Cloudera Training for Apache Kafka Course Overview

Cloudera Training for Apache Kafka Course Overview

The Cloudera Training for Apache Kafka course is a comprehensive program designed to equip learners with in-depth knowledge and practical skills in managing and deploying Kafka clusters within a Cloudera distribution. It covers a wide range of topics, from high-level architecture and common use cases to deployment, management, and performance optimization of Kafka. Throughout the course, participants will engage in hands-on exercises that provide real-world experience with Kafka's command line, Java API, and Streams Messaging Manager (SMM).

Learners will also delve into more advanced topics such as replication, scalability, reliability, and security to ensure Kafka clusters are robust and secure. By the end of the course, participants will be well-versed in Kafka training techniques and ready to efficiently handle data streaming tasks. The curriculum of Apache Kafka training ensures that learners are able to monitor, manage, and optimize Kafka to meet the demands of their organization's data processing needs.

This is a Rare Course and it can be take up to 3 weeks to arrange the training.

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  • Live Online Training (Duration : 32 Hours)
  • Per Participant
  • Guaranteed-to-Run (GTR)
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♱ Excluding VAT/GST

Classroom Training price is on request

  • Live Online Training (Duration : 32 Hours)
  • Per Participant

♱ Excluding VAT/GST

Classroom Training price is on request

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Course Prerequisites

To successfully undertake the Cloudera Training for Apache Kafka course, it is recommended that participants have the following minimum prerequisites:


  • Basic understanding of Linux command line operations, as Kafka and its components are typically managed in a Linux environment.
  • Familiarity with basic Linux system administration tasks, such as installing and configuring software and managing services.
  • Fundamental knowledge of computer networking concepts to understand how Kafka nodes communicate within a cluster.
  • A grasp of the Java programming language, as the course includes modules that involve writing Kafka clients using Java.
  • Conceptual understanding of distributed systems is beneficial, though not strictly required, for comprehending Kafka's architecture and operation.
  • Prior exposure to any messaging or queueing system concepts would be helpful, although not mandatory, for understanding Kafka's use cases and comparison with other technologies.

Please note that while these prerequisites are aimed at ensuring a smooth learning experience, our course is designed to accommodate a range of skill levels, and our expert instructors are committed to helping all participants achieve a comprehensive understanding of Apache Kafka.


Target Audience for Cloudera Training for Apache Kafka

Koenig Solutions' Cloudera Training for Apache Kafka equips participants with the skills to deploy, manage, and optimize Kafka clusters.


  • Data Engineers


  • Data Architects


  • System Administrators


  • DevOps Engineers


  • Software Developers working with big data


  • IT Professionals involved in messaging systems


  • Technical Managers overseeing data pipeline infrastructure


  • Analysts interested in real-time data processing


  • Professionals seeking to learn about high-throughput messaging systems


  • Cloudera Administrators and Consultants


  • Security Engineers focusing on secure data transmission


  • Quality Assurance Engineers testing messaging systems


  • Technical Leads and Architects designing real-time data solutions


  • Database Professionals expanding their skills to include Kafka


  • Big Data Enthusiasts looking to enhance their skillset with Kafka knowledge




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

  1. Introduction to the course's learning outcomes and concepts: This Cloudera Training for Apache Kafka course equips participants with the knowledge to deploy, manage, and optimize Kafka clusters, ensuring high availability, scalability, and performance in real-world scenarios.

  2. Learning objectives and outcomes:

  • Understand Kafka's high-level architecture and its common use cases within the Cloudera distribution.
  • Learn to deploy Apache Kafka considering system requirements, dependencies, and service roles.
  • Gain proficiency in using Kafka's command line interface to create and manage topics, and run producers and consumers.
  • Utilize Streams Messaging Manager (SMM) for monitoring and managing Kafka topics, producers, and consumers.
  • Develop skills to work with Kafka Java API for topic management and implementing producers and consumers.
  • Enhance cluster availability through replication, including setting up replicas and handling broker failures.
  • Improve application scalability using partitioning, consumer groups, and rebalancing, and manage consumer offsets effectively.
  • Ensure application reliability with delivery semantics, idempotent producers, transactional messaging, and handling of producer and consumer failures.
  • Monitor and analyze Kafka clusters using Cloudera Manager and SMM, understanding metrics and implementing alert policies.
  • Secure the Kafka cluster with encryption, authentication, authorization, and auditing best practices.