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Apache Ambari

A completely open source management platform for provisioning, managing, monitoring and securing Apache Hadoop clusters. Apache Ambari takes the guesswork out of operating Hadoop.

Apache Ambari, as part of the Hortonworks Data Platform, allows enterprises to plan, install and securely configure HDP making it easier to provide ongoing cluster maintenance and management, no matter the size of the cluster.

What Ambari Does

Ambari makes Hadoop management simpler by providing a consistent, secure platform for operational control. Ambari provides an intuitive Web UI as well as a robust REST API, which is particularly useful for automating cluster operations. With Ambari, Hadoop operators get the following core benefits:

  • Simplified Installation, Configuration and Management. Easily and efficiently create, manage and monitor clusters at scale. Takes the guesswork out of configuration with Smart Configs and Cluster Recommendations.
  • Centralized Security Setup. Reduce the complexity to administer and configure cluster security across the entire platform. Helps automate the setup and configuration of advanced cluster security capabilities such as Kerberos and Apache Ranger.
  • Full Visibility into Cluster Health. Ensure your cluster is healthy and available with a holistic approach to monitoring. Configures predefined alerts — based on operational best practices — for cluster monitoring. Captures and visualizes critical operational metrics for analysis and troubleshooting. Integrated with Hortonworks SmartSense for proactive issue prevention and resolution.
  • Highly Extensible and Customizable. Enables Hadoop to fit seamlessly into your enterprise environment. Highly extensible with Ambari Stacks for bringing custom services under management, and with Ambari Views for customizing the Ambari Web UI.

Collaboration and Focus

Hortonworks is focused on going to market with a 100% open source solution. This focus allows us to collectively provide the product management guidance for Enterprise Grade Hadoop to mainstream enterprises and our partner ecosystem, and further innovate the core of Hadoop.

  • OpenDeliver a complete set of features for Hadoop operations, in public and with the community, by defining the operational framework and lifecycle.
  • IntegratedEnsure that Hadoop operations can be integrated with existing IT tools, behind a single pane of glass, by providing REST APIs and multiple views of the cluster.
  • IntuitiveMake Hadoop’s most complex operational challenges easy to manage with more insight and visibility into cluster performance.

The community will continue to innovate Ambari so that its operational capabilities keep pace with Hadoop’s ever-expanding functionality for data management, data access, governance and security.

It is exciting to see Ambari come together and we are very interested in hearing feedback as these contributions mature. Therefore, we have made the Ambari Operations and User Views available within the Hortonworks Sandbox to make it easier for you to try them out.  For questions and feedback on Ambari operations please post to the Ambari Forum. If you have questions or feedback on the User Views please post them to the Ambari User View Forum.

Recent Improvements

Apache Ambari 2.2, which is part of the Hortonworks Data Platform (HDP) 2.4 release, serves as the management system for enterprises looking to easily and securely adopt HDP. Ambari simplifies the experience of provisioning, managing, monitoring, securing and troubleshooting Apache Hadoop deployments. Ambari removes the manual — often error prone — tasks associated with operating Hadoop. It also provides the necessary customization “hooks” to fit seamlessly into the enterprise, and enables the IT Operator to focus on delivering world-class service and support for their consumers of the Hortonworks Data Platform.

Advanced Metrics Visualization & Dashboarding

The Ambari Metrics system provides a scalable low-latency storage system to capture the metrics data emitted from Hadoop. Understanding which specific metrics to look at for each of the Hadoop components takes experience and understanding of how the components work themselves and with each other.

To help simplify the process of reviewing metrics, and to be more prescriptive about which metrics to look at, Ambari 2.2 now including Grafana with Ambari Metrics for an advanced metrics visualization & dashboarding experience. Grafana is the leading graph and dashboard builder for visualizing time series metrics, and the integration of Grafana with Ambari Metrics brings the most important and valuable cluster metrics front-and-center. This makes is easier for the Hadoop Operator to troubleshoot cluster operations. With this new feature, the Hadoop Operator can:

  • Isolate the most critical metrics for critical cluster services such as HDFS, YARN, HBase for simpler troubleshooting.
  • Gain advanced visualization of cluster health and performance metrics through pre-built dashboards.
  • Reduce time to troubleshoot a problem and deliver an improved level of service for cluster users.

Example of the HDFS NameNode Dashboard highlights file system activity.

HDFS_NameNode

More Flexible Cluster Upgrades

As enterprises everywhere adopt Hadoop, they deploy more and more mission-critical analytic applications. This makes upgrading a system as diverse as Hadoop can be a daunting task. But with Ambari, Hadoop operators can easily upgrade their cluster to the latest software release in an automated, repeatable fashion.

Ambari 2.2 introduces a new Express Upgrade option that provides a faster way to upgrade your cluster with less prerequisites than the traditional Rolling Upgrade option.

