Apache Kafka Training | Kafka Tutorial - Online Course | Simplilearn

Course description

  • What is this course all about?

    Apache Kafka is an open source Apache project. It is a high-performance real-time messaging system that can process millions of messages per second. It provides a distributed and partitioned messaging system and is highly fault tolerant.

    The Apache Kafka course offered by Simplilearn takes participants through the Kafka architecture, installation, interfaces and configuration. The participants are also trained in the fundamental concepts of Big Data in this course.

  • Why is the course most sought-after?

    Apache Kafka course is popularly used in many companies across the world. The training in Apache Kafka is most sought-after for the following reasons:
    • Apache Kafka is the preferred messaging platform for processing big data in real-time and fast processing of real-time message feeds.
    • Kafka was initially developed at LinkedIn to process millions of messages per second and later became a part of Apache open source projects. It is a highly scalable and fault-tolerant messaging system with peta-byte scale message processing in real-time
    • The Apache Kafka professionals can demonstrate their expertise in the fast-growing big data industry
    • Trained Apache Kafka professionals are experienced in tools used to process huge amounts of data which will help them to take their organization towards big data analytics

  • What learning benefits do you get from Simplilearn’s training?

    Apache Kafka is one among the top ten fastest growing, in-demand technical skills. This course is designed to meet this demand and train professionals in Apache Kafka. By the end of Simplilearn’s training in Apache Kafka, participants will be able to:
    • Describe the importance of big data
    • Describe the fundamental concepts of Kafka
    • Describe the architecture of Kafka
    • Explain how to install and configure Kafka
    • Explain how to use Kafka for real-time messaging

  • What are the career benefits of this course?

    The Apache Kafka certification helps IT professionals add weight to their profile, and typically earn more compared to their non-certified peers. The certified professionals can look for career paths such as Senior Software Professional, IT Consultants, Lead Software Professionals and Big Data professionals.

    The value of Apache Kafka has increased sharply in the recent years and this certification is fast becoming an entry requirement for a majority of IT-based roles. According to a Dataquest survey, Apache Kafka figures among the top 10 highest paying IT jobs of 2015 with a salary of $134,950. (http://www.dqindia.com/top-ten-highest-it-paying-jobs-of-2015/).

  • Who should do this course?

    Following are the applicable careers for the Apache Kafka course:
    • Professionals aspiring for a career in big data
    • Analytics professionals, research professionals, IT Developers, Testers, and Project Managers
    • Students
    • Individuals looking for a change in career

