1. GE Energy
High performance Web solution
based on Geospatial Server
Erwin Saegesser - NIS AG - Switzerland

2. High performance Web solution
based on Geospatial Server

3. .. beware of lurking pitfalls

4. High performance is within
reach, but you need to know the
tricks of the trade!

5. First of all - You need to know your
enemy

6. Secondly - Derive the actions

7. about us NIS AG
Since 1996
Provider of Software and
Services for Utilities

8. EKS
EBM IBW ewz EN Uster
EBL
AEK
AEN
AEW
EKZ
EUG SAK
CKW
BKW EWS
EWA
Swisscom AKONIS
EW Flims
Energie Thun
EWZ-GR
Serving our Utilities SES
SES

9. EKS
EBM IBW ewz EN Uster
EBL
AEN
AEK AEW
EKZ SAK
EUG
CKW
BKW EWS
Elektrizitätswerke Kanton Zürich - EKZ
Swisscom
EWA
AKONIS
• Canton of Zürich 1’800 km2 area EW Flims
• 286’000 customers Thun
Energie
EWZ-GR
• 1’600 employees
• 37 substations SES
• 2’500 transformer stations SES
• 10’000 km cables of which 90% are under ground
• 8’000 print orders per year

10. You need to know your enemy
Customer
Software Infrastructure
Data

11. You need to know your enemy
Customer
Software Infrastructure
Data

12. You need to know your enemy
… its Requirements
Software Infrastructure
Data

13. its Requirements
• What keeps you up at night
• Separate made-up and “useless“ from valuable
• “who – what – why” and “the 5 why’s”

14. 45’’
for an answer requires less clicks

15. Software Infrastructure
• Architecture
• Caching
• Configuration

16. File
MapCache
File
HTTPS AJP
Client Application-
Webserver
nisXplorer server Agent(s)
Apache
Browser JBoss
GIS
SWMFS
Smallworld
Service
Providers (SSP)

17. Presentation Business logic / Data layer
– HTML / JavaScript – Java EE
– Open Source Frameworks – Grails
– Geospatial Server
– REST Services
– Smallworld verticals

18. Caching - Should you use it?

19. Yes, absolutely!
Faster
Reliable
Larger

20. Faster

21. Faster Tiles
15 tiles on average

22. Single dyn request* = 2500 ms
Single tile request* = 200 ms
Faster
* 1 SSP gets 1 Core and 1.5 GB RAM

23. Dynamic requests per day
140 25
Response times in Seconds and # of
120
20
100
Requests 15
# of requests
80
Sessions
Sessions
60
10
40
Response 5
20
0 0
00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23

24. Tile requests per day
6000 25
Response times in Seconds and # of
5000
20
4000
# of requests
15
Requests
Sessions
3000
Sessions 10
2000
1000
Response 5
0 0
00 01 02 03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23

25. • Available 7 x 24
• No off times during rollforward
Reliable • Average time for rollforward = 15’ *
* EKZ data

26. nisXplorer = 16 scales
Larger Google = 19 scales

27. nisXplorer = 16 scales
Google = 19 scales
Larger Exponential increase
of tiles

28. Scale MB/km2*
Others 0.1
1:500 0.5
Larger 1:250 1.3
1:100 7.0
* EKZ data

29. Larger

30. Larger
75%

31. Configuration – Best practices
• Cache only works for one world
• Consider limit of 10 SSP per layer for caching
• No need to backup the cache
• Consider re-population - Don’t mix interaction and cache
population
• Do not cache all scales
• Consider other caches such as Grails or “HTML 5 Offline
Application Caching” and/or “HTTP Proxies”

32. Configuration – Best practices
• Cache “top ten” layers
• Use visibility through print layout
• Merge server side - not too many layers in client
• Avoid “always on” effect
• Check and scale hardware (1 SSP – 1.5 GB RAM - 1 Core)
• Increase # of SSP and consider the cloud
• Assign dedicated SSP resources to single service types

33. Dedicated GSS Agent configurations …

34. Agent configurations
Requests Agent Dedicated SSPs

35. Agent configurations
Requests Agent Dedicated SSPs
Use different setups

36. Data
• Get to know your data health
• Clarify its usage
• Data “mash up” - use 3rd party to your benefit

37. Data
• Get to know your data health
• Clarify its usage
• Data “mash up” - use 3rd party to your benefit
Swisstopo 500 Mio Tiles

38. Avoid “Bottlenecks”

39. Bad compression rate … think mobile

40. 0/0 coordinates … bad for rollforward

41. Derive the actions
• User interface – Allow for quick success
• Apply appropriate layer and caching strategy in coordination
with the right size of hardware
• Inspect and adjust

42. UI best practices
• “Slim UI”
• Map extend with buffer
• Highlight already loaded
• UI not blocked during user interaction

43. Setup best practices
Port 80/443 Port 8009 (AJP) Business Logic and Database
HW: 8 GB RAM; 4 Cores; Standard Disk
Applicationserver J2EE/JBoss
Project configuration
Webserver Database
nisXplorer- HW: 4 GB RAM; 2 Cores
Clients Webserver Apache
Serviceprovider
HW: 24-32 GB RAM; 24 Cores;
GSS Agents
• 10-n Images for map interaction
• 10 Images for MapCache
• 1 Image for Index
Cache
• GSS Cache Data (no Backup)

44. Focus and customer
involvement from the first
What we did day

45. Applied key lessons
learned through iterative
What we did
and incremental
development

46. Integrated on state of the
What we did art software with GSS and
Open Source components

47. Five things to remember
• Intuitive UI makes solution fast
• Use cache in a "smart way"
• Optimize configuration for the use cases
• Get and keep your data healthy
• Continuosely check for the weak link in the chain

48. about me
erwin.saegesser@nis.ch
certified scrum master
nis ag - Switzerland

49. Credits
• www.wickie-film.de
• Elektrizitätswerke Kanton Zürich
• agilemanifesto.org
• scrum.com
• agileproductdesign.com
• scrum.jeffsutherland.com