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  • 10 hours of self-paced video
  • Includes 2 hands-on lab exercises
  • Includes 1 industry-based case study
  • Includes 2 simulation exams

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 Introduction00:11
      • 0.2 Course Objectives00:20
      • 0.3 Course Overview00:18
      • 0.4 Target Audience00:17
      • 0.5 Prerequisites00:14
      • 0.6 Lessons Covered00:08
      • 0.7 Conclusion00:07
    • Lesson 01 - Big Data Overview 18:21
      • 1.1 Lesson 1—Big Data Overview00:08
      • 1.2 Objectives00:21
      • 1.3 Big Data—Introduction00:25
      • 1.4 The Three Vs of Big Data00:14
      • 1.5 Data Volume00:34
      • 1.6 Data Sizes00:28
      • 1.7 Data Velocity00:49
      • 1.8 Data Variety00:38
      • 1.9 Data Evolution00:54
      • 1.10 Features of Big data00:50
      • 1.11 Industry Examples01:42
      • 1.12 Big Data Analysis00:39
      • 1.13 Technology Comparison01:05
      • 1.14 Stream00:50
      • 1.15 Apache Hadoop00:55
      • 1.16 Hadoop Distributed File System00:58
      • 1.17 MapReduce00:43
      • 1.18 Real-Time Big Data Tools00:13
      • 1.19 Apache Kafka00:19
      • 1.20 Apache Storm00:26
      • 1.21 Apache Spark00:56
      • 1.22 Apache Cassandra00:55
      • 1.23 Apache Hbase00:22
      • 1.24 Real-Time Big Data Tools—Uses00:26
      • 1.25 Real-Time Big Data—Use Cases01:32
      • 1.26 Quiz
      • 1.27 Summary00:53
      • 1.28 Conclusion00:06
    • Lesson 02 - Introduction to Zookeeper 24:27
      • 2.1 Introduction to ZooKeeper00:10
      • 2.2 Objectives00:26
      • 2.3 ZooKeeper—Introduction00:30
      • 2.4 Distributed Applications01:06
      • 2.5 Challenges of Distributed Applications00:17
      • 2.6 Partial Failures00:41
      • 2.7 Race Conditions00:40
      • 2.8 Deadlocks00:41
      • 2.9 Inconsistencies00:48
      • 2.10 ZooKeeper Characteristics00:53
      • 2.11 ZooKeeper Data Model00:42
      • 2.12 Types of Znodes00:38
      • 2.13 Sequential Znodes00:32
      • 2.14 VMware00:29
      • 2.15 Simplilearn Virtual Machine00:23
      • 2.16 PuTTY00:22
      • 2.17 WinSCP00:19
      • 2.18 Demo—Install and Setup VM00:06
      • 2.19 Demo—Install and Setup VM08:12
      • 2.20 ZooKeeper Installation00:20
      • 2.21 ZooKeeper Configuration00:18
      • 2.22 ZooKeeper Command Line Interface00:27
      • 2.23 ZooKeeper Command Line Interface Commands01:07
      • 2.24 ZooKeeper Client APIs00:30
      • 2.25 ZooKeeper Recipe 1: Handling Partial Failures00:58
      • 2.26 ZooKeeper Recipe 2: Leader Election02:09
      • 2.27 Quiz
      • 2.28 Summary00:35
      • 2.29 Conclusion00:08
    • Lesson 03 - Introduction to Kafka 16:01
      • 3.1 Lesson 3 Introduction to Kafka00:09
      • 3.2 Objectives00:19
      • 3.3 Apache Kafka—Introduction00:23
      • 3.4 Kafka History00:30
      • 3.5 Kafka Use Cases00:48
      • 3.6 Aggregating User Activity Using Kafka—Example00:43
      • 3.7 Kafka Data Model01:27
      • 3.8 Topics01:15
      • 3.9 Partitions00:36
      • 3.10 Partition Distribution00:48
      • 3.11 Producers00:48
      • 3.12 Consumers00:46
      • 3.13 Kafka Architecture01:10
      • 3.14 Types of Messaging Systems00:42
      • 3.15 Queue System—Example00:37
      • 3.16 Publish-Subscribe System—Example00:34
