Yesterday the Apache Ambari community proudly released version 1.5.1. This is the result of constant, concerted collaboration among the Ambari project’s many members. This release represents the work of over 30 individuals over 5 months and, combined with the Ambari 1.5.0 release, resolves more than 1,000 JIRAs.
This version of Ambari makes huge strides in simplifying the deployment, management and monitoring of large Hadoop clusters, including those running Hortonworks Data Platform 2.1.
Ambari 1.5.1 contains many new features – let’s take a look at those.
This feature silences alerts on Services and Hosts, an ideal feature for when you need to perform cluster maintenance. The Hadoop operator can put Services or Hosts “out of service” and alerts will be suspended for those items.
Rolling restarts minimize cluster downtime and service impact when making configuration changes across many hosts. Administrators can initiate a rolling restart of cluster components (such as DataNodes), with the option of including only hosts with configuration changes.
As clusters grow larger, Hadoop operators need to host operations on batches of hosts. This feature makes those “bulk” operations easy and available via the Ambari Web interface. Supported bulk operations are: Stop, Start, Restart, Decommission and Maintenance Mode. These operations may be applied to all hosts, the filtered group of hosts or a selected group of hosts.
It is sometimes necessary to remove data from existing services for storage elsewhere while performing maintenance. Decommission allows the Hadoop operator to phase out service components without bringing down services or losing data.
This allows Hadoop operators to install clusters with the minimum amount of required services, and then add on additional services later with the new “Add Service” control in the Ambari Web UI. This permits more agile, flexible growth of components and services in a cluster.
MANY THANKS to all the contributors that made the Ambari 1.5.1 release possible!
This release also includes a technical preview of the Ambari Blueprints feature. With Ambari Blueprints, you can simplify the automation of cluster installs by defining the stack to use, the components layout and the configuration. With just a few API calls, you have a cluster up and running. This is particularly helpful for virtual and cloud environments where the Hadoop operator wants to create ad hoc discovery clusters or dev and test clusters, in an automated and consistent fashion.