We have a service that can generate million of transactions in short period of time, even few seconds. We started the API backend with RoR on a robust cloud service. We had few customers at the beginning and few transactions. Then, before starting the first big event we made some load test, and we understood that we needed more performance. We have changed the platform many times: servers, languages from RoR, C++, C#, C# mono, to Go. Now, we are still using Go. I will show you the pros and cons in all different scenarios.

1. We started with RoR, C++, C#, nodeJS and...
at the end we chose GO
Maurizio de Gregorio
Emilio de Lazzari
MILAN 25-26 NOVEMBER 2016

2. Agenda
What to expect from this speech
What is Parterre
The Platform Story
Current Platform
Future Development
2

3. The Platform Story
Maurizio de Gregorio
CEO & Founder, Parterre
Business Development & Data Scientist

4. 4
Audience engagement and Data Mining
ENGAGE YOUR AUDIENCE
COLLECT DATA

5. 5
Audience engagement and Data Mining
ENGAGE YOUR AUDIENCE
COLLECT DATA

6. Millions of
transactions
6
concentrated in spikes of almost 10K t/s
cloud load-balancer
auto-scaling
DB RDScosts

7. High
Performance
7
API Server
load-test
check-performance
AWS bees

8. RoR
8
Powerful Framework
Big Developers community
Transactions/s: Low
Thin
Unicorn
nginx

9. C++
9
Performance: Highest
Know how: Low level programming interface
Deployment: dependencies -> complex
Troubleshooting: memory leak -> complex

10. C# mono
10
Performance: High
Know how: easy to find developers
Deployment: dependencies -> complex
Troubleshooting: complex

11. Load Test
11
Current Implementation

12. Test Results - Apache AB
12
server@social:~$ ab -n 1000 -c 300 http://parterre.eu/api3/xxx
This is ApacheBench, Version 2.3 <$Revision: 1528965 $>
Copyright 1996 Adam Twiss, Zeus Technology Ltd, http://www.zeustech.net/
Licensed to The Apache Software Foundation, http://www.apache.org/
Server Software:
Server Hostname: parterre.eu
Server Port: 80
Document Length: 1086 bytes
Concurrency Level: 300
Time taken for tests: 0.257 seconds
Complete requests: 1000
Failed requests: 0
Total transferred: 1243000 bytes
HTML transferred: 1086000 bytes
Requests per second: 3891.55 [#/sec] (mean)
Time per request: 77.090 [ms] (mean)
Time per request: 0.257 [ms] (mean, across all concurrent requests)
Transfer rate: 4723.83 [Kbytes/sec] received
Connection Times (ms)
min mean[+/-sd] median max
Connect: 10 22 4.4 23 33
Processing: 18 33 12.0 31 234
Waiting: 18 33 12.0 31 234
Total: 34 55 12.1 55 254

13. Test Results - Amazon Bees
13
$ bees up -s 5
$ bees attack -n 20000 -c 4500 -u “http://parterre.eu/api3/xxx“
Read 5 bees from the roster.
Connecting to the hive.
Assembling bees.
Each of 5 bees will fire 4000 rounds, 900 at a time.
Stinging URL so it will be cached for the attack.
Organizing the swarm.
Bee 0 is firing his machine gun. Bang bang!
Bee 2 is firing his machine gun. Bang bang!
Bee 1 is firing his machine gun. Bang bang!
Bee 4 is firing his machine gun. Bang bang!
Bee 3 is firing his machine gun. Bang bang!
Bee 2 is out of ammo.
Bee 0 is out of ammo.
Bee 1 is out of ammo.
Bee 4 is out of ammo.
Bee 3 is out of ammo.
Offensive complete.
Complete requests: 20000
Requests per second: 9650.760000 [#/sec] (mean)
Time per request: 62.9969400 [ms] (mean)
50% response time: 56.6800000 [ms] (mean)
90% response time: 67.7800000 [ms] (mean)
Mission Assessment: Target successfully fended off the swarm.
The swarm is awaiting new orders.
multi instance generator

14. Resources Monitor
14
NANO machines @ < 10% CPU

15. Case Study: GO Platform
Emilio De Lazzari
CTO & Founder
Backend Architect & Developer

16. Golang why?
Environment
16
Least dependencies
Indifferent to updates

17. Strong Typed
17
Compiled Language
Compile time error checking
IDE autocomplete suggestion
Refactoring

18. Deployment
18
Machine state
All dependencies inside
Single Executable
Fast

19. Cross Compile
19
MAC, Windows & Linux single executable
Tests and debugging
Compile for the target ready to deploy

20. Performance
20
Speed comparable to C++ code
Exceptional use of machine resources

21. IMPROVEMENT of the PLATFORM
21

22. Parterre platform
22

23. Parterre Team
Maurizio de Gregorio
CEO & Founder
Business Development &
Data Scientist
Emilio De Lazzari
CTO & Founder
Backend Architect & Developer
23
Claudio Bonucci
Junior Developer
Riccardo Pizzoni
Senior Developer

24. Summary and Q&A
24
STRONG TYPED LANGUAGE
PRODUCTION DEPENDENCY FREE
FAST DEPLOYMENT
CROSS COMPILE
PERFORMANCE

25. Thank you.
ENGAGE YOUR AUDIENCE
COLLECT DATA
http://parterre.eu