decoupling allows scalable and modular deployment.

🌱 IoT Sensor Networks

In smart agriculture or smart buildings, thousands of sensors collect environmental data. MQTT lets them stream data efficiently to cloud dashboards or data lakes. Its small packet size and ability to queue messages during outages make it ideal for such deployments.

Conclusion

MQTT shines in environments where reliability, real-time messaging, and efficiency are non-negotiable – especially with edge devices and large-scale IoT systems.

If you’re building an architecture that involves devices, events, and cloud connectivity, MQTT fits right between the edge and your application or data layer, acting as the glue that keeps everything talking smoothly.

💡 Use MQTT when:

• Your devices are constrained (CPU/bandwidth/power)

• You need low-latency updates

• You want scalable, decoupled communication

• Your network is unreliable or cellular-based

• You need to unify your namespaces and share data between various systems

As systems grow more distributed and real-time by design, MQTT is no longer just a “nice-to-have” – it’s becoming foundational.