Course details

Stabilizing Hadoop Clusters

Stabilizing Hadoop Clusters

Target Audience
Expected Duration
Lesson Objectives
Course Number
Expertise Level

Apache Hadoop is increasingly in popularity as a framework for large-scale, data-intensive applications. Tuning Hadoop clusters is vital to improve cluster performance. In this course you will look at the importance of incident and log management and examine the best practices for root cause analysis. This learning path can be used as part of the preparation for the Cloudera Certified Administrator for Apache Hadoop (CCA-500) exam.

Target Audience
Engineers looking to expand their skill sets in the area of Hadoop stability


Expected Duration (hours)

Lesson Objectives

Stabilizing Hadoop Clusters

  • start the course
  • describe the importance of event management
  • describe the importance of incident management
  • describe the different methodologies used for root cause analysis
  • recall what Ganglia is and what it can be used for
  • recall how Ganglia monitors Hadoop clusters
  • install Ganglia
  • describe Hadoop Metrics2
  • install Hadoop Metrics2 for Ganglia
  • describe how to use Ganglia to monitor a Hadoop cluster
  • use Ganglia to monitor a Hadoop cluster
  • recall what Nagios is and what it can be used for
  • install Nagios
  • manage Nagios contact records
  • manage Nagios Push
  • use Nagios commands
  • use Nagios to monitor a Hadoop cluster
  • use Hadoop Metrics2 for Nagios
  • describe how to manage logging levels
  • describe how to configure Hadoop jobs for logging
  • describe how to configure log4j for Hadoop
  • describe how to configure JogHistoryServer logs
  • configure Hadoop logs
  • describe the problem management lifecycle
  • recall some of the best practices for problem management
  • describe the categories of errors for a Hadoop cluster
  • conduct a root cause analysis on a major problem
  • use different monitoring tools to identify problems, failures, errors and solutions
  • Course Number:

    Expertise Level