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QTBSept2013
	
  
@thoughtworks	
  
@tramchester	
  
#twuknorth	
  
	
  
What is a Tech Lab?
•  Experiment	
  and	
  learn	
  about	
  technology	
  
•  Time-­‐boxed	
  
– 6	
  weeks	
  maximum	
  
•  Small	
  team	
  
– Core	
  of	
  3	
  people	
  (2	
  Developers,	
  1	
  BA)	
  
•  With	
  support	
  and	
  experKse	
  as	
  needed	
  
	
  
Tech Lab - Desired Outcomes
More	
  important	
  Less	
  important	
  
Tech	
  Learning	
  
Produce	
  Collateral	
  
Excite	
  community	
  
Working	
  soOware	
  to	
  demo	
  
•  Tech	
  Learning	
  
•  Understand	
  the	
  pros	
  and	
  cons	
  of	
  a	
  technology	
  
•  What	
  is	
  good	
  and	
  what	
  is	
  not	
  so	
  good	
  
•  Working	
  SoOware	
  to	
  demo	
  
•  Create	
  something	
  real!	
  
•  Produce	
  collateral	
  	
  
•  Produced	
  tangible	
  outputs	
  we	
  can	
  share	
  
•  Excite	
  Community	
  
•  Get	
  people	
  excited	
  about	
  what	
  we	
  are	
  doing	
  
What did we look at?
•  Domain:	
  Travel	
  in	
  and	
  around	
  
Manchester	
  
–  Raw	
  Data	
  is	
  available	
  from	
  
hUp://www.datagm.org.uk/	
  
–  Metrolink	
  was	
  iniKal	
  focus	
  
•  Tech:	
  Not	
  Only	
  Sql	
  
–  Experiment	
  with	
  Graph	
  database	
  as	
  way	
  
of	
  modeling	
  a	
  travel	
  network	
  
•  Tech:	
  cloud	
  
–  Host	
  in	
  AWS	
  
Why the cloud?
•  Keep	
  things	
  “RealisKc”	
  
– Compiling	
  and	
  running	
  on	
  a	
  
laptop	
  doesn’t	
  tell	
  us	
  enough	
  
•  Experiment;	
  not	
  sure	
  what	
  
we’d	
  need	
  
•  Keep	
  costs	
  reasonable	
  and	
  
controllable	
  
•  Very	
  easy	
  to	
  automate	
  and	
  
script	
  AWS	
  
Deployment
•  ConKnuous	
  Deployment	
  
– We	
  used	
  Go	
  
•  Use	
  Phoenix	
  Server	
  paUern	
  
•  Ant,	
  shell	
  scripts	
  and	
  Cloud	
  
FormaKon	
  
•  cloudinit	
  for	
  “bootstrapping”	
  
soOware	
  on	
  to	
  the	
  instances	
  	
  
Phoenix Server
•  Axiom:	
  It	
  is	
  easier	
  to	
  create	
  new	
  
instances	
  and	
  install	
  soOware	
  on	
  to	
  
them	
  than	
  it	
  is	
  to	
  try	
  and	
  upgrade	
  
and	
  reconfigure	
  soOware	
  on	
  
exisKng	
  instances	
  
•  Wanted	
  to	
  avoid	
  complex	
  chef/puppet	
  scripts	
  	
  
•  We	
  avoided	
  chef/puppet	
  enKrely	
  J	
  
•  “Banned”	
  manual	
  updates	
  to	
  deployed	
  
instances	
  
Why a graph database?
Map	
  ©	
  Transport	
  for	
  Greater	
  Manchester	
  2013	
  
