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MQTT with Kafka: Supercharging IoT Data Integration

2023-08-21 20:58:49
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Illustration: © IoT For All

How Is MQTT Used with Kafka?

MQTT (Message Queuing Telemetry Transport) is a lightweight messaging protocol for efficient communication between devices in constrained networks. Apache Kafka is a distributed streaming platform. It is designed to handle large-scale, real-time data streaming and processing.

Kafka and MQTT are complementary technologies that enable end-to-end integration of IoT data. By integrating Kafka and MQTT, businesses can establish a robust IoT architecture that guarantees reliable connectivity and efficient data exchange between devices and IoT platforms. At the same time, it also facilitates high throughput real-time data processing and analysis throughout the entire IoT system.

There are many IoT use cases where integrating MQTT and Kafka provides significant value, such as Connected Cars and Telematics, Smart City Infrastructure, Industrial IoT Monitoring, Logistics Management, etc. In this blog post, we will explore the seamless integration of MQTT data with Kafka for the IoT Application.

Which IoT Challenges Can Kafka and MQTT Address?

When designing an IoT platform architecture, several challenges arise that need to be addressed:

  • Connectivity and network resilience: Critical IoT scenarios, such as Connected Cars, rely on network connectivity to transmit data to the platform. The architecture should be designed to handle intermittent connectivity, network latency, and varying network conditions.

  • Scaling: As the number of devices increases, the architecture must be scalable to handle the growing volume of data generated by IoT devices.

  • Message Throughput: IoT devices generate a vast amount of data in real time, including sensor readings, location information, and so on. The platform architecture must be capable of handling high message throughput to ensure that all data is efficiently collected, processed, and delivered to the appropriate components.

  • Data storage: IoT devices generate a continuous stream of data, which needs to be stored and managed effectively.

The Need to Integrate MQTT with Kafka in an IoT Architecture

While Kafka excels in its role as a reliable streaming data processing platform for facilitating data sharing between enterprise systems, certain limitations make it less ideal for IoT use cases:

  • Client complexity and resource intensiveness: Kafka clients are known for their complexity and resource requirements. This poses difficulties for smaller IoT devices with constrained resources, as running a Kafka client on such devices may be impractical or inefficient.

  • Topic scalability: Kafka has limitations in handling a large number of topics. This can be problematic for IoV deployments with extensive topic definition, as they may not seamlessly fit into Kafka’s architecture, especially in scenarios involving a significant number of devices and multiple topics in each device.

  • Unreliable connectivity: Kafka clients require a stable IP connection, which proves challenging for IoT devices operating over unreliable mobile networks. These networks can introduce intermittent connectivity issues, disrupting the consistent communication required by Kafka.

Integrating MQTT with Kafka can help address most of the limitations of Kafka in IoT device connectivity scenarios:

  • Direct addressing: MQTT supports load balancing, enabling IoT devices to connect to Kafka brokers indirectly through load balancers.

  • Topic scalability: MQTT is well-suited for handling many topics, making it an ideal candidate for IoT platform deployments with extensive topic design.

  • Reliable connectivity: MQTT is designed to operate over unreliable networks, making it a reliable messaging protocol for IoT devices and connections.

  • Lightweight client: MQTT clients are designed to be lightweight, making them more suitable for resource-constrained IoV devices.

Comparison of Viable MQTT-Kafka Integration Solutions

When integrating MQTT and Kafka in an IoT platform, several viable solutions are available. Each solution offers its own advantages and considerations. Let’s explore some of the popular MQTT + Kafka integration options:

EMQX Kafka Data Integration

EMQX is a popular MQTT broker that offers seamless integration with Kafka through its Kafka Data Integration feature. As a bridge between MQTT and Kafka, EMQX enables smooth communication between the two protocols.

This integration allows the creation of data bridges to Kafka in two roles: producer (sending messages to Kafka) and consumer (receiving messages from Kafka). EMQX allows users to establish data bridges in either of these roles. With its bi-directional data transmission capability, EMQX provides flexibility in architecture design. Additionally, it offers low latency and high throughput, ensuring efficient and reliable data-bridging operations.

Confluent MQTT Proxy

Confluent is the company behind Kafka. Its MQTT Proxy connects MQTT clients and Kafka brokers, allowing them to publish and subscribe to Kafka topics. This solution simplifies the integration process by abstracting the complexities of direct communication with Kafka brokers.

Currently, this solution is limited to supporting MQTT version 3.1.1, and the performance of MQTT client connections may influence the throughput.

Custom Development with Open-Source MQTT Broker and Kafka

With the use of an open-source MQTT Broker, users have the flexibility to develop their own bridge service that connects MQTT and Kafka. This bridge service can be built using an MQTT client to subscribe to data from the MQTT Broker and utilize the Kafka producer API to publish the data into Kafka.

This solution requires development and maintenance efforts, as well as significant work to ensure reliability and scalability.

Conclusion

The MQTT + Kafka architecture is well-suited for use cases that require real-time data collecting, scalability, reliability, and integration capabilities in IoT. It enables a seamless flow of data, efficient communication, and innovative use cases such as applications and services for the connected vehicle ecosystem. Hence, the combination of MQTT and Kafka is an ideal solution for seamless end-to-end integration of IoT architectures, spanning from the IoT device to the cloud and ensuring bi-directional communication.

