Cloudera Training for Apache Kafka Course Overview

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.