3	
  
3	
  
5	
  
5	
  
2	
  
2	
  
2	
  
2	
  
Tram Data…
•  Tabular	
  Data	
  in	
  text	
  file	
  
	
  •  4	
  Important	
  Concepts	
  
•  Stops	
  
•  Routes	
  
•  Services	
  
•  Trips	
  
Graph Model – Iteration 1
A1	
  
A2	
  
B1	
  
B2	
  
3	
  
3	
  
C1	
  
C2	
  
4	
  
4	
  
D1	
  
D2	
  
2	
  
2	
  
E1	
  
E2	
  
3	
  
3	
  
G2	
  
F2	
  
3	
  
2	
  
G1	
  
F1	
  
2	
  
Graph Model – Iteration 2
A1	
  
A2	
  
B1	
  
B2	
  
C1	
  
C2	
  
D1	
  
D2	
  
E1	
  
E2	
  
G2	
  
F2	
  
G1	
  
F1	
  
S1	
  
Graph Model – Iteration 3
A1	
  
A2	
  
B1	
  
B2	
  
C1	
  
C2	
  
D1	
  
D2	
  
E1	
  
E2	
  
G2	
  
F2	
  
G1	
  
F1	
  
S1	
  
S2	
  
S3	
  
S4	
  
Graph Model – Iteration 4
A1	
  
A2	
  
B1	
  
B2	
  
C1	
  
C2	
  
D1	
  
D2	
  
E1	
  
E2	
  
R1	
  
A1	
  
R1	
  
B1	
  
3	
   R1	
  
C1	
  
4	
   R1	
  
D1	
  
2	
   R1	
  
E1	
  
3	
  
5	
   1	
  
A1	
  
5	
   1	
   5	
   1	
   5	
   1	
   5	
   1	
  
Time Dependent Graph
A	
   B	
  
T1	
  (08:00)	
  
T2	
  (08:12)	
  
T3	
  (08:24)	
  
T4	
  (08:36)	
  
T5	
  (08:48)	
  
T6	
  (09:00)	
  
T7	
  (09:12)	
  
T8	
  (09:24)	
  
T9	
  (09:36)	
  
T10	
  (09:48)	
  
T11	
  (10:00)	
  
T12	
  (10:12)	
  
Up	
  to	
  900	
  RelaKonships	
  
C	
  
T1	
  (08:05)	
  
T2	
  (08:17)	
  
T3	
  (08:29)	
  
T4	
  (08:41)	
  
T5	
  (08:53)	
  
T6	
  (09:05)	
  
T7	
  (09:17)	
  
T8	
  (09:29)	
  
T9	
  (09:41)	
  
T10	
  (09:53)	
  
T11	
  (10:05)	
  
T12	
  (10:17)	
  
Heuristics
A	
   B	
  
T4	
  (08:36)	
  
T5	
  (08:48)	
  
T6	
  (09:00)	
  
T7	
  (09:12)	
  
T8	
  (09:24)	
  
C	
  
T4	
  (08:41)	
  
T5	
  (08:53)	
  
T6	
  (09:05)	
  
T7	
  (09:17)	
  
T8	
  (09:29)	
  
Geek Night
Next	
  Wednesday	
  
	
  September	
  25th	
  	
  
An	
  introducKon	
  to	
  	
  
Graph	
  Databases	
  
The App
hUp://www.tramchester.co.uk	
  
How did the team do?
More	
  important	
  Less	
  important	
  
Tech	
  Learning	
  
Produce	
  Collateral	
  
Excite	
  community	
  
Working	
  soOware	
  to	
  demo	
  
✔
•  Learnt	
  about	
  the	
  pros	
  and	
  cons	
  of	
  graph	
  databases	
  
•  Proved	
  workability	
  of	
  this	
  approach	
  
•  Re-­‐enforces	
  view	
  that	
  need	
  to	
  pick	
  the	
  right	
  Database	
  
model	
  for	
  the	
  domain	
  
•  Learnt	
  more	
  about	
  using	
  cloud	
  formaKon	
  and	
  cloudinit	
  
How did the team do?
More	
  important	
  Less	
  important	
  
Tech	
  Learning	
  
Produce	
  Collateral	
  
Excite	
  community	
  
Working	
  soOware	
  to	
  demo	
   ✔
•  Built	
  a	
  working	
  mobile	
  web	
  applicaKon	
  
•  More	
  successful	
  than	
  we	
  thought!	
  
