Apache Kafka Course Overview

Apache Kafka Course Overview

The Apache Kafka course is a comprehensive program designed to introduce learners to the world of big data and real-time data processing using Apache Kafka. The course is structured into various modules, each focusing on different aspects of Kafka, from basic concepts and architecture to advanced programming and performance tuning.

In Module 1, participants will gain a foundational understanding of big data and explore real-world big data customer scenarios. They will be introduced to Kafka, understand its necessity in the big data ecosystem, dive into its core concepts, and learn about its architecture and use cases.

Module 2 will delve into the Kafka cluster, covering its components, installation, and configuration. Learners will also get hands-on experience with Kafka producers and consumers, observing them in action.

Module 3 is dedicated to Kafka Java programming, where students will build and run Kafka projects using Java, mastering producer callbacks, consumer rebalance, and offset commit behaviors.

In Module 4, the course focuses on Kafka operations and performance tuning, including monitoring, design considerations, and hardware optimizations.

Module 5 and Module 6 offer advanced configurations and real-world project implementations, such as the Wikimedia Producer and OpenSearch Consumer, covering topics like producer acknowledgements, retries, idempotence, and consumer delivery semantics.

Overall, this course empowers learners with the necessary skills to work with Kafka in a professional setting, providing a balance of theoretical knowledge and practical application.

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  • Live Online Training (Duration : 32 Hours)
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  • Live Online Training (Duration : 32 Hours)
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Classroom Training price is on request

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Course Prerequisites

To ensure that you can successfully undertake training in our Apache Kafka course, we recommend that you possess the following minimum prerequisites:

  • Basic understanding of Big Data concepts and its significance in the current technological landscape.
  • Fundamental knowledge of distributed systems and their common use cases.
  • Familiarity with command-line interfaces (CLI) and basic Linux commands, as they are frequently used when working with Kafka.
  • Experience with a programming language, preferably Java, since the course includes hands-on Kafka programming modules.
  • Some exposure to software development concepts such as version control systems (e.g., Git) can be beneficial.
  • It is helpful to have a rudimentary understanding of data streaming and message brokers, though not strictly necessary.

These prerequisites are designed to ensure that you have a solid foundation upon which to build your Kafka expertise. They are not meant to deter you from enrolling; rather, they are intended to prepare you for a rewarding learning experience.

Target Audience for Apache Kafka

Apache Kafka is an advanced course for IT professionals seeking to master Big Data processing and streaming.

  • Data Engineers
  • Big Data Architects
  • Software Developers and Engineers working on real-time data processing
  • IT Professionals involved in data analytics
  • System Administrators and DevOps Professionals managing Kafka clusters
  • Technical Leads and Project Managers overseeing Big Data projects
  • Data Scientists requiring knowledge of data streaming platforms
  • Application Architects designing systems that include data ingestion and processing
  • Technology Consultants specializing in messaging systems and streaming platforms
  • Professionals with a background in Apache Hadoop looking to enhance their skill set with Kafka

Learning Objectives - What you will Learn in this Apache Kafka?

Introduction to Apache Kafka Course Learning Outcomes

This Apache Kafka course offers an in-depth understanding of big data processing, Kafka architecture, cluster management, and real-world applications using Java programming for robust Kafka operations.

Learning Objectives and Outcomes

  • Gain foundational knowledge of Big Data concepts and understand the role of Apache Kafka in Big Data scenarios.
  • Learn the core concepts and architecture of Kafka, including its components and usage in various domains.
  • Set up and configure a Kafka Cluster, and understand the roles of producers and consumers in the Kafka ecosystem.
  • Develop proficiency in Kafka Java programming, including the creation of Kafka projects and the implementation of Java producers and consumers.
  • Master the operational aspects of Kafka, such as monitoring, performance tuning, and understanding offset management.
  • Explore advanced Kafka producer configurations, ensuring message durability, and implementing producer acknowledgments and retries.
  • Understand the importance of idempotent producers and configure safe Kafka producer settings to prevent data loss.
  • Learn to implement an OpenSearch Consumer, manage delivery semantics, and strategize consumer offset commits for efficient data processing.
  • Dive into advanced consumer configurations, including batching data for performance optimization and resetting consumer offsets to replay data.
  • Build practical skills through hands-on projects like the Wikimedia Producer and OpenSearch Consumer, reinforcing the theoretical knowledge with real-world applications.

These learning objectives are designed to equip students with the necessary skills to effectively implement and manage Apache Kafka solutions in their IT environments, contributing to their organizations' data processing and streaming capabilities.