Learning Objectives: In this module, you will understand where Kafka fits in the Big Data space, and Kafka Architecture. In addition, you will learn about Kafka Cluster, its Components, and how to Configure a Cluster
You will learn about Kafka Concepts, Kafka Installation, Configuring Kafka Cluster. At the end of this module, you should be able to:

• Explain what is Big Data
• Understand why Big Data Analytics is important
• Describe the need of Kafka
• Know the role of each Kafka Components
• Understand the role of ZooKeeper
• Install ZooKeeper and Kafka
• Classify different type of Kafka Clusters
• Work with Single Node-Single Broker Cluster

Topics:

• Introduction to Big Data
• Big Data Analytics
• Need for Kafka
• What is Kafka?
• Kafka Features
• Kafka Concepts
• Kafka Architecture
• Kafka Components
• ZooKeeper
• Where is Kafka Used?
• Kafka Installation
• Kafka Cluster
• Types of Kafka Clusters
• Configuring Single Node Single Broker Cluster

Hands on:

• Kafka Installation
• Implementing Single Node-Single Broker Cluster

Learning Objectives: Kafka Producers send records to topics. The records are sometimes referred to as Messages. In this Module, you will work with different Kafka Producer APIs. You will leartn about Configure Kafka Producer, Constructing Kafka Producer, Kafka Producer APIs, Handling Partitions. At the end of this module, you should be able to:

• Construct a Kafka Producer
• Send messages to Kafka
• Send messages Synchronously & Asynchronously
• Configure Producers
• Serialize Using Apache Avro
• Create & handle Partitions

Topics:

• Configuring Single Node Multi Broker Cluster
• Constructing a Kafka Producer
• Sending a Message to Kafka
• Producing Keyed and Non-Keyed Messages
• Sending a Message Synchronously & Asynchronously
• Configuring Producers
• Serializers
• Serializing Using Apache Avro
• Partitions

Hands on:

• Working with Single Node Multi Broker Cluster
• Creating a Kafka Producer
• Configuring a Kafka Producer
• Sending a Message Synchronously & Asynchronously

Learning Objectives: Applications that need to read data from Kafka use a Kafka Consumer to subscribe to Kafka topics and receive messages from these topics. In this module, you will learn to construct Kafka Consumer, process messages from Kafka with Consumer, run Kafka Consumer and subscribe to Topics. You will learn about Configure Kafka Consumer, Kafka Consumer API, Constructing Kafka Consumer. At the end of this module, you should be able to:

• Perform Operations on Kafka
• Define Kafka Consumer and Consumer Groups
• Explain how Partition Rebalance occurs
• Describe how Partitions are assigned to Kafka Broker
• Configure Kafka Consumer
• Create a Kafka consumer and subscribe to Topics
• Describe & implement different Types of Commit
• Deserialize the received messages

Topics:

• Consumers and Consumer Groups
• Standalone Consumer
• Consumer Groups and Partition Rebalance
• Creating a Kafka Consumer
• Subscribing to Topics
• The Poll Loop
• Configuring Consumers
• Commits and Offsets
• Rebalance Listeners
• Consuming Records with Specific Offsets
• Deserializers

Hands on:

• Creating a Kafka Consumer
• Configuring a Kafka Consumer
• Working with Offsets

Learning Objectives: Apache Kafka provides a unified, high-throughput, low-latency platform for handling real-time data feeds. Learn more about tuning Kafka to meet your high-performance needs. You will learn about Kafka APIs, Kafka Storage , Configure Broker. At the end of this module, you should be able to:

• Understand Kafka Internals
• Explain how Replication works in Kafka
• Differentiate between In-sync and Out-off-sync Replicas
• Understand the Partition Allocation
• Classify and Describe Requests in Kafka
• Configure Broker, Producer, and Consumer for a Reliable System
• Validate System Reliabilities
• Configure Kafka for Performance Tuning

Topics:

• Cluster Membership
• The Controller
• Replication
• Request Processing
• Physical Storage
• Reliability
• Broker Configuration
• Using Producers in a Reliable System
• Using Consumers in a Reliable System
• Validating System Reliability
• Performance Tuning in Kafka

Hands on:

• Create topic with partition & replication factor 3 and execute it on multi-broker cluster
• Show fault tolerance by shutting down 1 Broker and serving its partition from another broker

Learning Objectives: Kafka Cluster typically consists of multiple brokers to maintain load balance. ZooKeeper is used for managing and coordinating Kafka broker. Learn about Kafka Multi-Cluster Architectures, Kafka Brokers, Topic, Partitions, Consumer Group, Mirroring, and ZooKeeper Coordination in this module. You will learn about Administer Kafka. At the end of this module, you should be able to

