Published on Dec 15,2016
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Apache Hadoop jobs have increased at an average rate of 34% over the last four years, and out of the Hadoop jobs currently available, 88% are technology based, according to a survey by Cebglobal (Survey Sample: UK).  Today, Apache Ambari is  one of the most intuitive open source tools in the market that helps manage Hadoop. Consequently, it is a  thriving platform for big data careers.

Apache Ambari is an all-encompassing open-source tool and framework that is used to provision, manage, and monitor Hadoop clusters. With its easy-to-use web-based user interface or through making use of its collection of RESTful APIs, it brings everything in the Hadoop ecosystem under one roof.

Five reasons to learn Apache Ambari

Here are the top five reasons why getting trained in Apache Ambari should be your next plan of action if you want to bag your dream big data job.

1. Simplicity:

The crux of Ambari’s web interface is simplicity. The goal of Ambari is to make provisioning, managing, and monitoring as seamless and easy to use as possible. Ambari APIs can be used to automate a cluster installation with  zero user interaction. Moreover, Ambari is designed with a ‘server-agent’ type architecture. There is a single Ambari server that is installed and run on one host. This server is the single entry point to the cluster, which runs the web user interface, and provides Ambari’s RESTful APIs. Ambari also simplifies manual provisioning to a great extent. Provisioning is usually a long and tedious process, but with Apache Ambari, you can just pick the hosts you want to initially use for the cluster, select what services to be installed (HDFS, Hbase, Pig, ZooKeeper, etc.), specify what hosts should be the master, client, or slave for the specified Hadoop services, review the installation configuration, and then launch .

2. Lifecycle Management Format:

Ambari’s excellent managing capability is centered on a lifecycle management format. Any service that has been integrated to work with Ambari responds to defined lifecycle commands i.e. start, stop, status, install and configure. Ambari has the seamless flexibility to add, remove, or reconfigure services at any time.

Lifecycle management in Ambari is truly intuitive. Hadoop ecosystem is constantly transforming with software changes and Ambari enables hassle-free adoption of these changes.

3. Unparalleled Management Capabilities:

Ambari has unparalleled management capabilities and there is null chance that the Hadoop ecosystem can be managed in a better way. Here is a list of some of the unique capabilities that Ambari provides:

  1. Stop, start, restart, add, or remove services
  2. Add or remove hosts to a cluster
  3. Put specific hosts or the entire cluster in maintenance mode
  4. Move a name node or secondary name node to a different host
  5. Restart the entire cluster using rolling restarts
  6. Run service checks to verify service running and responding
  7. Decommission or recommission data nodes
  8. Edit service and component configurations
  9. Rollback configurations
  10. View history of past configuration changes
  11. Restart services after configuration changes
  12. Define host configuration groups for better management
  13. Search for specific hosts by name, IP address, hardware specs, or services installed
  14. Automation and integration

Let’s elaborate on No. 14. There are three pieces to automation and integration: Ambari Stacks, Ambari Blueprints, and the Ambari API.

  • Stacks

Ambari Stacks provide a way to define a group of services together by describing

  1. A set of available services that can be installed
  2. Where the service software packages can be found (repos), and
  3. Specific information for various services (HDFS, Zookeeper, HBase, etc.).The advantage of stacks is that they are extensible and support versioning.
  • Blueprints

An Ambari Blueprint is a declarative way to define how to form a cluster install from scratch in a programmed way. A blueprint can contain configuration settings for explicit services but the heart of a blueprint contains all host and all concomitant services. All it takes to automate a cluster install is registering a valid Ambari blueprint with the Ambari server, then making an API call to start the installation.

  • API

The API can be used for automating everything related to provisioning and managing or for integrating Ambari’s authority into additional existing systems. The web interface strictly uses Ambari’s APIs for everything you see on the screen and everything that occurs in the background.

4. Career Progression and Opportunities:

The average salary offered for Apache Ambari skills in 2016 has seen a growth of 12.5% over the previous year. (Source:

The graph below shows that the hiring demand for Hadoop has been growing and thus Apache Ambari training open the doors to a lucrative big data career.


(Source: CEB Global)

The demand trend of job ads citing Ambari as a proportion of all IT jobs with a match in the Systems Management category has shown exponential growth over the last four years.



Start your Apache Ambari training with Edureka and become a successful Hadoop Administrator! The Edureka Ambari course is designed to help you understand fundamental concepts of Hadoop and management tools. The course also includes advanced topics such as tuning and tweaking of the Hadoop cluster. To check out the course, click here!

Got a question for us? Please mention it in the comments section and we will get back to you.

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Shradha Sethi
Published on Dec 15,2016

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