Course preview

    • Lesson 00 - Course introduction 01:35
      • 0.1 Course Introduction 00:11
      • 0.2 Course Objectives 00:20
      • 0.3 Course Overview 00:18
      • 0.4 Target Audience 00:17
      • 0.5 Prerequisites 00:14
      • 0.6 Lessons Covered 00:08
      • 0.7 Conclusion 00:07
    • Lesson 01 - Big Data Overview 18:21
      • 1.1 Lesson 1—Big Data Overview 00:08
      • 1.2 Objectives 00:21
      • 1.3 Big Data—Introduction 00:25
      • 1.4 The Three Vs of Big Data 00:14
      • 1.5 Data Volume 00:34
      • 1.6 Data Sizes 00:28
      • 1.7 Data Velocity 00:49
      • 1.8 Data Variety 00:38
      • 1.9 Data Evolution 00:54
      • 1.10 Features of Big data 00:50
      • 1.11 Industry Examples 01:42
      • 1.12 Big Data Analysis 00:39
      • 1.13 Technology Comparison 01:05
      • 1.14 Stream 00:50
      • 1.15 Apache Hadoop 00:55
      • 1.16 Hadoop Distributed File System 00:58
      • 1.17 MapReduce 00:43
      • 1.18 Real-Time Big Data Tools 00:13
      • 1.19 Apache Kafka 00:19
      • 1.20 Apache Storm 00:26
      • 1.21 Apache Spark 00:56
      • 1.22 Apache Cassandra 00:55
      • 1.23 Apache Hbase 00:22
      • 1.24 Real-Time Big Data Tools—Uses 00:26
      • 1.25 Real-Time Big Data—Use Cases 01:32
      • 1.26 Quiz
      • 1.27 Summary 00:53
      • 1.28 Conclusion 00:06
    • Lesson 02 - Introduction to Zookeeper 24:27
      • 2.1 Introduction to ZooKeeper 00:10
      • 2.2 Objectives 00:26
      • 2.3 ZooKeeper—Introduction 00:30
      • 2.4 Distributed Applications 01:06
      • 2.5 Challenges of Distributed Applications 00:17
      • 2.6 Partial Failures 00:41
      • 2.7 Race Conditions 00:40
      • 2.8 Deadlocks 00:41
      • 2.9 Inconsistencies 00:48
      • 2.10 ZooKeeper Characteristics 00:53
      • 2.11 ZooKeeper Data Model 00:42
      • 2.12 Types of Znodes 00:38
      • 2.13 Sequential Znodes 00:32
      • 2.14 VMware 00:29
      • 2.15 Simplilearn Virtual Machine 00:23
      • 2.16 PuTTY 00:22
      • 2.17 WinSCP 00:19
      • 2.18 Demo—Install and Setup VM 00:06
      • 2.19 Demo—Install and Setup VM 08:12
      • 2.20 ZooKeeper Installation 00:20
      • 2.21 ZooKeeper Configuration 00:18
      • 2.22 ZooKeeper Command Line Interface 00:27
      • 2.23 ZooKeeper Command Line Interface Commands 01:07
      • 2.24 ZooKeeper Client APIs 00:30
      • 2.25 ZooKeeper Recipe 1: Handling Partial Failures 00:58
      • 2.26 ZooKeeper Recipe 2: Leader Election 02:09
      • 2.27 Quiz
      • 2.28 Summary 00:35
      • 2.29 Conclusion 00:08
    • Lesson 03 - Introduction to Kafka 16:01
      • 3.1 Lesson 3 Introduction to Kafka 00:09
      • 3.2 Objectives 00:19
      • 3.3 Apache Kafka—Introduction 00:23
      • 3.4 Kafka History 00:30
      • 3.5 Kafka Use Cases 00:48
      • 3.6 Aggregating User Activity Using Kafka—Example 00:43
      • 3.7 Kafka Data Model 01:27
      • 3.8 Topics 01:15
      • 3.9 Partitions 00:36
      • 3.10 Partition Distribution 00:48
      • 3.11 Producers 00:48
      • 3.12 Consumers 00:46
      • 3.13 Kafka Architecture 01:10
      • 3.14 Types of Messaging Systems 00:42
      • 3.15 Queue System—Example 00:37
      • 3.16 Publish-Subscribe System—Example 00:34
      • 3.17 Brokers 00:24
      • 3.18 Kafka Guarantees 00:58
      • 3.19 Kafka at LinkedIn 00:54
      • 3.20 Replication in Kafka 00:44
      • 3.21 Persistence in Kafka 00:41
      • 3.22 Quiz
      • 3.23 Summary 00:38
      • 3.24 Conclusion 00:07
    • Lesson 04 - Installation and Configuration 08:53
      • 4.1 Lesson 4—Installation and Configuration 00:10
      • 4.2 Objectives 00:22
      • 4.3 Kafka Versions 00:49
      • 4.4 OS Selection 00:19
      • 4.5 Machine Selection 00:34
      • 4.6 Preparing for Installation 00:19
      • 4.7 Demo 1—Kafka Installation and Configuration 00:05
      • 4.8 Demo 1—Kafka Installation and Configuration 00:05
      • 4.9 Demo 2—Creating and Sending Messages 00:05
      • 4.10 Demo 2—Creating and Sending Messages 00:05