•  Local	
  media	
  caught	
  on	
  
•  In	
  daily	
  use	
  
How did the team do?
More	
  important	
  Less	
  important	
  
Tech	
  Learning	
  
Produce	
  Collateral	
  
Excite	
  community	
  
Working	
  soOware	
  to	
  demo	
  
✔
•  Able	
  to	
  produce	
  diaries,	
  presentaKons,	
  whitepapers,	
  
videos,	
  conferences,	
  and	
  labs	
  
•  Including	
  this	
  talk	
  ;-­‐)	
  
•  Geek	
  Night	
  
•  New	
  York	
  GraphConnect	
  Conference	
  	
  
How did the team do?
More	
  important	
  Less	
  important	
  
Tech	
  Learning	
  
Produce	
  Collateral	
  
Excite	
  community	
  
Working	
  soOware	
  to	
  demo	
  
✔
•  Lots	
  of	
  interest	
  inside	
  of	
  ThoughtWorks	
  
•  Internal	
  talks	
  and	
  presentaKons	
  conKnue	
  
•  Interest	
  outside	
  of	
  ThoughtWorks	
  as	
  well	
  
•  Next	
  steps….?	
  
A nice problem to have…..
Next Steps?
•  Would	
  our	
  clients	
  be	
  
interesKng	
  in	
  doing	
  TechLabs?	
  
•  Team	
  are	
  passionate	
  and	
  
want	
  to	
  conKnue	
  
– Your	
  Ideas?	
  
– Do	
  we	
  Open	
  Source?	
  
•  Feature	
  requests	
  are	
  sKll	
  
arriving…..	
  
Any Questions?
•  Check	
  out	
  the	
  app	
  at	
  
– hUp://www.tramchester.co.uk	
  
– @tramchester	
  

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Tech Lab Explores Graph Database for Modeling Manchester Travel Network

