Nagios Conference 2013 - Andy Brist - Data Visualizations and Nagios XI


Published on

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:

Published in: Technology, Education
  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Nagios Conference 2013 - Andy Brist - Data Visualizations and Nagios XI

  1. 1. Data Visualizations and Nagios XI Andy Brist
  2. 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. 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. 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. 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. 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. 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. 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. 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. 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. 11 Back to Earth Ignoring the philosophy and psychology of visualizations, why should we care? What real world impact do visualizations provide?
  12. 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. 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. 14 Standard Details Pages
  15. 15. 15 Standard Summary Pages
  16. 16. 16 BBMap
  17. 17. 17 BPI
  18. 18. 18 Network Status Map
  19. 19. 19 Hypermap
  20. 20. 20 Network Replay
  21. 21. 21 Google Map Component
  22. 22. 22 pnp4nagios
  23. 23. 23 Metrics
  24. 24. 24 Alert Cloud
  25. 25. 25 Alert Heatmap
  26. 26. 26 Alert Stream
  27. 27. 27 Graph Explorer
  28. 28. 28 Graph Explorer
  29. 29. 29 Graph Explorer
  30. 30. 30 Nagvis
  31. 31. 31 Nagvis
  32. 32. 32 Nagvis
  33. 33. 33 Nagvis
  34. 34. 34 Operations Center
  35. 35. 35 Nocscreen
  36. 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. 37 Stacked Graphs
  38. 38. 38 GLMap Cube3d
  39. 39. 39 GLMap Cube3d
  40. 40. 40 GLMap Cube3d
  41. 41. 41 GLMap Cube3d
  42. 42. 42 GLRRD
  43. 43. 43 GLRRD
  44. 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. 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