Chapter 8. Telemetry

Ceilometer is the telemetry component in OpenStack. While all the other components in OpenStack are busy managing virtual resources, Ceilometer keeps a watchful eye over them and measures the usage of resources, what resources are being used, and how they are being used within the cluster. In this chapter, we are going take a look at what is being measured and how to query the telemetry data. Then, we will use gnuplot to plot some of the data on a graph.

Understanding the data store

Before we start exploring Ceilometer, it is important to know that, by default, Ceilometer uses MongoDB to store all of its telemetry data. This data store can grow very rapidly and can use excess space. It is in your interest to keep Mongo's data store separate from the root partition of your control node so that the telemetry data does not fill up your control node's root disk. OpenStack has a horrible time functioning without a disk to write to. Mongo's data store is /var/lib/mongodb/ by default. A simple way to be sure that the node's root disk doesn't fill up would be to mount another partition, logical volume, or some other external storage to /var/lib/mongodb/. If there isn't any important data in Ceilometer, you can even stop the MongoDB service, delete the contents of the data store directory, mount the new storage, ensure the ownership is correct, and restart the central and collector services of both the MongoDB and Ceilometer APIs. The files that...

Definitions of Ceilometer's configuration terms

As resources are being managed within the OpenStack cluster, there are certain types of things that are being measured by Ceilometer. These types of things are called meters in Ceilometer. Each of these types of measurements gathers samples. Samples are single measurements or data points of a certain meter. The definition of how often to sample a meter is called a pipeline. Once enough samples are collected, they can be aggregated into statistics. Ceilometer statistics show a collection of samples over time for a particular meter. Ceilometer also has the ability to set alarms that will monitor statistics and is able to respond to matching criteria.

Pipelines

Pipelines are something that you shouldn't have to spend time configuring. Ceilometer has a collection of predefined pipelines that should suit most of your needs. If you end up needing a custom pipeline, it would be done in the /etc/ceilometer/pipeline.yaml configuration file. Take a look...

Graphing the data

Up until now, we have just seen data points flowing through our screen that may or may not be very useful to us. Wouldn't it be nice to make something visual to help display this data? There are plenty of options that could be used to plot this data. As an example, let's take a quick look at gnuplot, which is a command-line program that is packaged with most modern Linux distributions. This book has been using Fedora; to install gnuplot, simply yum install it:

undercloud# yum install -y gnuplot

There are options that need to be fed into gnuplot to tell it how to render the graph that it creates. Let's use a configuration file that will be passed to gnuplot. Put the following content into a file. I'm going to name mine memory.cfg because I will plot the memory usage that's already been aggregated by the Ceilometer statistics command:

#memory.conf
set terminal png truecolor
set output "memory.png"
set autoscale
set xdata time
set timefmt '%Y-%m-%dT%H:%M:%S'
set style data...

Summary

In this chapter, we looked at how to view, aggregate, and plot telemetry data using Ceilometer. This data is useful to monitor the health of a set of instances, a billing client, and so on. As mentioned in this chapter, Ceilometer's alarms are a useful resource for the orchestration tool in OpenStack. Next, we will look at cloud orchestration using the OpenStack component named Heat.