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Cloudera Training for Apache Kafka

This four-day instructor-led course begins by introducing Apache Kafka, explaining its key concepts and architecture, and discussing several common use cases. Building on this foundation, you will...

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$3,195 USD
Course Code CLOUD-AK
Duration 4 days
Available Formats Classroom
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This four-day instructor-led course begins by introducing Apache Kafka, explaining its key concepts and architecture, and discussing several common use cases. Building on this foundation, you will learn how to plan a Kafka deployment, and then gain hands-on experience by installing and configuring your own cloud-based, multi-node cluster running Kafka on the Cloudera Data Platform (CDP).

You will then use this cluster during more than 20 hands-on exercises that follow, covering a range of essential skills, starting with how to create Kafka topics, producers, and consumers, then continuing through progressively more challenging aspects of Kafka operations and development, such as those related to scalability, reliability, and performance problems. Throughout the course, you will learn and use Cloudera’s recommended tools for working with Kafka, including Cloudera Manager, Schema Registry, Streams Messaging Manager, and Cruise Control.

Skills Gained

  • Plan, deploy, and operate Kafka clusters
  • Create and manage topics
  • Develop producers and consumers
  • Use replication to improve fault tolerance
  • Use partitioning to improve scalability
  • Troubleshoot common problems and performance issues

Who Can Benefit

This course is designed for system administrators, data engineers, and developers. All students are expected to have basic Linux experience, and basic proficiency with the Java programming language is recommended.

Prerequisites

No prior experience with Apache Kafka is necessary.

Course Details

Course Outline

  • Kafka Overview
  • Deploying Apache Kafka
  • Kafka Command Line Basics
  • Using Streams Messaging Manager (SMM)
  • Kafka Java API Basics
  • Improving Availability through Replication
  • Improving Application Scalability
  • Improving Application Reliability
  • Analyzing Kafka Clusters with SMM
  • Monitoring Kafka
  • Managing Kafka
  • Message Structure, Format, and Versioning
  • Improving Application Performance
  • Improving Kafka Service Performance
  • Securing the Kafka Cluster
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