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Cloudera Training for Apache Kafka

Cloudera Training for Apache Kafka is an advanced training course designed for professionals who want to master real-time data streaming and processing using Apache Kafka on the Cloudera Data Platform (CDP). This course covers everything from setting up Kafka clusters to designing, configuring, and managing data streams. Learn how to work with producers, consumers, topics, and Kafka Streams to build highly scalable and fault-tolerant data pipelines. You'll gain hands-on experience deploying and managing Kafka on the Cloudera platform and learn how to integrate it with other big data technologies like Apache Hadoop, Apache Spark, and Cloudera Data Flow to build efficient and reliable data streaming architectures.

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Schedule Learners Course Fee (Incl. of all Taxes) Register Your Interest
December 22nd - 25th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
Guaranteed-to-Run
10% Off
$1,600
$1,440
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December 27th - 04th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
10% Off
$1,600
$1,440
January 05th - 08th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
20% Off
$1,600
$1,280
January 10th - 18th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
20% Off
$1,600
$1,280
January 12th - 15th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
20% Off
$1,600
$1,280
January 19th - 28th
06:00 AM - 10:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
20% Off
$1,600
$1,280
January 26th - 29th
09:00 AM - 05:00 PM (CST)
Live Virtual Classroom (Duration : 32 Hours)
Guaranteed-to-Run
20% Off
$1,600
$1,280

Course Prerequisites

  • Basic knowledge of Apache Kafka concepts
  • Familiarity with distributed systems and data streaming principles
  • Understanding of Cloudera Data Platform (CDP) or similar big data platforms
  • Experience with Linux/Unix systems is helpful
  • Basic understanding of data pipelines, Hadoop, and Spark is beneficial

Learning Objectives

By the end of this course, participants will be able to:

  • Deploy and configure Apache Kafka on Cloudera Data Platform (CDP)
  • Build and manage real-time data streaming pipelines using Kafka
  • Scale Kafka clusters and optimize for performance and fault tolerance
  • Secure Kafka environments using authentication, authorization, and encryption
  • Implement Kafka Streams for real-time data processing and analytics
  • Integrate Kafka with other big data technologies like Hadoop, Spark, and Cloudera Data Flow
  • Troubleshoot and debug Kafka applications and clusters efficiently

Target Audience

This course is ideal for professionals involved in managing and developing real-time data streaming solutions. The target audience includes:

  • Data Engineers
  • Big Data Architects
  • Systems Administrators
  • Data Scientists working with real-time data
  • IT professionals managing Kafka clusters
  • Developers building real-time data processing applications
  • Cloud Engineers and DevOps Teams

Course Modules

  • Introduction to Apache Kafka and Real-Time Data Streaming

    • Overview of Apache Kafka and its ecosystem
    • Key components of Kafka: Producers, Consumers, Topics, Brokers, and Zookeeper
    • Use cases and applications for real-time data streaming
  • Setting Up and Configuring Apache Kafka on Cloudera

    • Installing and configuring Apache Kafka in Cloudera Data Platform (CDP)
    • Configuring and managing Kafka brokers for high availability
    • Integrating Kafka with other Cloudera services like Hadoop and Spark
  • Kafka Data Pipeline Design and Management

    • Building data pipelines using Kafka producers and consumers
    • Creating and managing Kafka topics and partitions
    • Understanding Kafka's message delivery guarantees: at-most-once, at-least-once, and exactly-once semantics
  • Managing Kafka Streams and Real-Time Data Processing

    • Introduction to Kafka Streams for stream processing
    • Setting up Kafka Streams applications and processing real-time data
    • Implementing aggregations, transformations, and joins in stream processing
  • Kafka Connect for Data Integration

    • Using Kafka Connect to integrate Kafka with external systems and databases
    • Configuring source and sink connectors for various data sources
    • Best practices for scaling and managing Kafka Connect deployments
  • Scaling and Monitoring Kafka Clusters

    • Horizontal scaling strategies for Kafka clusters in Cloudera
    • Performance tuning and capacity planning for Kafka workloads
    • Monitoring Kafka with Cloudera Manager and other monitoring tools
  • Security and Data Governance in Kafka

    • Implementing Kafka security mechanisms: SSL, SASL, ACLs
    • Ensuring data governance in Kafka with access control and data encryption
    • Managing data retention policies and auditing Kafka clusters
  • Fault Tolerance and High Availability in Kafka

    • Ensuring Kafka cluster fault tolerance with replication and leader election
    • Setting up Kafka cluster for high availability and disaster recovery
    • Monitoring and maintaining the health of Kafka clusters
  • Best Practices for Apache Kafka on Cloudera

    • Advanced topics and tips for optimizing Kafka performance
    • Real-world best practices for Kafka cluster management
    • Troubleshooting and debugging Kafka issues effectively

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