Stabilizing Hadoop Clusters

Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number
Expertise Level

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Overview/Description
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

Prerequisites
None

Expected Duration (hours)
3.7

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:
df_ahop_a07_it_enus

Expertise Level
Intermediate