Automated Blueprint Install with Ambari Shell

Ambari Shell is an interactive command line tool to administrate Ambari manged HDP clusters. It supports all available functionality provided by the UI of the Ambari web application. Written as a Java application based on a Groovy REST client it further provides tab completion and a context aware commands. In a previous post we already discussed various contexts like service and state will using REST calls to alter them. Ambari Shell is a convenient tool for managing most of the complex aspects discussed there.

With that it can also be used for automated cluster installs based on Ambari Blueprints. While it is fairly simple to use two curl request to do a blueprint based install, Ambari Shell gives the advantage of monitoring the process. In scripted setups and with the use of provisioning tools like Puppet, Chef, or Ansible it gives the possibility to time setup steps after a complete cluster install. Executing a cluster install with --exitOnFinish true will halt the execution of the script until the install has finished.

An example of this is used as part of this Dockerfile where a parameterized script The below example is being used as part of a Puppet install triggered with Vagrant:

Further Readings

Kafka Security with Kerberos

Apache Kafka developed as a durable and fast messaging queue handling real-time data feeds originally did not come with any security approach. Similar to Hadoop Kafka at the beginning was expected to be used in a trusted environment focusing on functionality instead of compliance. With the ever growing popularity and the widespread use of Kafka the community recently picked up traction around a complete security design including authentication with Kerberos and SSL, encryption, and authorization. Judging by the details of the security proposal found here the complete security measures will be included with the 0.9 release of Apache Kafka.

The releases of HDP 2.3 already today support a secure implementation of Kafka with authentication and authorization. Especially the integration with the security framework Apache Ranger this becomes a comprehensive security solution for any Hadoop deployment with real-time data demands. In this post we by example look at how working with a kerberized Kafka broker is different from before. Here working with the known shell tools and a custom Java producer. Continue reading “Kafka Security with Kerberos”