Get travis into better shape

- There are more to go

Principles-of-Operation.md

@@ -1,7 +1,7 @@
 # Principles of Operation
 
 To understand Cacti's principal of operation, you have to start
-at the top and work down.  Cacti's operational model is 
+at the top and work down.  Cacti's operational model is
 divided into multiple layers.  They include
 
 - Devices
@@ -13,8 +13,8 @@ divided into multiple layers.  They include
 
 ## Devices
 
-Cacti **Devices** are either physical hosts, sensors, clusters, 
-services, or any type of object with a name and that can 
+Cacti **Devices** are either physical hosts, sensors, clusters,
+services, or any type of object with a name and that can
 provide information about it self that should go into a
 **Graph** or could be used to provide additional information
 useful for Operations.
@@ -22,7 +22,7 @@ useful for Operations.
 The Cacti **Device** object serves as the center Cacti's world
 it's where stores information on how gather data about it.  You
 can have from one to tens of thousands of **Devices** monitored
-from one Cacti system.  It's very scalable.  They can be 
+from one Cacti system.  It's very scalable.  They can be
 discovered using Cacti's Automation sub-system, added manually,
 or gathered from a CMDB and added to Cacti using it's command
 line interface.
@@ -49,7 +49,7 @@ can be migrated live which does not interrupt data collection.
 ## Data Retrieval
 
 The Data Collectors first and foremost task it to retrieve data and
-forward it to the main Cacti server for storage. Cacti will do so 
+forward it to the main Cacti server for storage. Cacti will do so
 using its poller which is a part of the Data Collector. The Poller
 is executed from the operating system's scheduler or from systemd
 depending on the OS and the version of the OS.  It collects data
@@ -66,9 +66,9 @@ the device to the Cacti database.
 In enterprise installations, you're dealing with potentially
 thousands of devices of different type, e.g. Servers, Network
 Equipment, Appliances, Sensors, PDU's, Static Transfer Switches
-and the like. To retrieve data from remote targets/hosts, Cacti 
+and the like. To retrieve data from remote targets/hosts, Cacti
 will mainly use the Simple Network Management Protocol SNMP.
-Thus, all devices capable of using SNMP will be eligible to be 
+Thus, all devices capable of using SNMP will be eligible to be
 monitored by Cacti.  But that's just the simplest case.
 
 Many customers gather data using out of band processes like
@@ -87,7 +87,7 @@ However, most customers will use SNMP, or SSH to gather
 metrics from their Devices.  I mean, how many companies
 have 50 thousand devices that they monitor with regularity?
 
-Once the data has been gathered, Cacti then uses either an 
+Once the data has been gathered, Cacti then uses either an
 out-of-band or in-band process to store the data into Round
 Robin Archive files, which represent a flat very well performing
 Time Series Databases called RRDfiles.  See below for details
@@ -101,7 +101,7 @@ There are only so many ways to make a hammer, and RRDtool's a great
 hammer.  Other approaches in the industry use SQL database,
 others flat files or document stores like Elastic Search, Splunk,
 Mongo DB, InfluxDB.  There are a number of options out there.
-You can get more information about RRDfile from the 
+You can get more information about RRDfile from the
 [RRDtool Website](http://www.RRDtool.org/).
 
 `RRD` is an acronym for **Round Robin Database**. RRD is a system to store and
@@ -111,8 +111,8 @@ expand over time, and it can create beautiful graphs.  Data that ages
 beyond a certain point is consolidated and very old data just rolls off
 the end of the RRDfile.  It ages out.  This keeps storage requirements at bay.
 
-As mentioned, performs consolidation to combine raw data (a `primary data point` 
-in RRDtool lingo) to consolidated data (a `consolidated data point`). 
+As mentioned, performs consolidation to combine raw data (a `primary data point`
+in RRDtool lingo) to consolidated data (a `consolidated data point`).
 This way, historical data is compressed to save space. RRDtool knows
 different consolidation functions: AVERAGE, MAXIMUM, MINIMUM and LAST.
 
@@ -126,17 +126,17 @@ merely any browser on any platform.
 The Graphing engine is quite flexible. It is possible, to graph one or
 many items in one graph. Auto-scaling is supported and logarithmic y-axis,
 left and right axes, and much much more. You may stack items onto another
-and print pretty legends denoting characteristics such as minimum, 
+and print pretty legends denoting characteristics such as minimum,
 average, maximum and lots more.
 
 ## Extending Built-in capabilities
 
 As mentioned, scripts and Queries extend Cacti's capabilities beyond
 just SNMP. They allow for data retrieval using custom-made code.
-This is not even restricted to certain programming languages; 
-you will find PHP, Perl, Python, shell/batch 
-and more. These scripts and queries are executed locally by Cacti's Poller. But they may
-retrieve data from remote hosts by different protocols, e.g.
+This is not even restricted to certain programming languages;
+you will find PHP, Perl, Python, shell/batch
+and more. These scripts and queries are executed locally by Cacti's Poller.
+But they may retrieve data from remote hosts by different protocols, e.g.
 
 Protocol | Description
 --- | ---