Gatling is a load testing tool that uses an asynchronous, non-blocking model to address issues with other tools like JMeter. It provides a DSL for writing scalable load tests and integrates with tools like Maven. Gatling aims to make load testing easy, powerful, and maintainable compared to other options. It has been gaining popularity since its first commit in 2011.
Gatling is Open Source Stress testing tool.
Why Gatling:
- High Performance.
- Multi Threading vs (Akka) Actor Model.
- Synchronous Blocking IOs vs asynchronous Non-blocking IOs Netty.
Gatling, one of the most popular stress test OSS frameworks, is powered by Akka and Scala. In this talk I share insight gained while working with and customizing Gatling to exercise Protobuf-based backed services. I also show how to use Gatling for web applications.
Performance Test Automation With GatlingKnoldus Inc.
Gatling is a lightweight 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.
In 30 minutes I would like to show:
1. Why is it worth to spend some time and learn Gatling - a tool for integration/performance test of your web application?
2. Under what circumstances it is necessary to have Gatling in your toolbox?
3. What are Gatling cons and what kind of problems can you expect?
For sure there is no silver bullet in testing tools area, but you will definitely love Gatling DSL.
Gatling is Open Source Stress testing tool.
Why Gatling:
- High Performance.
- Multi Threading vs (Akka) Actor Model.
- Synchronous Blocking IOs vs asynchronous Non-blocking IOs Netty.
Gatling, one of the most popular stress test OSS frameworks, is powered by Akka and Scala. In this talk I share insight gained while working with and customizing Gatling to exercise Protobuf-based backed services. I also show how to use Gatling for web applications.
Performance Test Automation With GatlingKnoldus Inc.
Gatling is a lightweight 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.
In 30 minutes I would like to show:
1. Why is it worth to spend some time and learn Gatling - a tool for integration/performance test of your web application?
2. Under what circumstances it is necessary to have Gatling in your toolbox?
3. What are Gatling cons and what kind of problems can you expect?
For sure there is no silver bullet in testing tools area, but you will definitely love Gatling DSL.
Performance Testing is a type of testing to ensure software applications will perform well under their expected workload.
It evaluates the quality or capability of a product. Take your Performance Tests to next level with Gatling!
Gatling is a project that can be used as a load testing tool for analyzing and measuring the performance of a variety of services, with a focus on web applications. It is Scala-based, high performance load and stress test tool.
How to test-drive your Qt QML code. Overview on how you do simple testing, UI level testing, synchronous testing, data-driven testing.
These are the slides used in the Helsinki MeeGo meetup in 2012.
Performance optimization techniques for Java codeAttila Balazs
The presentation covers the the basics of performance optimizations for real-world Java code. It starts with a theoretical overview of the concepts followed by several live demos
showing how performance bottlenecks can be diagnosed and eliminated. The demos include some non-trivial multi-threaded examples
inspired by real-world applications.
Java Performance: What developers must knowDiego Lemos
In my career, I could help some companies to solve many application performance issues. After several suggestions from colleagues, I have tried to put together in this presentation the main points that I think Java developer should take into account to fix and prevent performance issues.
Load Testing with Taurus using Jenkins and AWSGuy Salton
How to use Taurus, an open source automation framework to easily create and run open source load testing tools from CI and scale your tests with BlazeMeter
How to test-drive your Qt QML code. Overview on how you do simple testing, UI level testing, synchronous testing, data-driven testing.
These are the slides used on the Tampere MeeGo meetup on March 15, 2011 and text may not be super clear for those who didn't attend the meetup. You can still download the example and examine it.
Reactive by example - at Reversim Summit 2015Eran Harel
Explaining the reactive manifesto by a real world case study.
This is a cool story about the evolution of our monitoring infrastructure. From the naive approach to a super resilient system.
How do we manage to handle 4M metrics / minute, and over 1K concurrent connections?
What strategies did we try to apply and where did it fail?
What are the techniques and technologies we use in order to achieve this?
How do we handle errors, and failures at this scale?
What can we still improve?
Ob1k is a new open source RPC container. it belongs to a new breed of frameworks that tries to improve on the classic J2EE model by embedding the server and reducing redundant bloatware. Ob1k supports two modes of operations: sync and async, the async mode aims for maximum performance by adopting reactive principals like using non-blocking code and functional composition using futures. Ob1k also aims to be ops/devops friendly by being self contained and easily configured.
Antifragility and testing for distributed systems failureDiUS
Failure is inevitable. In our modern world filled with continuously delivered and increasingly complex distributed architectures (looking at you micro-services), it is important to be able to test and improve our systems under a range of failure conditions.
In this talk, Matt discusses these complexities and the forces they exert on development teams, presenting some simple strategies and practical advice to deal with them.
Après avoir fait ce talk à la conférence NSSpain, Simone Civetta va nous expliquer sur quelles métriques il est possible de se baser pour évaluer la qualité d’un code source. Cette question étant toujours sujette à débat, préparez vos arguments !