  • 1.
  • 3. What is a Tech Lab? •  Experiment  and  learn  about  technology   •  Time-­‐boxed   – 6  weeks  maximum   •  Small  team   – Core  of  3  people  (2  Developers,  1  BA)   •  With  support  and  experKse  as  needed    
  • 4. Tech Lab - Desired Outcomes More  important  Less  important   Tech  Learning   Produce  Collateral   Excite  community   Working  soOware  to  demo   •  Tech  Learning   •  Understand  the  pros  and  cons  of  a  technology   •  What  is  good  and  what  is  not  so  good   •  Working  SoOware  to  demo   •  Create  something  real!   •  Produce  collateral     •  Produced  tangible  outputs  we  can  share   •  Excite  Community   •  Get  people  excited  about  what  we  are  doing  
  • 5. What did we look at? •  Domain:  Travel  in  and  around   Manchester   –  Raw  Data  is  available  from   hUp://www.datagm.org.uk/   –  Metrolink  was  iniKal  focus   •  Tech:  Not  Only  Sql   –  Experiment  with  Graph  database  as  way   of  modeling  a  travel  network   •  Tech:  cloud   –  Host  in  AWS  
  • 6. Why the cloud? •  Keep  things  “RealisKc”   – Compiling  and  running  on  a   laptop  doesn’t  tell  us  enough   •  Experiment;  not  sure  what   we’d  need   •  Keep  costs  reasonable  and   controllable   •  Very  easy  to  automate  and   script  AWS  
  • 7. Deployment •  ConKnuous  Deployment   – We  used  Go   •  Use  Phoenix  Server  paUern   •  Ant,  shell  scripts  and  Cloud   FormaKon   •  cloudinit  for  “bootstrapping”   soOware  on  to  the  instances    
  • 8. Phoenix Server •  Axiom:  It  is  easier  to  create  new   instances  and  install  soOware  on  to   them  than  it  is  to  try  and  upgrade   and  reconfigure  soOware  on   exisKng  instances   •  Wanted  to  avoid  complex  chef/puppet  scripts     •  We  avoided  chef/puppet  enKrely  J   •  “Banned”  manual  updates  to  deployed   instances  
  • 9. Why a graph database? Map  ©  Transport  for  Greater  Manchester  2013   3   3   5   5   2   2   2   2  
  • 10. Tram Data… •  Tabular  Data  in  text  file    •  4  Important  Concepts   •  Stops   •  Routes   •  Services   •  Trips  
  • 11. Graph Model – Iteration 1 A1   A2   B1   B2   3   3   C1   C2   4   4   D1   D2   2   2   E1   E2   3   3   G2   F2   3   2   G1   F1   2  
  • 12. Graph Model – Iteration 2 A1   A2   B1   B2   C1   C2   D1   D2   E1   E2   G2   F2   G1   F1   S1  
  • 13. Graph Model – Iteration 3 A1   A2   B1   B2   C1   C2   D1   D2   E1   E2   G2   F2   G1   F1   S1   S2   S3   S4  
  • 14. Graph Model – Iteration 4 A1   A2   B1   B2   C1   C2   D1   D2   E1   E2   R1   A1   R1   B1   3   R1   C1   4   R1   D1   2   R1   E1   3   5   1   A1   5   1   5   1   5   1   5   1  
  • 15. Time Dependent Graph A   B   T1  (08:00)   T2  (08:12)   T3  (08:24)   T4  (08:36)   T5  (08:48)   T6  (09:00)   T7  (09:12)   T8  (09:24)   T9  (09:36)   T10  (09:48)   T11  (10:00)   T12  (10:12)   Up  to  900  RelaKonships   C   T1  (08:05)   T2  (08:17)   T3  (08:29)   T4  (08:41)   T5  (08:53)   T6  (09:05)   T7  (09:17)   T8  (09:29)   T9  (09:41)   T10  (09:53)   T11  (10:05)   T12  (10:17)  
  • 16. Heuristics A   B   T4  (08:36)   T5  (08:48)   T6  (09:00)   T7  (09:12)   T8  (09:24)   C   T4  (08:41)   T5  (08:53)   T6  (09:05)   T7  (09:17)   T8  (09:29)  
  • 17. Geek Night Next  Wednesday    September  25th     An  introducKon  to     Graph  Databases  
  • 19. How did the team do? More  important  Less  important   Tech  Learning   Produce  Collateral   Excite  community   Working  soOware  to  demo   ✔ •  Learnt  about  the  pros  and  cons  of  graph  databases   •  Proved  workability  of  this  approach   •  Re-­‐enforces  view  that  need  to  pick  the  right  Database   model  for  the  domain   •  Learnt  more  about  using  cloud  formaKon  and  cloudinit  
  • 20. How did the team do? More  important  Less  important   Tech  Learning   Produce  Collateral   Excite  community   Working  soOware  to  demo   ✔ •  Built  a  working  mobile  web  applicaKon   •  More  successful  than  we  thought!   •  Local  media  caught  on   •  In  daily  use  
  • 21. How did the team do? More  important  Less  important   Tech  Learning   Produce  Collateral   Excite  community   Working  soOware  to  demo   ✔ •  Able  to  produce  diaries,  presentaKons,  whitepapers,   videos,  conferences,  and  labs   •  Including  this  talk  ;-­‐)   •  Geek  Night   •  New  York  GraphConnect  Conference    
  • 22. How did the team do? More  important  Less  important   Tech  Learning   Produce  Collateral   Excite  community   Working  soOware  to  demo   ✔ •  Lots  of  interest  inside  of  ThoughtWorks   •  Internal  talks  and  presentaKons  conKnue   •  Interest  outside  of  ThoughtWorks  as  well   •  Next  steps….?  
  • 23. A nice problem to have…..
  • 24. Next Steps? •  Would  our  clients  be   interesKng  in  doing  TechLabs?   •  Team  are  passionate  and   want  to  conKnue   – Your  Ideas?   – Do  we  Open  Source?   •  Feature  requests  are  sKll   arriving…..  
  • 25. Any Questions? •  Check  out  the  app  at   – hUp://www.tramchester.co.uk   – @tramchester