01 Stream processing with Kafka

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

02 Prerequisites

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

03 What is stream processing

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

04 Streaming opportunities and challenges

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

05 Streaming with Kafka Streams

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

06 Kafka Streams DSL

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

07 Setting up the exercise files

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

08 Setting up Kafka

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

09 Setting up MariaDB and Redis

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

10 Streaming analytics Pattern

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

11 Streaming analytics Use case design

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

12 Streaming analytics Helper classes

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

13 Streaming analytics Pipeline implementation

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

14 Streaming analytics Results review

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

15 Alerts and thresholds Pattern

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

16 Alerts and thresholds Use case design

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

17 Alerts and thresholds Helper classes

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

18 Alerts and thresholds Pipeline implementation

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

19 Alerts and thresholds Review

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

20 Leaderboards Pattern

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

21 Leaderboards Use case design

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

22 Leaderboards Helper classes

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

23 Leaderboards Pipeline implementation

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

24 Leaderboards Review

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

25 Real-time predictions Pattern

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

26 Real-time predictions Use case design

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

27 Real-time predictions Helper classes

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

28 Real-time predictions Pipeline implementation

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

29 Real-time predictions Review

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

30 Use case definition

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

31 Design of the project

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

32 Code walk-through

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

33 Execute and analyze

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

34 Next steps

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.

KafkaStreams_Stream_Processing_Patterns.zip

Description

Stream Processing Design Patterns with Kafka Streams

Stream processing is rapidly growing in popularity, as more and more data is generated every day by websites, devices, and communications. Platforms such as Apache Kafka Streams can help you build fast, scalable stream processing applications, but big data engineers still need to design smart use cases to achieve maximum efficiency. In this course, get insight into how to solve stream processing problems with Kafka Streams in Java as you learn how to build use cases with popular design patterns. Review some of the significant features of Kafka Streams and discover four popular patterns for stream processing: streaming analytics, alerts and thresholds, leaderboards, and real-time predictions. Along the way, review example use cases, and discover how to leverage Kafka Streams, as well as key technologies like MariaDB and Redis, to implement key examples.