Introduction

Apache Ambari is a web-based tool for installing, managing, and monitoring Apache Hadoop clusters. The set of Hadoop components that are currently supported by Ambari includes:

• Apache HBase
• Apache HCatalog
• Apache Hadoop HDFS
• Apache Hive
• Apache Hadoop MapReduce
• Apache Oozie
• Apache Pig
• Apache Sqoop
• Apache Templeton
• Apache Zookeeper

Ambari's primary audience is system administrators responsible for managing Hadoop clusters.

Ambari allows them to:

• Easily Install a Hadoop Cluster
  • Ambari provides an easy-to-use, step-by-step wizard for installing Hadoop services across any number of nodes.
  • Ambari leverages Puppet to perform installation and configuration of Hadoop services for the cluster.

• Manage a Hadoop Cluster
  • Ambari provides central management for starting, stopping, and reconfiguring Hadoop services across the entire cluster.

• Monitor a Hadoop Cluster
  • Ambari provides a dashboard for monitoring health and status of the Hadoop cluster. Ambari leverages Ganglia to collect system metrics.
  • Ambari sends email alerts when your attention is needed (e.g., a node goes down, remaining disk space is low, etc). Ambari leverages Nagios to monitor and trigger alerts.

In the near future, Ambari will allow third-party tool developers to integrate Hadoop cluster management and monitoring capabilities via its RESTful interface.

Ambari Installation

Follow the installation guide for 0.9 (stable) or installation guide for trunk.

Roadmap

• Support for Hadoop Security

• Support for various operating systems
  • Ambari currently supports 64-bit RHEL/CentOS 5.* and 6.*
  • Support for other operating systems are being worked on (SLES 11.* support will be coming soon)

• RESTful API for third-party integration
  • Ambari will expose a unified, RESTful API to enable third-party applications to integrate Hadoop cluster management and monitoring capabilities. This is an area of active development. We will publish the API docs soon.

• Granular configurations
  • Ambari currently applies configurations at the cluster-level. To allow for more flexibility, Ambari will allow for configurations in a more granular manner (e.g., apply a set of configurations to a specific group of nodes, etc.)

• Security
  • Easy installation of secure Hadoop clusters (Kerberos-based)
  • Role-based user authentication, authorization, and auditing
  • Support for LDAP and Active Directory

• Visualization
  • Interactive visualization of current and historical states of the cluster for a number of key metrics
  • Interactive visualization of Pig, Hive, and MapReduce jobs