This post explores use cases and architectures for processing data in motion with Apache Kafka in Industrial IoT (IIoT) across verticals such as automotive, energy, steel manufacturing, oil&gas, cybersecurity, shipping, logistics. Use cases include predictive maintenance, quality assurance, track and track, real-time locating system (RTLS), asset tracking, customer 360, and more. Examples include BMW, Bosch, Baader, Intel, Porsche, and Devon.
Industrial IoT was a mess of monolithic and proprietary technologies in the last decades. Modbus, Siemens S7, SCADA, and similar “concepts” controlled the industry. Vendors locked in enterprises by intentionally building incompatible products without open interfaces. These systems still run on Windows XP or similar non-supported outdated operating systems and without security in mind.
Fortunately, this is completely changing. Apache Kafka and its ecosystem play a key role in the IIoT evolution. System integration and data processing get an open architecture with a scalable, reliable infrastructure.
I speak to customers in this industry every week across the globe. Very different challenges, use cases, and innovative ideas originate. I covered this topic a lot in the past, already.
Check out my other related blog posts for Kafka in IIoT and Manufacturing. Learn about use cases and architecture for deployments at the edge (i.e., outside the data center), the relation between Kafka and other IoT standards like MQTT or OPC-UA, and how to build a modern, open and scalable data historian.
I want to highlight one post as it is superimportant for any discussion around shop floors, PLCs, machines, robots, cars, and any other embedded systems: Kafka and other IT software are NOT hard real-time.
This post here “just” shares my latest presentation on this topic, including the slide deck and on-demand video recording. Before we get there, let’s summarize the current scenarios for Kafka in Industrial IoT in one concrete example.
Let’s take a look at one specific example. The following picture depicts the usage of event streaming in combination with other OT and IT technologies in the shipping industry:
This is an interesting example because it shows many challenges and requirements of many Industrial IoT real-world scenarios across verticals:
A unique value of Kafka is that you can use one single technology for scalable real-time messaging, storage and caching, continuous stateless and stateful data processing, and data integration with the OT and IT world. This is especially important at the edge where the hardware is constrained, and the network is limited. It is much easier to operate and much more cost-efficient to deploy one single infrastructure instead of glue together a best-of-breed like you often do in the cloud.
With this introduction, let’s now share the slide deck and video recording to talk about all these points in much more detail.
Here is the slide deck:
Click on the button to load the content from www.slideshare.net.
Here is the video recording:
Industrial IoT was a mess of monolithic and proprietary technologies in the last decades. Fortunately, Apache Kafka is completely changing many industrial environments. An open architecture with a scalable, reliable infrastructure changes how systems are integrated and how data is processed in the future.
What are your experiences and plans in IIoT projects? What use case and architecture did you implement? Let’s connect on LinkedIn and discuss it! Stay informed about new blog posts by subscribing to my newsletter.
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