Monitoring with Ganglia

With Ganglia, you can monitor the performance of several deployment scenarios – but this tool’s strength can also be a weakness if you don’t know how all its pieces work together. This book shows you how to configure Ganglia to monitor clusters, grids, or cloud infrastructures at very large scales on the order of thousands of machines. Experienced users will get up to speed on the latest Ganglia release (3.x), including several recent features, such as sFlow support and Ganglia’s new web frontend. You’ll learn how to extend the base set of metrics you collect, fetch current values, see aggregate view of metrics, and look at time-series trends in your data.

Author Biography

Matt Massie open-sourced Ganglia in 2000 while working as a Staff Researcher at the University of California, Berkeley. He designed ganglia to monitor a shared computational grid of clusters distributed across the United States for scientific research. In 2010, he contributed a chapter on cluster monitoring for the O’Reilly book “Web Operations: Keeping the Data On Time” by John Allspaw and Jesse Robbins. Matt is currently a software engineer at Cloudera focused on Apache Hadoop enterprise management and monitoring. Bernard Li is a High Performance Computing (HPC) Systems Engineer at Lawrence Berkeley National Laboratory. He is currently one of the maintainers of the Ganglia project. He has been involved with HPC since 2003 and has worked on Open Source projects such as OSCAR, SystemImager and Warewulf. Brad Nicholes is a member of the Apache Software Foundation and is currently working as a Consultant Software Engineer for NetIQ. In addition to being a committer on the Apache HTTPD and APR projects, Brad is also a developer as well as one of the administrators of the Ganglia project. As a developer on the Ganglia project, Brad developed and introduced the C/C++ and Python metric module interface into Gangla 3.1.x. He also developed and contributed several of the initial metric modules that currently ship with Ganglia. Brad attended school at the University of Utah and Brigham Young University and holds a degree in Computer Science. Vladimir Vuksan (Broadcom) has worked in technical operations, systems engineering and software development for over 15 years. Prior to Broadcom he has worked at Mocospace, Rave Mobile Safety, Demandware, University of New Mexico implementing high availability solutions and building tools to make managing and running infrastructure easier.