Kafka Streams API for Developers

This course provides practical, hands-on training in Kafka Streams, covering:

• Building streaming applications that process real-time data.
• Handling large-scale events efficiently using Kafka Streams operators.
• Developing REST APIs to query stateful streaming data.
• Integrating Kafka Streams with Spring Boot for enterprise applications.
• Implementing real-world use cases like an Order Management System.
• Writing and testing Kafka Streams applications for production.

By the end of the course, you will be job-ready for Kafka Streams-related roles.

Yes, you will need:

• Java 17 or later
• Apache Kafka and Zookeeper (Docker recommended)
• Kafka Streams API
• Spring Boot (for microservices integration)
• Schema Registry (if working with AVRO serialization)
• Gradle or Maven (for project management)
• IntelliJ IDEA or any other Java IDE

Docker is highly recommended to simplify the Kafka setup.

If you have prior Kafka experience, you can master Kafka Streams with:

• Basic Concepts & API Understanding – 1-2 weeks
• Building Kafka Streams Applications – 2-3 weeks
• Advanced Topics (Stateful Operations, Joins, Windowing) – 3-4 weeks
• Testing & Debugging Kafka Streams Apps – 2-3 weeks
• Deploying Kafka Streams Apps in Production – 3-4 weeks

For a strong grasp of Kafka Streams in production, 3-6 months of hands-on experience is recommended.

This course provides hands-on experience with:

• Kafka Streams API
• Spring Boot (for enterprise integration)
• Kafka Producer and Consumer APIs
• Stateful operations (Joins, Aggregations, Windowing, KTables, GlobalKTables)
• Testing Kafka Streams applications (JUnit, Embedded Kafka, TopologyTestDriver)
• RESTful APIs for interactive queries
• Serialization & Deserialization (JSON, Avro, Custom Serdes)
• Error handling in streaming applications

Kafka Streams is widely used in industries that require real-time processing and decision-making, including:

• Financial Services – Fraud detection, real-time risk analysis, stock trading platforms.
• E-commerce – Order tracking, real-time inventory updates, personalized recommendations.
• Telecom – Network monitoring, call data analysis, predictive maintenance.
• Healthcare – IoT-enabled patient monitoring, real-time diagnostics.
• Cybersecurity – Intrusion detection, threat analysis.
• IoT & Smart Cities – Sensor data processing, traffic monitoring, environmental analytics.

No. This course is intended for experienced Java developers with prior knowledge of Kafka Producers and Consumers. If you are new to Kafka, you should first understand Kafka fundamentals before diving into Kafka Streams.

To make the most of this course, you should have:

• Strong Java programming skills (Java 17 recommended).
• Experience working with Kafka Producers and Consumers.
• Basic understanding of distributed systems and event-driven architectures.
• Familiarity with IntelliJ or any other Java IDE.
• Knowledge of build tools like Maven or Gradle.

Having prior experience with Spring Boot is beneficial but not mandatory.

India:

• Entry-level (0-2 years): ₹8 - ₹12 LPA
• Mid-level (3-6 years): ₹15 - ₹25 LPA
• Senior-level (7+ years): ₹30 - ₹50 LPA

United States:

• Entry-level: $100,000 - $130,000 per year
• Mid-level: $130,000 - $170,000 per year
• Senior-level: $170,000 - $220,000 per year

Professionals with Kafka Streams + Cloud experience (AWS/GCP/Azure) often earn higher salaries.

Kafka Streams is a powerful stream processing library built on Apache Kafka, designed for real-time data transformation and analytics. Unlike traditional batch processing, Kafka Streams allows developers to process and analyze data as it flows, making it ideal for building event-driven applications, monitoring systems, fraud detection systems, and more.

It simplifies real-time processing by eliminating the need for additional infrastructure, making it a lightweight and scalable solution for streaming applications.

With the increasing demand for real-time data processing, mastering Kafka Streams opens doors to various high-paying job roles, including:

• Kafka Streams Developer
• Big Data Engineer
• Software Engineer (Kafka & Event-Driven Architecture)
• Streaming Data Architect
• Backend Engineer (Kafka & Microservices)
• Cloud Data Engineer (Kafka on AWS/GCP/Azure)

Industries like finance, e-commerce, telecom, healthcare, cybersecurity, and IoT are actively hiring Kafka Streams professionals.