Apache Storm Certification Training

Apache Storm is an open-source and distributed stream processing computation framework used for processing large volumes of high-velocity data. This training will help you learn reliable real-time data processing capabilities of Storm and, how Storm is different from Hadoop & Kafka. You can smartly use Apache Storm at various place such as Ecommerce, Supply chain, Streaming etc.

Original price was: $259.00.Current price is: $181.00.

Online self paced classes

Online Self Learning Courses are designed for self-directed training, allowing participants to begin at their convenience with structured training and review exercises to reinforce learning. You’ll learn through videos, PPTs and complete assignments, projects and other activities designed to enhance learning outcomes, all at times that are most convenient to you.

Introduction to Big Data and Real Time Big data processing

Learning Objetives: In this module, you will learn about Big Data and how it is solving real problems. At the end of this module, you should be able to:

  • Explain the use of Big data
  • Difference between Batch and Real-time Processing
  • How Apache Storm can be helpful for Real-time processing


  • Big Data
  • Hadoop
  • Batch Processing
  • Real-time analytics
  • Storm origin
  • Architecture
  • Comparison with Hadoop and Spark


  • Batch processing vs real-time processing
  • Aggregating click and impression data from different streams
  • Trending search on any e-commerce portal
  • Twitter Streaming

Storm Installation and groupings

Learning Objetives: In this module, you will learn How to install Storm and various Groupings architecture. At the end of this module, you should be able to:

  • Install Apache Storm in cluster mode
  • Nimbus, Supervisor and Worker Nodes
  • Groupings in Storm


  • Installation of Storm
  • Nimbus Node
  • Supervisor Nodes
  • Worker Nodes
  • Running Modes
  • Local Mode
  • Remote Mode
  • Stream Grouping
  • Shuffle Grouping
  • Fields Grouping
  • All Grouping
  • Custom Grouping
  • Direct Grouping
  • Global Grouping
  • None Grouping


  • Setting up Storm Custer
  • Various Components of Cluster
  • Storm Grouping

Storm Spouts & Bolts

Learning Objetives: In this module, you will learn more about internal components of Storm and their working. You will be able to use Spouts and bolts and their mechanisms. Different type of Spouts and their working. Lifecycle of bolts and it’s working. At the end of this module, you should be able to:

  • Spouts and how to create your custom Spout
  • Different types of Bolts and working


  • Basic components of Apache Storm
  • Spout
  • Bolts
  • Running Mode in Storm
  • Reliable and unreliable messaging
  • Spouts
  • Introduction
  • Data fetching techniques
  • Direct Connection
  • Enqueued message
  • DRPC
  • How to create custom Spouts
  • Introduction to Kafka Spouts
  • Bolts
  • Bolt Lifecycle
  • Bolt Structure
  • Reliable and Unreliable Bolts
  • Basic topology example using Spout and bolts
  • Storm UI


  • Trending Search topology
  • You will be given file of various search keywords you have to find top 10 search keywords in last 60 seconds at any moment.

Kafka Introduction

Learning Objetives: In this module, you will learn about Apache Kafka, A highly scalable and widely used event messaging system. How it works and it’s high level components. At the end of this module, you should be able to:

  • Set up Kafka and familiar with produce and consumer
  • Kafka Spout in Apache Storm


  • What is Apache Kafka?
  • Setting up Standalone Kafka
  • How to use Kafka Producer
  • How to use Kafka Consumer
  • Hand on Kafka
  • How Kafka Spout works in Apache Storm and its configuration


  • Given a file of search keywords you have to produce and consume from Kafka.
  • Extension of previous case study: Keyword source will be Kafka Spout not file.

Trident Topology

Learning Objetives: In this module, you will learn about Trident topology. Performing complex transformations on the fly using the Trident topology: Map, Filter, Windowing and Partitioning operations. At the end of this module, you should be able to:

  • Trident in Apache Storm
  • Understanding Trident topology for failure handling, process
  • Understanding of Trident Spouts and its different types, the various Trident Spout interface and components, familiarizing with Trident Filter, Aggregator and Functions.


  • Trident Design
  • Trident in Storm
  • RQ Class, Coordinator, Emitter bolt
  • Committer Bolts, Partitioned Transactional Spouts
  • Transaction Topologies


  • Twitter Data Analysis using Trident

Practical of Apache Storm

Learning Objetives: In this module, you will work on industry level project. Design and its development. At the end of this module, you should be able to:

  • Set up Apache Storm cluster
  • Configuring Spout a Bolts
  • Developing topology
  • How to use Cassandra and Mongo in Apache Storm


  • Product Catalog management system


  • Catalogue management system: You are getting product details and you have to send same data to multiple systems like Solr, Mongo, Cassandra, HDFS or MySQL etc. You have to develop topology which can perform the task.

About the course

The course is designed to introduce you to the concept of Apache Storm and explain the fundamentals of Storm. The course will provide an overview of the structure and mechanism of Storm. Learn about Apache Storm, its architecture and concepts. You will get familiar with Both standalone and cluster setup of Apache Storm. Storm topology, how it can be used in various real-time streaming use cases. Different components of Apache storm which includes Spouts and Bolts. How Storm can be used in Distributed Computing. Difference between Storm and Hadoop. Real-time processing and batch processing. Working on some industrial use cases of Storm.

What are the objectives of this course?

After completing this Training, you should be able to:

  • Introduction to Big Data and Real Time Big data processing
  • Batch Processing vs Real time Processing
  • Comparison with Hadoop and Spark
  • Installation of Storm
  • Various Grouping in Storm
  • Storm Spouts & Bolts
  • Basic components of Apache Storm and their working
  • Basic topology example using Spout and bolts
  • Kafka Introduction
  • Trident Topology
  • Transaction Topologies
  • Practical Case Studies

Why Learn Storm?

Apache Storm is a free and open source distributed real-time computation system. Storm makes it easy to reliably process unbounded streams of data, doing for real-time processing what Hadoop did for batch processing. Storm is simple, can be used with any programming language, and is a lot of fun to use! Storm has many use cases: real-time analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.

Who should go for this course?

This course is designed for professionals aspiring to make a career in Real-Time Big Data Analytics using Apache Storm and the Hadoop Framework

  • Software Professionals, Data Scientists, ETL developers and Project Managers are the key beneficiaries of this course.
  • Other professionals who are looking forward to acquiring a solid foundation of Apache Storm Architecture can also opt for this course.

What are the pre-requisites for this course?

Development experience with an object-oriented language is required. Also, fundamentals of networking and basic knowledge of command line& Linux would be advantageous. Experience with Java, git, Kafka will be beneficial. We have the following Courses that can be helpful –

  • Linux Fundamentals
  • Java certification training
  • Kafka training

What are the system requirements for this course?

The requirement for this course is a system with Intel i3 processor or above, minimum 8GB RAM and 25 GB HDD Storage, Chrome (latest version) / Mozilla with firebug (latest version), Java, Apache Storm and Kafka.

How will I execute the practicals?

For Practical’s, we will help you to install and setup virtual machine with Ubuntu as the client using the Installation Guide. The detailed installation guides are provided in the LMS for setting up the environment and will be addressed during the session. In case you come across any doubt, the 24*7 support team will promptly assist you.

What if I miss a class?

You will never miss a lecture at Edureka! 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.

Will I get placement assistance?

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.

Can I attend a demo session before enrollment?

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.

Who are the instructors?

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

What if I have more queries?

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

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