• Understand Use Cases of Cross-Cluster Mirroring
• Learn Multi-cluster Architectures
• Explain Apache Kafka’s MirrorMaker
• Perform Topic Operations
• Understand Consumer Groups
• Describe Dynamic Configuration Changes
• Learn Partition Management
• Understand Consuming and Producing
• Explain Unsafe Operations

Topics:

• Use Cases – Cross-Cluster Mirroring
• Multi-Cluster Architectures
• Apache Kafka’s MirrorMaker
• Other Cross-Cluster Mirroring Solutions
• Topic Operations
• Consumer Groups
• Dynamic Configuration Changes
• Partition Management
• Consuming and Producing
• Unsafe Operations

Hands on:

• Topic Operations
• Consumer Group Operations
• Partition Operations
• Consumer and Producer Operations

Learning Objectives: Learn about the Kafka Connect API and Kafka Monitoring. Kafka Connect is a scalable tool for reliably streaming data between Apache Kafka and other systems. You will learn about: Kafka Connect, Metrics Concepts, Monitoring Kafka. At the end of this module, you should be able to:

• Explain the Metrics of Kafka Monitoring
• Understand Kafka Connect
• Build Data pipelines using Kafka Connect
• Understand when to use Kafka Connect vs Producer/Consumer API
• Perform File source and sink using Kafka Connect

Topics:

• Considerations When Building Data Pipelines
• Metric Basics
• Kafka Broker Metrics
• Client Monitoring
• Lag Monitoring
• End-to-End Monitoring
• Kafka Connect
• When to Use Kafka Connect?
• Kafka Connect Properties

Hands on:

• Kafka Connect

Learning Objectives: Learn about the Kafka Streams API in this module. Kafka Streams is a client library for building mission-critical real-time applications and microservices, where the input and/or output data is stored in Kafka Clusters. You will learn about Stream Processing using Kafka. At the end of this module, you should be able to:

• Describe What is Stream Processing
• Learn Different types of Programming Paradigm
• Describe Stream Processing Design Patterns
• Explain Kafka Streams & Kafka Streams API

Topics:

• Stream Processing
• Stream-Processing Concepts
• Stream-Processing Design Patterns
• Kafka Streams by Example
• Kafka Streams: Architecture Overview

Hands on:

• Kafka Streams
• Word Count Stream Processing

Learning Objectives: In this module, you will learn about Apache Hadoop, Hadoop Architecture, Apache Storm, Storm Configuration, and Spark Ecosystem. In addition, you will configure Spark Cluster, Integrate Kafka with Hadoop, Storm, and Spark. You will learn about Kafka Integration with Hadoop, Kafka Integration with Storm, Kafka Integration with Spark. At the end of this module, you will be able to:

• Understand What is Hadoop
• Explain Hadoop 2.x Core Components
• Integrate Kafka with Hadoop
• Understand What is Apache Storm
• Explain Storm Components
• Integrate Kafka with Storm
• Understand What is Spark
• Describe RDDs
• Explain Spark Components
• Integrate Kafka with Spark

Topics:

• Apache Hadoop Basics
• Hadoop Configuration
• Kafka Integration with Hadoop
• Apache Storm Basics
• Configuration of Storm
• Integration of Kafka with Storm
• Apache Spark Basics
• Spark Configuration
• Kafka Integration with Spark

Hands on:

• Kafka integration with Hadoop
• Kafka integration with Storm
• Kafka integration with Spark

Learning Objectives: Learn how to integrate Kafka with Flume, Cassandra and Talend. You will learn about Kafka Integration with Flume, Kafka Integration with Cassandra, Kafka Integration with Talend. At the end of this module, you should be able to:

• Understand Flume
• Explain Flume Architecture and its Components
• Setup a Flume Agent
• Integrate Kafka with Flume
• Understand Cassandra
• Learn Cassandra Database Elements
• Create a Keyspace in Cassandra
• Integrate Kafka with Cassandra
• Understand Talend
• Create Talend Jobs
• Integrate Kafka with Talend

Topics:

• Flume Basics
• Integration of Kafka with Flume
• Cassandra Basics such as and KeySpace and Table Creation
• Integration of Kafka with Cassandra
• Talend Basics
• Integration of Kafka with Talend

Hands on:

• Kafka demo with Flume
• Kafka demo with Cassandra
• Kafka demo with Talend

Apache Kafka Certification Training is designed to provide you with the knowledge and skills to become a successful Kafka Big Data Developer. The training encompasses the fundamental concepts (such as Kafka Cluster and Kafka API) of Kafka and covers the advanced topics (such as Kafka Connect, Kafka streams, Kafka Integration with Hadoop, Storm and Spark) thereby enabling you to gain expertise in Apache Kafka.

