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Top 5 Apache Kafka Use Cases for 2022

Apache Kafka and Event Streaming are two of the most relevant buzzwords in tech these days. Do you wonder about my predicted top 5 event streaming architectures and use cases for 2022 to set data in motion? Check out the following presentation and learn about the Kappa architecture, hyper-personalized omnichannel, multi-cloud deployments, edge analytics, and real-time cybersecurity. 

Some followers might notice that I did the same presentation a year ago about the top 5 event streaming use cases for 2021. My predictions for 2022 partly overlap with this session. That's fine. It shows that event streaming with Apache Kafka is a journey and evolution to set data in motion.

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Streaming Machine Learning With Kafka-Native Model Server

Apache Kafka became the de facto standard for event streaming across the globe and industries. Machine Learning (ML) includes model training on historical data and model deployment for scoring and predictions. While training is mostly batch, scoring usually requires real-time capabilities at scale and reliability. Apache Kafka plays a key role in modern machine learning infrastructures. The next-generation architecture leverages a Kafka-native streaming model server instead of RPC (HTTP/gRPC) calls:

This blog post explores the architectures and trade-offs between three options for model deployment with Kafka: Embedded model into the Kafka application, model server and RPC, model server, and Kafka-native communication.

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KSQL: A SQL Streaming Engine for Apache Kafka

KSQL is a SQL streaming engine for Apache Kafka. It provides an easy-to-use, yet powerful interactive SQL interface for stream processing on Kafka, without the need to write code in a programming language like Java or Python. KSQL is scalable, elastic, and fault-tolerant. It supports a wide range of streaming operations, including data filtering, transformations, aggregations, joins, windowing, and sessionization.

What Is Streaming?

In stream processing, data is continuously processed, as new data become available for analyzing. Data is processed sequentially as an unbounded stream and may be pulled in by a “listening” analytics system as a record in key-value pairs.

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Apache Kafka, KSQL, and Apache PLC4X for Industrial IoT and Automation

Learn more about IIoT automation with Apache Kafka, KSQL, and Apache PLC4X

Data integration and processing is a huge challenge in Industrial IoT (IIoT, aka Industry 4.0 or Automation Industry) due to monolithic systems and proprietary protocols. Apache Kafka, its ecosystem (Kafka Connect, KSQL), and Apache PLC4X are a great open-source choice to implement this IIoT integration end-to-end in a scalable, reliable, and flexible way.

This blog post covers a high-level overview of the challenges and good, flexible architecture to solve the problems. In the end, I share a video recording and the corresponding slide deck. These provide many more details and insights.