About The Course
The LearnChase Ambari training is designed to provide the requisite knowledge and skills to become a successful Hadoop Administrator. The course starts with the fundamental concepts of Hadoop and management tools and includes advanced topics around tuning and tweaking of the Hadoop cluster.
After the completion of the Ambari course at LearnChase, you will be able to:
1. Understand and identify different management tools
2. Describe Ambari architecture and its various components
3. Use Ambari components to build the cluster, add nodes and remove nodes seamlessly
4. Describe the basic and advanced features and functionalities of Ambari along with use cases
Who should go for this course?
The course is designed for all those who want to learn Apache Ambari. It is suitable especially for:
1. DevOps specialists or administrators who want to boost their careers and become Hadoop Administrators
2. DBA s who are subject matter experts, working in jobs around large clusters
3. Testing specialists around Mainframe or Java
Why learn Apache Ambari?
The Apache Ambari training equips you with in-demand skill around of Hadoop Administration and helps you grab high paying Hadoop Admin jobs.
Which Case-Studies will be a part of the Course?
Towards end of the course, participants will work on a live project using the Ambari wizards interface to perform implementation and designing of Big Data clusters.
Create a 3-Node Hadoop Cluster with these configurations using Ambari:
Node 1/2: Ambari master / slaves
Node 3: Ambari Agent/Masters
Perform the following activities in the Node Cluster using Ambari:
1. Adding an additional node and removing one
2. Removing some services
3. Adding new services
What are the pre-requisites for this Course?
The pre-requisites for this course include knowledge on management tools architecture, general relational databases (Oracle), Hadoop, and Basic Unix.
1. Getting started with Ambari
Learning Objectives – In this module, you will get an overview of Ambari, We will find out the various use cases of Ambari, why we use it, the different kinds of managing tools present in the market, and more. We will also learn about the prequisites for ambari and its industry relevance.
Topics – Introduction to the course, What is Ambari? Types of managing tools, Pre-requisites and Working of managing tools (Ambari).
2. Ambari Architecture / Installations
Learning Objectives – In this module, you will learn the internals of Ambari and its architecture. The objectives include installation of Hadoop and its ecosystem and to find out the various tasks related to the implementation of the Hadoop ecosystem.
Topics – Setting up Ambari and related tools, tasks in Ambari, installation of Hadoop, installation of different components of Hadoop and service management.
3. Using Ambari Client/Server
Learning Objectives – In this module, you will learn about Ambari Web UI, how to take the administration control of the cluster through, creating a Hadoop cluster and manage its Users, Groups and different Views.
Topics – Understanding of Ambari UI, administering Ambari, creating a cluster, managing users, groups and views.
4. Management with Ambari
Learning Objectives – In this module, you will learn about accessing the Ambari Web. We will learn the management of Services and Hosts. We will learn about Stacks and version management capabilities of Ambari. Also, learn how to set up Monitoring and Alerting through Ambari.
Topics – Accessing Ambari Web, service management, hosts managements, stacks and versions management, alerts and monitoring management.
5. Ambari Advance topics and Security
Learning Objectives – In this module, you will learn advanced topics around managing a Hadoop installation or cluster for fine-tuning its performance and several other administrative configurations such as Hadoop Security, database security, Ldap, memory optimization and troubleshooting.
Topics – TroubleShooting through Ambari, Reviewing logs and general Issues, Configuration of Security, Kerberos setup, Implementation of Ldap, Implement Security on Databases and Passwords, Performance optimization and Memory optimization.
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- 0 Units
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