After the completion of Real-Time Analytics with Apache Kafka course at CertAdda, you should be able to:

• Learn Kafka and its components
• Set up an end to end Kafka cluster along with Hadoop and YARN cluster
• Integrate Kafka with real time streaming systems like Spark & Storm
• Describe the basic and advanced features involved in designing and developing a high throughput messaging system
• Use Kafka to produce and consume messages from various sources including real time streaming sources like Twitter
• Get an insight of Kafka API
• Understand Kafka Stream APIs
• Work on a real-life project, ‘Implementing Twitter Streaming with Kafka, Flume, Hadoop & Storm

Kafka training helps you gain expertise in Kafka Architecture, Installation, Configuration, Performance Tuning, Kafka Client APIs like Producer, Consumer and Stream APIs, Kafka Administration, Kafka Connect API and Kafka Integration with Hadoop, Storm and Spark using Twitter Streaming use case.

This course is designed for professionals who want to learn Kafka techniques and wish to apply it on Big Data. It is highly recommended for:

• Developers, who want to gain acceleration in their career as a “Kafka Big Data Developer”
• Testing Professionals, who are currently involved in Queuing and Messaging Systems
• Big Data Architects, who like to include Kafka in their ecosystem
• Project Managers, who are working on projects related to Messaging Systems
• Admins, who want to gain acceleration in their careers as a “Apache Kafka Administrator

Fundamental knowledge of Java concepts is mandatory. CertAdda provides a complimentary course i.e., “Java Essentials” to all the participants, who enrolls for the Apache Kafka Certification Training

• Minimum RAM required: 4GB (Suggested: 8GB)
• Minimum Free Disk Space: 25GB
• Minimum Processor i3 or above
• Operating System of 64bit
• Participant’s machines must support a 64-bit VirtualBox guest image.

We will help you to setup CertAdda’s Virtual Machine in your System with local access. The detailed installation guides are provided in the LMS for setting up the environment. For any doubt, the 24*7 support team will promptly assist you. CertAdda Virtual Machine can be installed on Mac or Windows machine.

• Case Study 1: Stock Profit Ltd, India’s first discount broker, offers zero brokerage & unlimited online share trading in Equity Cash. Design a system to capture real-time stocks data from source (i.e. Yahoo.com) and calculate the profit and loss for customers who are subscribed to the tool. Finally, store the result in HDFS.
• Case Study 2: You are a SEO specialist in a company. You get an email from management wherein the requirement is to get Top Trending Keywords. You have to write the topology which can consume keywords from Kafka. You have given a file containing various search keywords across multiple verticals.
• Case Study 3: You have to build a system which should be consistent in nature. For example, if you are getting product feeds either through flat file or any event stream you have to make sure you don’t lose any events related to product specially inventory and price. If we talk about price and availability it should always be consistent because there might be possibility that product is sold or seller doesn’t want to sell it anymore or any other reason. However, attributes like Name, description doesn’t make that much noise if not updated on time.
• Case Study 4: John wants to build an e-commerce portal like Amazon, Flipkart or Paytm. He will ask sellers/local brands to upload all their products on the portal so that users/buyers can visit portal online and purchase. John doesn’t have much knowledge about the system and he hired you to build a reliable and scalable solution for him where buyers and sellers can easily update their products.

• Project-1:
  • Goal: In this module, you will work on a project, which will be gathering messages from multiple sources.
  • Scenario: In E-commerce industry, you must have seen how catalog changes frequently. Most deadly problem they face is “How to make their inventory and price consistent?”. There are various places where price reflects on Amazon, Flipkart or Snapdeal. If you will visit Search page, Product Description page or any ads on Facebook/google. You will find there are some mismatch in price and availability. If we see user point of view that’s very disappointing because he spends more time to find better products and at last if he doesn’t purchase just because of consistency. Here you have to build a system which should be consistent in nature. For example, if you are getting product feeds either through flat file or any event stream you have to make sure you don’t lose any events related to product specially inventory and price. If we talk about price and availability it should always be consistent because there might be possibility that the product is sold or the seller doesn’t want to sell it anymore or any other reason. However, attributes like Name, description doesn’t make that much noise if not updated on time.
  • Problem Statement: You have given set of sample products. You have to consume and push products to Cassandra/MySQL once we get products in the consumer. You have to save below-mentioned fields in Cassandra.
    • PogId
    • Supc
    • Brand
    • Description
    • Size
    • Category
    • Sub Category
    • Country
    • Seller Code

    In MySQL, you have to store

    • PogId
    • Supc
    • Price
    • Quantity
• Certification Project:
  • Goal: This Project enables you to gain Hands-On experience on the concepts that you have learned as part of this Course. You can email the solution to our Support team within 2 weeks from the Course Completion Date. CertAdda will evaluate the solution and award a Certificate with a Performance-based Grading.
  • Problem Statement: You are working for a website techreview.com that provides reviews for different technologies. The company has decided to include a new feature in the website which will allow users to compare the popularity or trend of multiple technologies based on twitter feeds. They want this comparison to happen in real time. So, as a big data developer of the company, you have been task to implement following things:
    • Near Real Time Streaming of the data from Twitter for displaying last minute’s count of people tweeting about a particular technology.
    • Store the twitter count data into Cassandra.

