Building maps for apps in the cloud - a Softlayer Use Case

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Together with Softlayer Snowciety gave a presentation at GOTO Amsterdam 2013 about building custom maps using OpenStreetMap and SRTM data, POstgis/PostgreSQL as a datsbase, Mapnik as a renderer, Tilestance and Apache as the http servers and Leaflet as the javascript client.

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Building maps for apps in the cloud - a Softlayer Use Case

  1. 1. Building maps forapps in the cloud
  2. 2. Share your skiing with the world.Join the Snowciety
  3. 3. Ski tracker
  4. 4. Friend finder
  5. 5. Share your skiing
  6. 6. Google Maps alternativebecause they charge heavy users nowadays
  7. 7. Freedomcreate radical designs
  8. 8. It is all Open Sourceeven the data from NASA
  9. 9. data database renderer http server
  10. 10. client
  11. 11. OpenStreetMapwikipedia for maps
  12. 12. SRTMShuttle Radar Topography Mission
  13. 13. Lots of dataour cluster contains roughly 3,5 terabyte of unrendered data
  14. 14. 350 GB of OSMPostgreSQL with PostGIS plugin
  15. 15. 3 TB of GEOTIFF
  16. 16. Mapnikrenderer
  17. 17. §
  18. 18. Journey to get here
  19. 19. Journey to get here
  20. 20. §
  21. 21. pngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpngpng256x256png png png png png png png png png png
  22. 22. Not only server-sidealso client-side library to interact with map
  23. 23. An Open-Source JavaScript Libraryfor Mobile-Friendly Interactive Maps
  24. 24. Apache httpdNo, not really the chopper
  25. 25. Tile StacheTranslating Apache requests into Mapnik render commands
  26. 26. Mapnikthe renderer from before
  27. 27. CachingMemcache, Disk, S3
  28. 28. CachingMemcache, Disk, S3
  29. 29. Importing datatakes a loooooooooooooooooooooooooooooooooooong time
  30. 30. 25GBgzipped xml file
  31. 31. and you know how well plaintext can be gzippedfile is roughly 250GB unzipped
  32. 32. 3 weeks and counting :-|M1 Large Instance7.5 GiB of memory, 4 EC2 Compute Units
  33. 33. High-Memory Quadruple ExtraLarge Instance68.4 GB of memory, 26 EC2 Compute Units, 24 EBS blocks RAID 1$1.640 per Hour = $ 1180 / month29 hours!
  34. 34. Dedicated hardware68 GB of memory, 8 Cores, 1 SATA disk$ 700 / month10 hours
  35. 35. Macbook Pro16 GB of Memory, SSD
  36. 36. 8.5 hoursit is all about lots of memory and lots and lots of IO speed
  37. 37. and that was just OSM!
  38. 38. SRTMShuttle Radar Topography Mission
  39. 39. about a minuteper 1” x 1” file
  40. 40. from -180,0 to 180,9028.800 files
  41. 41. 20 days laterwe were done importing
  42. 42. So now you knowhow it is made
  43. 43. Future?More sources, better maps, and..
  44. 44. Vector maps!
  45. 45. How do I get started?Mapbox.comdownload TileMill
  46. 46. Building your on OSM server (incl all build commands)http://weait.com/content/build-your-own-openstreetmap-server-lucidWorking with terrain data (hillshading, slopeshading, color-relief)http://www.mapbox.com/tilemill/docs/guides/terrain-data/for when viewing this presentation on SlideshareTutorials
  47. 47. THANK YOU@timanrebel
  48. 48. Rate me!GOTO Guide App!

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