Apache Ambari started as a sub-project of Hadoop but currently it enjoys the distinction of being a top-level Apache project. Due to the increasing size and complexities of Hadoop clusters with each passing day, the management of these Hadoop frameworks becomes a highly challenging task. This is where the Ambari framework stepped in to simplify the whole process of Hadoop cluster provisioning, managing and monitoring and bring in an extremely efficient system of Hadoop deployment for ever-increasing loads of Big Data applications.
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Ambari is part of the Apache Software Foundation and it provides a highly intuitive way to handle Hadoop systems using web user interface thanks to the RESTful APIs offered as part of the Hortonworks Data Platform. Business enterprises can easily plan and install the Hortonworks Data Platform and deploy Ambari for Hadoop cluster maintenance and monitoring regardless of the size and complexity of applications. Ambari clearly puts the power in the hands of Hadoop administrators by simplifying their tasks.
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Some of the ways in which Ambari helps are as below:
Hadoop cluster provisioning
You can now install Hadoop services across a whole host of commodity hardware in a super easy and efficient manner. It is also possible to easily configure Hadoop services throughout the huge Hadoop cluster thanks to Ambari.
Hadoop cluster management
Managing the extremely large Hadoop clusters can be a herculean tasks but Ambari gives the option to centrally manage all the Hadoop services. You can at your will start, stop or reconfigure any of the Hadoop services across the cluster thus giving you immense power when it comes to managing complex Hadoop clusters.
Hadoop cluster monitoring
There are a number of cluster monitoring features that Ambari provides which includes a dashboard, the Ambari Metrics System, Ambari Alert Framework among other things. Using these top-notch facilities you can easily collect the most vital metrics concerning the Hadoop clusters, get system alerts for various scenarios like node failure, disk space consumption and so on.
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Apart from these three important features, Ambari also lets you integrate your Hadoop framework and services with your rest of the enterprise infrastructure in order to achieve a seamless interface and support the larger goals of the enterprise.
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Deep Dive into Ambari for Hadoop Cluster Deployment
Business enterprises need consistency and security when it comes to working with extremely large volumes of data with the Hadoop framework. This is where Ambari provides the much-needed Hadoop cluster operations automation features as described below:
Cluster managing, creating and monitoring at scale is efficiently taken care of by Ambari. It provides Smart Configs and Cluster Recommendations for configuring the Hadoop services over extremely large sets of Hadoop nodes. Repeating of cluster creation can also be completely automated and enabled at scale thanks to Ambari Blueprints.
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Security is of vital concern for any enterprise that is working on large Hadoop clusters. The pressing security need could be as a direct consequence of the complexities of the tasks involved, the significance of the tasks being handled, the timeframes involved or the sensitivities of the kinds of data that are being used. Whatever may be the reason it is paramount to not let Hadoop cluster security be an afterthought. All the vital security related tasks can also be efficiently handled by Ambari framework. It provides the right options for staying on top of cluster security management through the deployment of some very clever security capabilities like Apache Ranger and Kerberos authentication.
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Since Hadoop is basically a large collection of commodity hardware that performs the tasks of storing and processing of large volume of data, there are always chances of nodes going down, data being lost or computing prowess getting hampered. So it is extremely vital to monitor the status of the entire cluster in a very sophisticated manner. Ambari helps by letting the Hadoop administrator configure predefined alerts as per specific needs, visualize and record key operational and time-series metrics through the deployment of Grafana.
You can also minutely analyze the performance of each component and provide the right troubleshooting mechanism all through the right deployment of Apache Ambari. As part of the Hortonworks Data Platform you can also integrate the Ambari features with Hortonworks SmartSense for building some really smart proactive mechanism for prevention of failure and even early resolution of the issues in case of failure.
You can deploy Ambari on Hadoop without having to worry about the right fit for your specific enterprise needs. All this is thanks to Ambari being extremely customizable and extensible to suit your exact needs. Now Hadoop is able to efficiently work in your enterprise data ecosystem with highly powerful and extensible Ambari Stacks. Using these Ambari Stacks it is possible to manage even the custom services deployed on Hadoop. You can also benefit from the Ambari Views in order to tailor-make the Ambari Web User Interface to your needs.
The Power of Ambari Dashboard for Seamless Control
Ambari is a web console that does really amazing work of provisioning, managing and monitoring of your Hadoop clusters. Now a very important component of the Ambari tool is its Dashboard. It is necessary to learn all its incredible features and benefits in order to extract the best from Ambari for staying on top of your Hadoop systems at all times. You are able to get a whole lot of metrics via the Dashboard which can then be minutely filtered based on various parameters like component, time and context to get the best flexibility and monitoring capabilities at all times.
All in all the Ambari Dashboard can be considered as your gateway to your Hadoop cluster. You get all the key information and control of all Hadoop services at one place through Dashboard Widgets. Each of the specifically allocated Widgets on the Dashboard will give you all the information regarding various services like HBase, YARN, Storm and HDFS on the Hadoop cluster. It is also possible to customize the Widgets to suit your specific needs. For choosing the right widgets all you need to do is drag-and-drop the widgets. Get in-depth report on the status of each service and visualize it in the form of charts, graphs and reports or even create complex visualizations showing an amalgamation of services, usage, load status, uptime, data sources among other things.
Learn about the important steps needed to set up a single-node cluster of Hadoop in our blog at Hadoop Single Node Installation and Set Up.
Check these important features of the Ambari Dashboard
- Services Interface: A single point to staying on top of all Ambari services that are currently in operation. This gives you a hands-on monitoring capability for all Hadoop services across the cluster.
- User Interface: This is your central place to monitor, add or remove any Hadoop users on to your cluster. This way you can efficiently manage all the users in order to ensure the Hadoop system works in the most optimal manner with the right set of users and user privileges.
- Jobs Interface: This is a complete set of the various applications and jobs that comprise of the entire workload on your Hadoop system. You can easily move to a particular job through this Dashboard interface for further actions or monitoring.
- Heatmaps: This is your one-stop shop for monitoring the highest and the lowest capacity utilization and everything in between on the entire Hadoop cluster. Having such a graphic representation of the cluster helps you actively and in real-time manage the load and capacity utilization for most optimal performance.
- Hosts Interface: This provides with the complete information of all the hosts that are part of the grand scheme of the Hadoop cluster. You can even drill down to a particular individual host in order to monitor and manage it through this incredible interface in the Ambari Dashboard.
So Apache Ambari is rightly the tool of choice for forward-thinking enterprises around the world in order to successfully monitor, manage and provision their extremely large Hadoop clusters for getting stellar results.
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