The document provides an overview of performance testing, emphasizing its importance in evaluating system responsiveness and stability. It introduces Gatling, a performance testing tool written in Scala that enables efficient load testing and integrates easily with CI/CD pipelines. Key features include dynamic reporting, high concurrency support, and the use of asynchronous I/O to enhance performance compared to traditional tools.

1. Performance Test Automation
With Gatling
Gaurav Kumar Shukla
Trainee Software Consultant
Knoldus Software LLP

2. Agenda
● Performance Testing
● Performance related testing and tools
● Load testing (The Gatling way)
● Demo

3. Performance Testing
Performance testing, a non-functional testing technique performed to
determine the system parameters in terms of responsiveness and
stability under various workload. Performance testing measures the
quality attributes of the system, such as scalability, reliability and
resource usage.

4. Conti...
Performance is very crucial part of an application so it is very
important to keep our eyes on following points
● Response time
● Throughput
● Scalability
● Availability

5. Performance Related Testing
● Load Testing
● Stress Testing
● Spike Testing
● Endurance Testing
● Scalability Testing
● Volume Testing

6. Performance testing tools
There are many tools available in the market with their own feture
which enables to test the performance of the applicaiton in more
efficient way.
Open Source Tools License Tools
JMeter Load Runner
Jcrawler Silk Performer
loadUI Rational Performance Tester
The Grinder Cloud Test

7. Let's start With Gatling

8. About Gatling
Gatling is a lightwaight dsl written in scala by which you can treat your
performance test as a production code means you can easily write a
readable code to test the performance of an application it s a framework
based on Scala, Akka and Netty.

9. Why Gatling
● Dynamic Reports :- Gatling's reports are clear, concise, dynamic and
exhaustive. Share it with your team and get everyone on board.
● Continuous integration and performance testing :- Gatling’s code-like
scripting is a new approach of performance testing. Experience
continuous integration with the Maven, SBT and Jenkins’ plugins.
● High concurrency rate :- Gatling is based on cutting-edge
technologies and frameworks like Scala, Akka and Netty. High
performance and efficiency are Gatling’s DNA.

10. ● Thanks to Stéphane Landelle is the main contributor and creator of
Gatling tool.
● The latest stable release is : Gatling 2.1.7
● There are various Key features with Gatling 2.1.7.
● DSL for simulation to treat performance as a code
● Produces higher load by using an asynchronous non-
blocking approach.
● Full support of HTTP(S) protocols
● Supports input files CSV, TSV, SSV to access random data for
data-driven tests.
● Generation of graphical reports using Graphite

11. Benifits of using Gatling
• All reports and graphs are generated automatically in HTML after
successful execution
• It is able to sustain high concurrent load with no obvious
degradation in response times at 20K users
• It gives more accurate results with less memory and CPU usage
• It can run on any operating system

12. Why Gatling
• It is an Open source stress testing tool under apache license.
• Easy to understand and reuse our simulation scripts to perform
operations again and again.
• Less Cpu utilization
• It can simulate multiple virtual users with a single Thread
• Gatling has a separate web proxy recorder, which enables to
generates a Scala simulation from the recorded user session.
• Generation of graphical reports using Graphite
• Easily integrate gatling with jenkins and other delivery tools and
continiously get the update of ur performance test against ur
applicaiton .

13. Issues with other tools
● Performance
● Blocking IO
● Usability
● Maintainability
● Matrices
● Plugins
● Demo

14. Performance :-
● Traditional Approach works on
1 virtual user = 1 Thread
50 virtual user = 50 Threads
10000 virtual user = 10000 Threads
● There is a lots of context switching, lots of cpu utilization occurs at the
time of process scheduling.
● It consume approx 60% to 70% cpu at the time of execution which
degrade the system performance.

15. Blocking IO
Most of the tools work on this approach :-
● In this Approach if 10000 requests sends then the most of the time
Your threads are sleeping.
● Drastically increase the responce time and degrade the performance.

16. The Gatling Approach
● Gatling Increase the performance with asynchronous akka actor
model.
● Actor model consist in two small entities
– MailBox- Stores all the messages recieved
– Computational unit- Execute a predefine action for each recieved
message

17. Gatling:- NonBlocking I/O
● Gatling uses Java framework Netty which is the no 1 Non-blocking
I/O framework running on the jvm.
● Which increase the response time of the threads and make the
application more responsive.

18. Usability Issue
● Most of the tools are comming with there own GUI platform.
● It is good even more compatible but the problems are more complex
then Hello world program.
– Versioning
– Refactoring
– Peer Review

19. Gatling = (Real programming language + Dsl +Api)
● As an Automation Tester
– Deals with the real code
– Easily able to use the various Api
– To write their own code which is more flexible to perform the Gui
operations and resolve these issues
– Versioning
– Refactoring
– Pear Review

20. Maintainability
● Most of the tools have their own default save mode.
– For example :- Jmeter save your result in Xml format .
Problems:-
● very difficult to understand
● Its not possible to change and edit these result
● To perform operations like git merge there is conflict occures
● Using gatling saves the result in normal scala format.
● Easy to understand
● Easy to make cahnges in the scripts
● Resolve the conflict easily

21. Matrics issue
● The next thing is about what kind of matrix you use.
● Most of the tools providing
– Minimum Value
– Maximum Value
– Average Time
– Standard Daviations
● For the accurate result they are using standard daviation.
● Sometimes the standard daviations are the crap.
● Standard daviation only meaningful for the normal distribution and the
real time distribution in IT systems never based on the normal
distribution.

22. Gatling :- Percentiles
● To resolve the matrics issue gatling uses the percentile approach.
Nth percentile = value >= Nth % of the value
● To implement the percentile there is proper java libraries are available
● HtrHistogram
● Tdigest

23. Plugins
● Inbuild plugins
● Websocket
● SSE
● JMS support
● Maven plugin
● Maven Artifacts
● Maven Archetype
● SBT plugin
● Jenkins Plugin

24. ● Third party Plugins
● Gradle
● Cassandra
● AMQP
● RabbitMQ
● SQL

25. Special Thanks to
Stéphane Landelle

26. References
1) http://gatling.io/docs/2.1.7
2) http://gatling.io/docs/2.1.7/extensions/sbt_plugin.html
3) https://www.youtube.com/watch?v=VUPTaPms210

27. Thank You