You will never miss a lecture at CertAdda You can choose either of the two options: View the recorded session of the class available in your LMS or You can attend the missed session, in any other live batch.

To help you in this endeavor, we have added a resume builder tool in your LMS. Now, you will be able to create a winning resume in just 3 easy steps. You will have unlimited access to use these templates across different roles and designations. All you need to do is, log in to your LMS and click on the “create your resume” option.

We have limited number of participants in a live session to maintain the Quality Standards. So, unfortunately participation in a live class without enrollment is not possible. However, you can go through the sample class recording and it would give you a clear insight about how are the classes conducted, quality of instructors and the level of interaction in a class.

All the instructors at CertAdda are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by CertAdda for providing an awesome learning experience to the participants.

Just give us a CALL at +91 8178510474 / +91 9967920486 OR email at admin@certadda.com

Apache Kafka is one of the most popular publish subscribe messaging systems which is used to build real-time streaming data pipelines that are robust, reliable, fault tolerant & distributed across a cluster of nodes. Kafka supports a variety of use-cases which commonly include Website activity tracking, messaging, log aggregation, Commit log & stream processing. These are reasons why many giants such as Airbnb, PayPal, Oracle, Netflix, Mozilla, Uber, Cisco, Coursera, Spotify, Twitter, Tumblr are looking for professionals with Kafka skills. Getting Kafka certified will help you land your dream job.

CertAdda’s Apache Kafka Certification Training is curated by industry experts and it covers in-depth knowledge on Kafka Producer & Consumer, Kafka Internals, Kafka Cluster Architecture, Kafka Administration, Kafka Connect & Kafka Streams. Throughout this online instructor-led Kafka Training you will be working on real-world Kafka use-cases belonging to finance, marketing and e-commerce domain, etc.

Technology Giants & MNCs such as Airbnb, PayPal, Oracle, Netflix, Mozilla, Uber, Cisco, Coursera, Spotify, Twitter & Tumblr are looking for Kafka certified professionals. Not only this, SMEs are also using Apache Kafka to build real-time streaming data pipelines. This will also lead to exponential growth in number of Kafka jobs available in the market.

To master Apache Kafka, you need to learn all the concepts related to Apache Kafka – Kafka Architecture, Kafka Producer & Consumer, Configuring Kafka Cluster, Kafka Monitoring, Kafka Connect & Kafka Streams. Knowledge of Kafka integration with other Big Data tools such as Hadoop, Flume, Talend, Cassandra, Storm and Spark will be a plus point.

With the growth of Big Data and advent of Microservices the adoption of Apache Kafka is increasing exponentially. But the there is a huge lack of professionals with Kafka skills. If you are planning to make a career in Big Data domain, now is the right time to get Kafka certified. Get certified get ahead.

Apache Kafka Certification Training costs $390. Once you enroll with CertAdda you get lifetime access to the course materials & a dedicated team of support ninjas who will be available 24×7 to clarify all your doubts & help you in executing your assignments & case-studies.

CertAdda Apache Kafka Certification Training is designed in such a way that it caters to both beginners & experts. You can leverage instructor’s knowledge who will be available throughout the training and will help you in understanding each concept thoroughly. Apart from that, we have 24×7 online support team to resolve all your technical queries.

As the technology is evolving the learning techniques are also enhancing. Flexibility & Quality are the two important pillars of online training. The major benefits of an online Kafka Training over offline training are:

• Latest Course Curriculum: The course curriculum frequently updates with changing industry demands & software updates.
• Quality Instructors: You can connect & learn, each & every nuance of the technology from an expert around the world.
• Learner’s Platform: You can connect with various learners across the globe & share your learning & ideas with them.
• Real-life Projects & Case Studies: You will master the technology with the help of real-world projects & case studies.
• Lifetime Access & 24×7 support: You will get lifetime access to the course content & 24×7 support for any doubts or errors.

There are a lot of job opportunities for Apache Kafka professionals as it is adopted by both SME & big giants. The average salary of a Software Engineer with Kafka skills is $110,209 whereas a Senior Software Engineer and a Lead Software Engineer can expect average salaries of $131,151 and $134,369 respectively.