Charla en español sobre Modelaje de Pruebas de rendimiento

1. Performance Modelling
Matemáticas y sentido común

2. import random
import time
import requests
class Speaker(object):
def __init__(self):
born = "Avilés - Asturias"
studies = "Applied Maths and Computability"
jobdescription = "Performance Jedi"
company = "Telefónica I+D"
team = "Product Engineering"
project = "AWAZZA"
talks = [VLC Testing, DevopsDays, WebPerfDays, Velocity]
def talk(self):
start_timer = time.time()
r = requests.get('http://www.slideshare.net/almudenavivanco')
r.raw.read()
latency = time.time() - start_timer
self.custom_timers[‘After Test 2016'] = latency
if __name__ == '__main__':
speech = Speaker()
speech.talk()
print trans.custom_timers
Almudena Vivanco
(@MrsDaehin)

3. Users vs request
• ¿cuánto aguanta nuestra plataforma?

4. SCENARIOS: Identify the scenarios that are most commonly executed or most resource-intensive

5. WORKLOAD MODEL: User Session Duration in average. It is important to define the load levels that will translate into
concurrent usage, overslapping users, or user sessions per second.

6. USER SCENARIO: Navigational Path, including intermediate steps or activities, taken by the user to complete a task. We will
call it User Session from now on.

7. THINK TIMES: User thinktimes → Pause between pages during a User Session depending on the User Type*

8. User Types: Identify the User … new, revisiting or both.

9. Performance Acceptance Criteria: Response time, System load, Throughput ...

10. METRICS: Only well-selected metrics that are analyzed correctly and contextually provide information of value.

11. DESIGN TEST: Using your scenarios, key metrics, and workload analysis …

12. RUN TEST: the load simulation must reflect the test design

13. ANALYZE RESULTS: Find bottlenecks, memory leaks, cpu hogs, bad sofware design …

14. The Maths behind

15. “mi tiempo medio de respuesta está
bien."

16. Afterwards … in PROD ...

17. Performance
It's not just about adding more servers

18. Apdex Index
t = acceptable response time
satisfied = response time < t
tolerating = t < response time > 4t
frustrated = response time > 4t
Apdex [t] = (satisfied + tolerating/2)/total requests

19. • Percentiles
• Moda
• Media
• Mediana
• Desviación Estándar

21. Matemáticas y Sentido Común
http://www.raosoft.com/samplesize.html

28. Distribución de Poisson

29. Modelando el uso de la aplicación
Identificar el objetivo de la prueba
• Volumen de tráfico?
• Escala?
• Picos de carga?
• Robusto?

31. Estadísticas
Sesión
Páginas Vistas
Flujo
Dispositivo
Localizacion

32. Modelización y Jmeter
JMeter

34. Jmeter Test Plan
User Defined Variables
Functional Test Mode

35. User defined Variables at Test Plan level to be used from Jenkins

36. User Behaviour in JMeter
Only Once Controllers
Cache Management
Cookie Management
Header Manager
Think Times

37. Jmeter in Cloud commercial tools

38. Resources
• http://www.raosoft.com/samplesize.html
• http://analyze.websiteoptimization.com/wso
• http://mobitest.akamai.com/m/index.cgi
• http://stevesouders.com/mobileperf/mobileperfbkm.php
• https://msdn.microsoft.com/en-us/library/bb924370.aspx
• http://www.quotium.com/performance/load-testing-