      • 3.17 Brokers00:24
      • 3.18 Kafka Guarantees00:58
      • 3.19 Kafka at LinkedIn00:54
      • 3.20 Replication in Kafka00:44
      • 3.21 Persistence in Kafka00:41
      • 3.22 Quiz
      • 3.23 Summary00:38
      • 3.24 Conclusion00:07
    • Lesson 04 - Installation and Configuration 08:53
      • 4.1 Lesson 4—Installation and Configuration00:10
      • 4.2 Objectives00:22
      • 4.3 Kafka Versions00:49
      • 4.4 OS Selection00:19
      • 4.5 Machine Selection00:34
      • 4.6 Preparing for Installation00:19
      • 4.7 Demo 1—Kafka Installation and Configuration00:05
      • 4.8 Demo 1—Kafka Installation and Configuration00:05
      • 4.9 Demo 2—Creating and Sending Messages00:05
      • 4.10 Demo 2—Creating and Sending Messages00:05
      • 4.11 Stop the Kafka Server00:40
      • 4.12 Setting up Multi-Node Kafka Cluster—Step 100:24
      • 4.13 Setting up Multi-Node Kafka Cluster—Step 200:59
      • 4.14 Setting up Multi-Node Kafka Cluster—Step 301:04
      • 4.15 Setting up Multi-Node Kafka Cluster—Step 400:36
      • 4.16 Setting up Multi-Node Kafka Cluster—Step 500:29
      • 4.17 Setting up Multi-Node Kafka Cluster—Step 601:08
      • 4.18 Quiz
      • 4.19 Summary00:33
      • 4.20 Conclusion00:07
    • Lesson 05 - Kafka Interfaces 18:17
      • 5.1 Lesson 5—Kafka Interfaces00:09
      • 5.2 Objectives00:18
      • 5.3 Kafka Interfaces—Introduction00:21
      • 5.4 Creating a Topic01:23
      • 5.5 Modifying a Topic00:36
      • 5.6 kafka-topics.sh Options00:57
      • 5.7 Creating a Message00:15
      • 5.8 kafka-console-producer.sh Options01:48
      • 5.9 Creating a Message—Example 101:01
      • 5.10 Creating a Message—Example 200:39
      • 5.11 Reading a Message00:21
      • 5.12 kafka-console-consumer.sh Options01:32
      • 5.13 Reading a Message—Example00:44
      • 5.14 Java Interface to Kafka00:18
      • 5.15 Producer Side API00:42
      • 5.16 Producer Side API Example—Step 100:32
      • 5.17 Producer Side API Example—Step 200:15
      • 5.18 Producer Side API Example—Step 300:21
      • 5.19 Producer Side API Example—Step 400:21
      • 5.20 Producer Side API Example—Step 500:17
      • 5.21 Consumer Side API00:37
      • 5.22 Consumer Side API Example—Step 100:21
      • 5.23 Consumer Side API Example—Step 200:15
      • 5.24 Consumer Side API Example—Step 300:20
      • 5.25 Consumer Side API Example—Step 400:25
      • 5.26 Consumer Side API Example—Step 500:25
      • 5.27 Compiling a Java Program00:29
      • 5.28 Running the Java Program00:18
      • 5.29 Java Interface Observations00:39
      • 5.30 Exercise 1—Tasks00:05
      • 5.31 Exercise 1—Tasks (contd.)00:05
      • 5.32 Exercise 1—Solutions00:05
      • 5.33 Exercise 1—Solutions (contd.)00:05
      • 5.34 Exercise 1—Solutions (contd.)00:05
      • 5.35 Exercise 2—Tasks00:05
      • 5.36 Exercise 2—Tasks (contd.)00:05
      • 5.37 Exercise 2—Solutions00:05
      • 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 Summary00:30
      • 5.44 Thank You00:08
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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 85% of the course.
    • 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.

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