  • A Rolling Upgrade orchestrates the HDP upgrade in an order that is meant to preserve cluster operation and minimize service impact during upgrade. This process has more stringent prerequisites (particularly regarding cluster high availability configuration) and can take longer to complete than an Express Upgrade.
  • An Express Upgrade orchestrates the HDP upgrade in an order that will incur cluster downtime but with less stringent prerequisites.

Having both Rolling Upgrade and Express Upgrade options provides the choice and flexibility to upgrade your cluster based on your specific deployments needs.

Simplified Security Configuration

Ambari provides automated features to setup and configure the comprehensive security capabilities that are used to protect the cluster.

  • Kerberos has long been the central technology for enabling strong authentication for Hadoop. Its configuration posed quite a challenge creating the principals and keytabs, and providing the ongoing maintenance of those artifacts. To solve those challenges, Ambari offers options for automated Kerberos setup to accommodate the most stringent enterprise environments. The Ambari “wizard-driven” Kerberos configuration approach eliminates time-consuming Kerberos administration tasks.
  • Apache Ranger is a critical cluster security component for defining and enforcing cluster security policies. Ambari includes support for installing and configuring Apache Ranger for centralized security administration, authorization and audit.

Ambari 2.2 introduces two new capabilities that serve to further simplify the experience of configuring and managing Ranger and Kerberos.

  • Ranger Guided Configurations. Built on Ambari Smart Configs framework, the Ranger configuration and management experience includes new UI controls and improved organization and layout to make setup of Ranger easier than even.
  • Manage Kerberos Credentials. Safety store and manage the KDC Admin credentials to simplify the administration of Kerberos when you modify your cluster.

Improved Troubleshooting

Having full visibility into the service health and availability of your cluster is critical for any enterprise. Ambari configures predefined alerts — based on operational best practices — for cluster monitoring that can seamlessly integrate with your existing enterprise monitoring tools. Ambari also automatically configures the collection of cluster operational metrics to aid with analysis and troubleshooting.

Ambari 2.2 has added new capabilities that make accessing the cluster operational metrics easier.

  • Customizable Time Range for Metric Graphs. Customize time range display to view operational activity so you can pin-point problems and perform root cause analysis.
  • Export Metric Graph Data. Easily export Ambari metrics data in CSV or JSON format for further analysis and to build custom reports.

Ambari User Views

It’s time to put a new face on Hadoop using the Ambari Views framework.A “view” is a way of extending Ambari that allows 3rd parties to plug in new resource types along with the APIs, providers and UI to support them.  Ambari is the only open source and open community effort designed to provide a compelling user experience for Hadoop while delivering consistent lifecycle management and security.

Most notably, there are the Ambari User Views contributions actively being worked in the community. Ambari User Views are designed to provide capabilities that assist with the operational aspects of data application development and workload management. .

User View Description
Tez The Tez View helps you understand and optimize your cluster resource usage. Using the view, you can optimize and accelerate individual SQL queries or Pig jobs to get the best performance in a multi-tenant Hadoop environment.
Hive Hive View allows the user to write & execute SQL queries on the cluster. It shows the history of all Hive queries executed on the cluster whether run from Hive view or another source such as JDBC/ODBC or CLI. It also provides graphical view of the query execution plan. This helps the user debug the query for correctness and for tuning the performance. It integrates Tez View that allows the user to debug any Tez job, including monitoring the progress of a job (whether from Hive or Pig) while it is running. This view contribution can be found here.
Pig Pig View is similar to the Hive View. It allows writing and running a Pig script. It has support for saving scripts, and loading and using existing UDFs in scripts. This view contribution can be found here.
Capacity Scheduler Capacity Scheduler View helps a Hadoop operator setup YARN workload management easily to enable multi-tenant and multi-workload processing. This view provisions cluster resources by creating and managing YARN queues. This view contribution can be found here.
Files Files View allows the user to manage, browse and upload files and folders in HDFS. This view contribution can be found here.

Beyond these out of the box User Views there is a growing ecosystem of Ambari User Views that are being developed by the community.  You can find community User Views in the Hortonworks Gallery.

Recent Ambari Releases

Download Ambari 2.2 and Learn More

For additional details about this release review the following resources:

Ambari Version Notable Enhancements
2.2
  • Advanced Metrics Visualization and Dashboards
  • HDP Express Upgrade for fast cluster upgrades
  • Ranger Guided Configurations for Simplified Security Setup
  • Improved capabilities for accessing cluster metrics
  • SmartSense Automatic Installation
2.1
  • Guided Configurations
  • Customizable Dashboards
  • RHEL/CentOS 7 Support
  • JDK 1.8 Support
2.0
  • Automated Rolling Upgrades for HDP
  • Simplified Kerberos Setup
  • Ranger and Spark support
  • Ambari Alerts & Ambari Metrics
  • New Tez View
1.7.0
  • Configuration versioning and history
  • Introduced the Ambari Stacks “Stack Advisor” for configuration validation
  • Introduced Ambari Views Framework for customizable user interfaces
1.6.0
  • Introduced Ambari Blueprints for automating cluster installs
  • Improved usability guardrails with more host and environment checks
  • Support for PostgreSQL database

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