Gatling - oružje u redovima performansnog testiranjaA. Kranjec
Nefunkcionalno testiranje je bitan, ali često zaboravljen element u procesu razvoju aplikacija. Gatling je alat za simulaciju opterećenja na testiranoj aplikaciji, provodi pripadna mjerenja i prezentira rezultate provedenog performansnog testiranja. Zašto je Gatling primijećen od strane ThoughtWorks radara? Zato što je alat baziran na Akka, Netty i Scala tehnologijama te će predavanje pokazati da pisanje performansnih testova ne mora biti dosadno. Uz koncept i metodologiju performansnog testiranja, korištenjem Gatlinga, autor će iznijeti osobna iskustva sa dosadašnjih projekata testiranja JVM aplikacija. Prezentacija sa konferencije JavaCro'14.
Performance Testing is a type of testing to ensure software applications will perform well under their expected workload.
It evaluates the quality or capability of a product. Take your Performance Tests to next level with Gatling!
Gatling is a project that can be used as a load testing tool for analyzing and measuring the performance of a variety of services, with a focus on web applications. It is Scala-based, high performance load and stress test tool.
How to test-drive your Qt QML code. Overview on how you do simple testing, UI level testing, synchronous testing, data-driven testing.
These are the slides used in the Helsinki MeeGo meetup in 2012.
Performance optimization techniques for Java codeAttila Balazs
The presentation covers the the basics of performance optimizations for real-world Java code. It starts with a theoretical overview of the concepts followed by several live demos
showing how performance bottlenecks can be diagnosed and eliminated. The demos include some non-trivial multi-threaded examples
inspired by real-world applications.
Java Performance: What developers must knowDiego Lemos
In my career, I could help some companies to solve many application performance issues. After several suggestions from colleagues, I have tried to put together in this presentation the main points that I think Java developer should take into account to fix and prevent performance issues.
Load Testing with Taurus using Jenkins and AWSGuy Salton
How to use Taurus, an open source automation framework to easily create and run open source load testing tools from CI and scale your tests with BlazeMeter
How to test-drive your Qt QML code. Overview on how you do simple testing, UI level testing, synchronous testing, data-driven testing.
These are the slides used on the Tampere MeeGo meetup on March 15, 2011 and text may not be super clear for those who didn't attend the meetup. You can still download the example and examine it.
Reactive by example - at Reversim Summit 2015Eran Harel
Explaining the reactive manifesto by a real world case study.
This is a cool story about the evolution of our monitoring infrastructure. From the naive approach to a super resilient system.
How do we manage to handle 4M metrics / minute, and over 1K concurrent connections?
What strategies did we try to apply and where did it fail?
What are the techniques and technologies we use in order to achieve this?
How do we handle errors, and failures at this scale?
What can we still improve?
Ob1k is a new open source RPC container. it belongs to a new breed of frameworks that tries to improve on the classic J2EE model by embedding the server and reducing redundant bloatware. Ob1k supports two modes of operations: sync and async, the async mode aims for maximum performance by adopting reactive principals like using non-blocking code and functional composition using futures. Ob1k also aims to be ops/devops friendly by being self contained and easily configured.
Antifragility and testing for distributed systems failureDiUS
Failure is inevitable. In our modern world filled with continuously delivered and increasingly complex distributed architectures (looking at you micro-services), it is important to be able to test and improve our systems under a range of failure conditions.
In this talk, Matt discusses these complexities and the forces they exert on development teams, presenting some simple strategies and practical advice to deal with them.
Après avoir fait ce talk à la conférence NSSpain, Simone Civetta va nous expliquer sur quelles métriques il est possible de se baser pour évaluer la qualité d’un code source. Cette question étant toujours sujette à débat, préparez vos arguments !
Gatling - oružje u redovima performansnog testiranjaA. Kranjec
Nefunkcionalno testiranje je bitan, ali često zaboravljen element u procesu razvoju aplikacija. Gatling je alat za simulaciju opterećenja na testiranoj aplikaciji, provodi pripadna mjerenja i prezentira rezultate provedenog performansnog testiranja. Zašto je Gatling primijećen od strane ThoughtWorks radara? Zato što je alat baziran na Akka, Netty i Scala tehnologijama te će predavanje pokazati da pisanje performansnih testova ne mora biti dosadno. Uz koncept i metodologiju performansnog testiranja, korištenjem Gatlinga, autor će iznijeti osobna iskustva sa dosadašnjih projekata testiranja JVM aplikacija. Prezentacija sa konferencije JavaCro'14.
DSLing your System For Scalability Testing Using Gatling - Dublin Scala User ...Aman Kohli
The power of Gatling is the DSL it provides to allow writing meaningful and expressive tests. We provide an overview of the framework, a description of their development environment and goals, and present their test results.
Source code available https://github.com/lawlessc/random-response-time
Zero to Sixty: AWS OpsWorks (DMG202) | AWS re:Invent 2013Amazon Web Services
AWS OpsWorks is a solution for managing applications of any scale or complexity on the AWS cloud. Accelerate your use of OpsWorks by learning how to use several of its operational features in this Zero to Sixty session. It starts with a demo of the OpsWorks main workflows—manage and configure instances, create and deploy apps, monitoring, and security. BeachMint will explain how they set up OpsWorks as part of their continuous deployment pipeline. The session finishes off by explaining how to use the OpsWorks API and Chef recipes to automate standard operating procedures. Demos and code samples are available to all session attendees.
