Gain Expert Knowledge with Cloudera Training for Apache Kafka

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Cloudera Training for Apache Kafka Course Overview

Cloudera Training for Apache Kafka is a comprehensive online course designed to provide hands-on instruction for developers and administrators to learn the fundamentals of Kafka streaming technology and develop applications for Kafka clusters. Using the distributed streaming platform Apache Kafka, the course covers topics like setting up and managing a Kafka cluster, developing applications with Kafka Streams, leveraging Kafka for real-time data processing and analytics, and visualizing data with Kafka Connect. The course also covers how to integrate Kafka with other big data technologies such as Hadoop, Spark, and Apache Avro. The course can be used to gain a better understanding of class streaming platform, develop Apache Kafka applications, or learn how to manage and monitor a Kafka cluster.

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


The 1-on-1 Advantage

Get 1on-1 session with our expert trainers at a date & time of your convenience.

Flexible Dates

Start your session at a date of your choice-weekend & evening slots included, and reschedule if necessary.

4-Hour Sessions

Training never been so convenient- attend training sessions 4-hour long for easy learning.

Destination Training

Attend trainings at some of the most loved cities such as Dubai, London, Delhi(India), Goa, Singapore, New York and Sydney.

You will learn:

Module 1: Kafka Overview
  • High-Level Architecture
  • Common Use Cases
  • Cloudera's Distribution of Apache Kafka
  • System Requirements and Dependencies
  • Service Roles
  • Planning Your Deployment Deploying Kafka Services
  • Exercise: Preparing the Exercise Environment
  • Exercise: Installing the Kafka Service with Cloudera Manager
  • Exercise (optional): Create Metrics Dashboards
  • Exercise (optional): Using the CM API
  • Create and Manage Topics
  • Running Producers and Consumers
  • Streams Messaging Manager Overview
  • Producers, Topics, and Consumers
  • Data Explorer
  • Brokers
  • Topic Management
  • Exercise: Managing Topics using the CLI
  • Exercise: Connecting Producers and Consumers from the Command Line
  • Overview of Kafka's APIs
  • Topic Management from the Java API
  • Exercise (optional): Managing Kafka Topics Using the Java API
  • Using Producers and Consumers from the Java API
  • Exercise: Developing Producers and Consumers with the Java API
  • Replication
  • Exercise: Observing Downtime Due to Broker Failure
  • Considerations for the Replication Factor
  • Exercise: Adding Replicas to Improve Availability
  • Partitioning
  • How Messages are Partitioned
  • Exercise: Observing How Partitioning Affects Performance
  • Consumer Groups
  • Exercise: Implementing Consumer Groups
  • Consumer Rebalancing
  • Exercise: Using a Key to Control Partition Assignment
  • Delivery Semantics
  • Demonstration (optional): ISRs vs. ACKs
  • Producer Delivery
  • Exercise: Idempotent Producer
  • Transactions
  • Exercise: Transactional Producers and Consumers
  • Handling Consumer Failure
  • Offset Management
  • Exercise: Detecting and Suppressing Duplicate Messages
  • Exercise: Handling Invalid Records
  • Handling Producer Failure
  • End-to-End Latency
  • Notifiers
  • Alert Policies
  • Use Cases
  • Monitoring Overview
  • Monitoring using Cloudera Manager
  • Charts and Reports in CM
  • Monitoring Recommendations
  • Metrics for Troubleshooting
  • Diagnosing Service Failure
  • Exercise: Monitoring Kafka
  • Managing Kafka Topic Storage
  • Demonstration (optional): Message Retention Period
  • Log Cleanup and Collection
  • Rebalancing Partitions
  • Cruise Control
  • Exercise: Installing Cruise Control
  • Exercise: Troubleshooting Kafka Topics
  • Unclean Leader Election
  • Exercise: Unclean Leader Election
  • Adding and Removing Brokers
  • Exercise: Adding and Removing Brokers
  • Best Practices
  • Message Structure
  • Schema Registry
  • Defining Schemas
  • Schema Evolution and Versioning
  • Schema Registry Client
  • Exercise: Using an Avro Schema
  • Message Size
  • Batching
  • Compression
  • Exercise: Observing How Compression Affects Performance
  • Performance Tuning Strategies for the Administrator
  • Cluster Sizing
  • Exercise: Planning Capacity Needed for a Use Case
  • Encryption
  • Authentication
  • Authorization
  • Auditing
Live Online Training (Duration : 32 Hours) 1750 + If you accept merging of other students. Per Participant & excluding VAT/GST
We Offer :
  • 1-on-1 Public - Select your own start date. Other students can be merged.
  • 1-on-1 Private - Select your own start date. You will be the only student in the class.

4 Hours
8 Hours
Week Days

Start Time : At any time

12 AM
12 PM

1-On-1 Training is Guaranteed to Run (GTR)
Group Training
Date On Request
Course Prerequisites

There are no specific prerequisites for taking up the Cloudera Training for Apache Kafka. However, it is advisable that participants have a basic knowledge of distributed systems and messaging middleware. Furthermore, some degree of knowledge in Apache Kafka and ZooKeeper, as well as Linux systems, would prove beneficial.

Target Audience

The target audience for the Cloudera Training for Apache Kafka training is software developers, administrators, and data analysts who are looking to learn more about distributed messaging and streaming applications
The course is designed for those with a basic understanding of software development, who want to improve their knowledge of Kafka
The training covers topics such as Apache Kafka architecture, installation and configuration, topics, partitions, consumers, and more
Those with a working knowledge of application development and related technologies will benefit the most from the course
At the end, attendees should have an understanding of how Apache Kafka can be used to meet organizational streaming needs

Learning Objectives of Cloudera Training for Apache Kafka

1. Learn what Apache Kafka is and its various components.
2. Understand the fundamentals of messaging, topics and partitions.
3. Gain knowledge on how producers and consumers work in the Kafka platform.
4. Acquire hands-on experience with the Kafka programming API and the command line interface.
5. Be able to Install, configure, and use Kafka from the command line and system administration perspective.
6. Learn basic operations such as creating topics, partitions and sending/receiving messages.
7. Use an Integrated Development Environment (IDE) such as IntelliJ to code and debug.
8. Understand the best practices to monitor, maintain and troubleshoot Kafka.
9. Leverage Kafka features such as Kafka Connect, Kafka Streams, and the Kafka Admin API.
10. Leverage Apache Spark to do real-time analytics using Kafka data streams.

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1-on-1 Public - Select your start date. Other students can be merged.
1-on-1 Private - Select your start date. You will be the only student in the class.
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Schedule for Group Training is decided by Koenig. Schedule for 1-on-1 is decided by you.
In 1 on 1 Public you can select your own schedule, other students can be merged. Choose 1-on-1 if published schedule doesn't meet your requirement. If you want a private session, opt for 1-on-1 Private.
Duration of Ultra-Fast Track is 50% of the duration of the Standard Track. Yes(course content is same).

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