      • 4.11 Stop the Kafka Server 00:40
      • 4.12 Setting up Multi-Node Kafka Cluster—Step 1 00:24
      • 4.13 Setting up Multi-Node Kafka Cluster—Step 2 00:59
      • 4.14 Setting up Multi-Node Kafka Cluster—Step 3 01:04
      • 4.15 Setting up Multi-Node Kafka Cluster—Step 4 00:36
      • 4.16 Setting up Multi-Node Kafka Cluster—Step 5 00:29
      • 4.17 Setting up Multi-Node Kafka Cluster—Step 6 01:08
      • 4.18 Quiz
      • 4.19 Summary 00:33
      • 4.20 Conclusion 00:07
    • Lesson 05 - Kafka Interfaces 18:17
      • 5.1 Lesson 5—Kafka Interfaces 00:09
      • 5.2 Objectives 00:18
      • 5.3 Kafka Interfaces—Introduction 00:21
      • 5.4 Creating a Topic 01:23
      • 5.5 Modifying a Topic 00:36
      • 5.6 kafka-topics.sh Options 00:57
      • 5.7 Creating a Message 00:15
      • 5.8 kafka-console-producer.sh Options 01:48
      • 5.9 Creating a Message—Example 1 01:01
      • 5.10 Creating a Message—Example 2 00:39
      • 5.11 Reading a Message 00:21
      • 5.12 kafka-console-consumer.sh Options 01:32
      • 5.13 Reading a Message—Example 00:44
      • 5.14 Java Interface to Kafka 00:18
      • 5.15 Producer Side API 00:42
      • 5.16 Producer Side API Example—Step 1 00:32
      • 5.17 Producer Side API Example—Step 2 00:15
      • 5.18 Producer Side API Example—Step 3 00:21
      • 5.19 Producer Side API Example—Step 4 00:21
      • 5.20 Producer Side API Example—Step 5 00:17
      • 5.21 Consumer Side API 00:37
      • 5.22 Consumer Side API Example—Step 1 00:21
      • 5.23 Consumer Side API Example—Step 2 00:15
      • 5.24 Consumer Side API Example—Step 3 00:20
      • 5.25 Consumer Side API Example—Step 4 00:25
      • 5.26 Consumer Side API Example—Step 5 00:25
      • 5.27 Compiling a Java Program 00:29
      • 5.28 Running the Java Program 00:18
      • 5.29 Java Interface Observations 00:39
      • 5.30 Exercise 1—Tasks 00:05
      • 5.31 Exercise 1—Tasks (contd.) 00:05
      • 5.32 Exercise 1—Solutions 00:05
      • 5.33 Exercise 1—Solutions (contd.) 00:05
      • 5.34 Exercise 1—Solutions (contd.) 00:05
      • 5.35 Exercise 2—Tasks 00:05
      • 5.36 Exercise 2—Tasks (contd.) 00:05
      • 5.37 Exercise 2—Solutions 00:05
      • 5.38 Exercise 2—Solutions (contd.) 00:05
      • 5.39 Exercise 2—Solutions (contd.) 00:05
      • 5.40 Exercise 2—Solutions (contd.) 00:05
      • 5.41 Exercise 2—Solutions (contd.) 00:05
      • 5.42 Quiz
      • 5.43 Summary 00:30
      • 5.44 Thank You 00:08
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Exam & certification

  • What are the prerequisites for the Apache Kafka course?

    The prerequisites for the Apache Kafka course are:
    • Knowledge of any messaging system
    • Basic knowledge of Java or any programming language
    • Some knowledge of Linux or Unix-based systems is desired

  • What do I need to do to unlock my Simplilearn certificate?

    Online Self-Learning:
    • Complete 1 simulation test with a minimum score of 60%.

FAQs

  • Do you provide demos in this course?

    Yes. In addition to the lessons, there are demos in this course for better understanding of the concepts.

  • Can I install Kafka on a Mac machine?

    Yes. Kafka can be installed on Mac systems. The installation steps are similar to the installation on Linux and can be done with the instructions provided in the lessons.

  • What are the system requirements to install Kafka?

    For this training, we recommend a laptop with windows 7 or higher version, with at least 4GB of RAM. If you already have a Linux or Mac System, then you can install on those systems as well.

  • How will the demos be done?

    For the demos, we will help you setup the virtual machine on your windows laptop and install Kafka on the virtual machine.

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  • Disclaimer
  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.
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