Master Apache Kafka configuration, monitoring, and optimization for production environments. This hands-on course teaches you to design high-availability topic architectures, diagnose performance bottlenecks using consumer lag analysis, and tune producers and consumers for maximum throughput while meeting strict latency SLAs. Through real-world scenarios based on challenges faced by companies like Netflix, LinkedIn, Uber, and Walmart, you'll learn to prevent data loss during broker failures, eliminate consumer lag issues, and optimize Kafka clusters processing millions of events per second. By the end of this course, you'll have the skills to build, monitor, and optimize production Kafka infrastructure that handles massive scale while maintaining reliability and performance.

This course is designed for software engineers, data platform specialists, and DevOps professionals who work with real-time data systems and want to deepen their expertise in Apache Kafka. Ideal learners already understand basic Kafka concepts and distributed systems fundamentals but seek to enhance their ability to configure, monitor, and optimize Kafka clusters for high-throughput, low-latency production environments. It’s also valuable for those preparing for roles in data engineering, site reliability, or systems performance optimization. Learners should have a basic understanding of distributed systems and networking concepts, familiarity with command-line interfaces, and introductory knowledge of Apache Kafka fundamentals such as topics, producers, and consumers. Prior experience with Linux environments, Docker, or monitoring tools like Grafana and Prometheus will be helpful but not required. By the end of this course, you’ll be able to configure and optimize Apache Kafka clusters for high throughput, low latency, and maximum availability. You’ll gain hands-on experience in monitoring broker health, diagnosing consumer lag, and tuning producer and consumer performance for real-world production environments. With these skills, you’ll be ready to build, scale, and maintain data streaming systems that power modern, high-performance applications.