Andy Brist's presentation on Data Visualizations and Nagios XI. The presentation was given during the Nagios World Conference North America held Sept 20-Oct 2nd, 2013 in Saint Paul, MN. For more information on the conference (including photos and videos), visit: http://go.nagios.com/nwcna

1. Data Visualizations
and Nagios XI
Andy Brist
abrist@nagios.com

2. 2
About This Presentation
A high level overview of data visualizations
A short breakdown of the philosophy and
psychology of visualizing data.
Nagios XI is used for most of the examples
Sneak peak at some of the upcoming
visualizations in XI

3. 3
Interacting with Data
You have data, what should you do with it?
Alert/notify
Interact with a ticketing system
Run event handlers/restart services
Send reports
Etc.

4. 4
Automation > Visualizations?
Most tasks acting on the data, or due to the
data, is automated.
Script logic handles large data sets much better
than the average human.
Condensed dashboards adequately represent
state of data, all intensive data manipulation is
handled by the backend.

5. 5
UI != Visualizations
Most "Visualizations" are actually UI in
disguise.
Purpose of UI is to interact with the views of
data.
These views are some form of rudimentary data
visualization, but are often too particular:
Only correlates one metric for many objects –
the "single value syndrome"
Shows all metrics for one object

6. 6
Then what are Proper Visualizations?
The "main goal of data visualization is to communicate
information clearly and effectively through graphical means. It
doesn’t mean that data visualization needs to look boring to be
functional or extremely sophisticated to look beautiful. To
convey ideas effectively, both aesthetic form and functionality
need to go hand in hand, providing insights into a rather
sparse and complex data set by communicating its key-
aspects in a more intuitive way. Yet designers often fail to
achieve a balance between form and function, creating
gorgeous data visualizations which fail to serve their main
purpose — to communicate information"
Vitaly Friedman (2008) "Data Visualization and Infographics"
in: Graphics, Monday Inspiration, January 14th, 2008.

7. 7
Key Points of a Visualizations
It must be communicative of data
It should reduce large, complex data sets to
manageable sizes and simplicity
Information must be displayed in a more
intuitive way than tables or single values.
Form and function are inextricably linked
Well suited for explaining the relationships
between sets of objects.

8. 8
Efficiency
Primary Visual Cortex: "It is the simplest,
earliest cortical visual area. It is highly
specialized for processing information about
static and moving objects and is excellent in
pattern recognition."

9. 9
Grokking and Your Lying Eyes
Visualizations, in a nutshell are optimizations
for a different architecture that when offloaded
to, process certain types of problems better.
Imagine your brain as a multicore computer,
with the Prefrontal Cotex as one CPU and the
Primary Visual Cortex as another.
Visualizations should aim to be a more efficient
means to display the relationships between
data points or sets.

10. 10
Goals of a Data Visualization
Provide the visual "glue" between the particular
and the general.
Provide a more efficient means to view and
understand data correlations
Help identify multifaceted trends
Simplify the understanding of the complex
without losing the complexities.

11. 11
Back to Earth
Ignoring the philosophy
and psychology of
visualizations, why
should we care?
What real world impact
do visualizations
provide?

12. 12
Benefits to the End User
Converts raw data into usable information
Can cleverly reveal relationships in data that
would otherwise be obfuscated by the size of
the data set
Presents technical data to the non-technical
user
Meaningful visualizations scale better than
tables or single value metrics

13. 13
Forms and Functions
Visualizations can make use of a number of
aesthetic qualities to express the data:
Length & width (& depth?)
Color / gradient
Relative position & distance
Movement
Size
Shape

14. 14
Standard Details Pages

15. 15
Standard Summary Pages

16. 16
BBMap

17. 17
BPI

18. 18
Network Status Map

19. 19
Hypermap

20. 20
Network Replay

21. 21
Google Map Component

22. 22
pnp4nagios

23. 23
Metrics

24. 24
Alert Cloud

25. 25
Alert Heatmap

26. 26
Alert Stream

27. 27
Graph Explorer

28. 28
Graph Explorer

29. 29
Graph Explorer

30. 30
Nagvis

31. 31
Nagvis

32. 32
Nagvis

33. 33
Nagvis

34. 34
Operations Center

35. 35
Nocscreen

36. 36
In Development
Multiple data source stacked graphs
The ability to alter the y-axis ratios per data
source to compensate for normalization
issues of different metric types
GLMap
3D UI – webgl based (three.js)
Realtime check information
Leverages the XI XML Backend currently
Plans for Integration with the JSON CGI

37. 37
Stacked Graphs

38. 38
GLMap Cube3d

39. 39
GLMap Cube3d

40. 40
GLMap Cube3d

41. 41
GLMap Cube3d

42. 42
GLRRD

43. 43
GLRRD

44. 44
Custom Visualizations
Learn the API(s)!!
Understand the requirements or goals
More metrics != better
It must do at least one thing well
Adding metrics without a purpose may
interfere with the clarity of the data
Flashy is not necessary, but helps when raises
and promotions are handed out

45. 45
Finishing Up
Visualizations must assist the understanding of
data
Use as many of the available graphical qualities
(size,shape,color,etc) as possible while still
retaining clarity
If all else fails, maybe management will still like
it