Are you new to AWS OpsWorks? Get up to speed for this session by first completing the 60-minute Introduction to AWS OpsWorks lab in the Self-Paced Hands-On Lab Lounge. It will lead you through all major functions of the service with a fun example.
Formation Gratuite Total Tests par les experts Java Ippon Ippon
Garantissez la qualité des vos applications par des tests efficaces : unitaire, d'intégration, de performance... Apprenez à mettre en oeuvre un harnais de tests complet et efficace avec Junit, AssertJ, Mockito, Spring Test, Arquillian, ... et assimilez les concepts du TDD et du BDD, illustré avec Cucumber. La formation Total Test Training ira encore plus loin en vous présentant l'utilisation de Sonar et le rôle des tests dans un système d'intégration continue. Enfin, les aspects liés à la mesure de la performance (instrumentation avec Metric et stress test avec JMeter et Gatling) et à l'optimisation ciblée vous permettront d'être en mesure de produire un code "propre", protégé des risques de regressions.
Gatling : Faites tomber la foudre sur votre serveur ! (Stéphane Landelle)Normandy JUG
Découvrez pourquoi (ben oui, au fait, pourquoi?) et comment stresser votre serveur: enregistrer un scenario, jouer avec le DSL, envoyer la purée et interpréter les résultats.
Why use JavaScript in Hardware? GoTo Conf - Berlin TechnicalMachine
A majority of this presentation was live demos of hardware in action (how to blink lights, send HTTP requests to an Express server, attach sensors, and an integration demo) but it also quickly goes over some reasons why you should consider using JavaScript to prototype hardware.
Let's make this test suite run faster! SoftShake 2010David Gageot
The more the tests, the longer the build. And when the build gets longer, the bugs take longer to fix, the features take longer to deploy. Every build should be minutes long, all tests included.
Now lets say, our test suite takes much longer than that. How to reduce its duration? Where to start?
Making tests become useless, converting functional tests to unit tests, running tests in parallel, building projects in parallel, doing slow tasks only once, writing fast DBMS tests... Let's share dozens of tips to fasten you test suite A LOT.
Nagios Conference 2014 - Gerald Combs - A Trillion TruthsNagios
Gerald Combs's presentation on A Trillion Truths.
The presentation was given during the Nagios World Conference North America held Oct 13th - Oct 16th, 2014 in Saint Paul, MN. For more information on the conference (including photos and videos), visit: http://go.nagios.com/conference
Modern Engineer’s Troubleshooting Tools, Techniques & Tricks at Confoo 2018Tier1app
Learn right tools, tricks and patterns to identify root cause of complex java problems in seconds (not even in minutes). Here is the presentation of Modern Engineer’s Troubleshooting Tools, Techniques & Tricks delivered at Confoo 2018
Jon liang stepped in to pinch hit on two sessions that the presenters had to miss. OpenGL and Acceleromter. Hit it out of the park. Non Game App Dev Track. 360|iDev San Jose 09
Static (ahead-of-time) compilation of code appeared in Oracle JDK 9. We have already discussed why this is necessary, and the scope of the current implementation. Now it makes sense to talk about the technical details. Anyone can easily suffer from some already known problems of current implementation. From the other hand it makes sense to test potential benefits and to try a tiny piece of bright future. But one must realize how to try it right. What information is generated by the AOT and how it is generated, how compiled AOT code interacts with Hotspot. What you can do with AOT code by external tools, and how to infiltrate into the compilation process. And of course, what grips to twist, and what will be the performance with AOT.
2018년 6월 28일 첫번째 함께하는 딥러닝 컨퍼런스에서 발표한 "내 손 위의 딥러닝_iOS에 딥러닝 심기"입니다.
앞으로 점점 더 가속화 될 모바일 딥러닝에 대해 소개합니다.
주요 내용은 아래와 같습니다.
1. 모바일 딥러닝이란 무엇인가
2. 모바일 딥러닝의 장점
3. 모바일 딥러닝의 등장 배경
4. 모바일 딥러닝 활용 방안
5. 모바일 딥러닝 iOS 구축 사례
6. 모바일 딥러닝 한계 및 극복 방법
궁금한 점이 있다면 github 혹은 메일을 활용해주세요.
Containers from Scratch: what are they made from?Giri Kuncoro
Talk from Docker meetup Jakarta. Presented and demoed various Linux kernel features that enable container runtime, i.e. chroot, namespaces, cgroups, capabilities.
13. Can you trust your results?
JMeter 2.8 perf test, expecting 300 tr/sec
http://wiki.apache.org/jmeter/JMeterPerformance?action=AttachFile&do=get&target=Transactions-2.8.png
30. Fact sheet
● First commit in june 2011
● Created by S. Landelle and R. Sertelon
● About 20k LOCs
● 21 persons have contributed to the project
● 2500 downloads since the beginning
● 650 downloads of Gatling 1.2.5
31. Really efficient?
JMeter perf test run with Gatling, expecting 300 tr/sec