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  • MQTT
  • Network and Protocols

  • MQTT
  • Network and Protocols

参考译文
MQTT与Kafka:为物联网数据集成注入强大动力# 示例输入与输出**输入**人工智能(AI)是计算机科学的一个分支,旨在开发表现出人类智能的软件或机器。这包括从经验中学习、理解自然语言、解决问题以及识别模式。**输出**人工智能(AI)是计算机科学的一个分支,旨在开发表现出人类智能的软件或机器。这包括从经验中学习、理解自然语言、解决问题以及识别模式。
插图:© IoT For All 如何将MQTT与Kafka结合使用?MQTT(Message Queuing Telemetry Transport)是一种轻量级消息协议,用于在资源受限的网络中实现设备间的高效通信。Apache Kafka 是一个分布式流处理平台,专为处理大规模实时数据流和处理而设计。Kafka 与 MQTT 是互补技术,可实现物联网数据的端到端集成。通过将 Kafka 与 MQTT 结合使用,企业可以构建一个强大的物联网架构,确保设备与物联网平台之间可靠的连接和高效的数据交换。同时,它还有助于在整个物联网系统中进行高吞吐量的实时数据处理和分析。在许多物联网应用场景中,MQTT 与 Kafka 的集成具有显著价值,例如车联网与远程信息处理、智慧城市基础设施、工业物联网监控、物流管理等。在本文中,我们将探讨MQTT数据与Kafka在物联网应用中的无缝集成。Kafka 与 MQTT 能解决哪些物联网挑战?在设计物联网平台架构时,会遇到一些需要解决的挑战:连接性和网络弹性:关键的物联网场景,如车联网,依赖于网络连接将数据传输到平台。架构应被设计为能够处理间歇性连接、网络延迟和变化的网络状况。可扩展性:随着设备数量的增加,架构必须具备可扩展性以处理来自物联网设备的不断增长的数据量。消息吞吐量:物联网设备实时生成大量数据,包括传感器读数、位置信息等。平台架构必须能够处理高消息吞吐量,以确保所有数据被有效收集、处理并传递到相应的组件。数据存储:物联网设备持续生成数据,这些数据需要有效存储和管理。在物联网架构中,将 MQTT 与 Kafka 集成的必要性:虽然 Kafka 在作为可靠的数据流处理平台方面表现优异,便于企业系统之间的数据共享,但它在某些方面存在限制,使其在物联网用例中不太理想:客户端的复杂性和资源密集性:Kafka 客户端以其复杂性和资源需求而著称。这使得资源受限的小型物联网设备难以高效运行 Kafka 客户端。主题可扩展性:Kafka 在处理大量主题方面存在限制。对于需要定义大量主题的物联网车辆部署,这可能会成为问题,因为它们可能无法无缝适应 Kafka 的架构,尤其是在涉及大量设备和每个设备多个主题的场景中。连接不可靠:Kafka 客户端需要稳定的 IP 连接,这对于在不可靠的移动网络上运行的物联网设备来说是一个挑战。这些网络可能会引发间歇性连接问题,从而中断 Kafka 所需的持续通信。将 MQTT 与 Kafka 集成可以帮助解决 Kafka 在物联网设备连接场景中的大部分限制:直接寻址:MQTT 支持负载均衡,使物联网设备能够通过负载均衡器间接连接到 Kafka 代理。主题可扩展性:MQTT 非常适合处理大量主题,因此是主题设计复杂的物联网平台部署的理想选择。可靠连接:MQTT 专为在不可靠网络上运行而设计,因此是物联网设备和连接的可靠消息协议。轻量级客户端:MQTT 客户端设计为轻量级,因此更适合资源受限的物联网车辆设备。MQTT 与 Kafka 可行集成方案比较:在物联网平台中集成 MQTT 与 Kafka 时,有几种可行的方案可供选择。每种方案都有自己的优势和需要考虑的因素。让我们看看一些流行的 MQTT + Kafka 集成方案:EMQX Kafka 数据集成:EMQX 是一个流行的 MQTT 代理,通过其 Kafka 数据集成功能可与 Kafka 无缝集成。作为 MQTT 与 Kafka 之间的桥梁,EMQX 使这两个协议之间能够顺畅通信。这种集成允许用户以两种角色创建连接到 Kafka 的数据桥接:生产者(向 Kafka 发送消息)和消费者(从 Kafka 接收消息)。EMQX 允许用户在任一角色中建立数据桥接。凭借其双向数据传输能力,EMQX 提供了架构设计的灵活性。此外,它还提供低延迟和高吞吐量,确保数据桥接操作的高效和可靠。Confluent MQTT 代理:Confluent 是 Kafka 的公司。它的 MQTT 代理连接 MQTT 客户端和 Kafka 代理,使它们能够发布和订阅 Kafka 主题。该方案通过抽象直接与 Kafka 代理通信的复杂性来简化集成过程。目前,该方案仅限于支持 MQTT 3.1.1 版本,MQTT 客户端连接的性能可能会对吞吐量产生影响。使用开源 MQTT 代理和 Kafka 进行定制开发:通过使用开源 MQTT 代理,用户可以灵活地开发自己的桥接服务,将 MQTT 与 Kafka 相连。该桥接服务可以使用 MQTT 客户端从 MQTT 代理中订阅数据,并使用 Kafka 生产者 API 将数据发布到 Kafka。此方案需要开发和维护工作,以及大量工作来确保其可靠性和可扩展性。结论:MQTT + Kafka 架构非常适合需要物联网中实时数据收集、可扩展性、可靠性和集成能力的用例。它能够实现数据的顺畅流动,高效通信,并支持诸如车联网生态系统等创新应用场景和服务。因此,MQTT 与 Kafka 的结合是物联网架构中端到端无缝集成的理想解决方案,涵盖从物联网设备到云的双向通信。推文分享分享电子邮件 MQTT 网络和协议 → MQTT 网络和协议
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