An in-depth look at OctoPerf report engine and all the report items that can make your analysis easier. We’ll even check the report comparison and throw in a few tips for good measure.
Introduction OctoPerf’s report engine provides many graphs to sort and presents test metrics in a comprehensive way. We’ve tried to improve it over the years so that you can access critical information very quickly. But requirements vary from one project to the other.
In this post we will look at how you can configure the report to show your preferred metrics, and also all the shortcuts you can take to achieve this goal.
Introduction You may have spent a considerable amount of time configuring Postman requests for your in-house API tests, and you wish to use them without having to create them again from scratch on Octoperf.
That’s one of the many situations where Octoperf’s compatibility with Jmeter is going to come in a handy.
Postman to Jmeter The first step will be to convert your requests into a JMeter-friendly format, using Postman Code Generation Snippet :
Introduction When we think of performance testing we normally think of thousands of requests with thousands of users generating huge volumes on our application under test or increasing the load until the application under test fails or runs out of resources.
This is not a good approach when determining load for your performance tests for several reasons and can in some cases render your performance testing meaningless.
This post will outline some of the pitfalls that are commonly made when it comes to generating load and will look at ways to suggest improvements to your approach to load profiles.
Introduction JMeter has many plug-ins and downloadable JAR Files you can use to support your testing, it is also possible to write your own custom Jar files and use these as well.
Why would you want to do that, you may say, well whilst it is unlikely that you would need to create anything too complicated.
You may feel the need to create utilities to support your own in-house performance testing or just something to make your testing process easier.
OctoPerf 11.9 is available, featuring new Azure on demand load generators, updated JMeter and setup/teardown actions
Introduction Here we are for yet another new release of OctoPerf. We’ve actually released two minor versions since the last update post, but this time we will also release a long awaited feature, Microsoft Azure on demand load generators!
We kept it in our beta version for a while since we wanted to be absolutely sure it can be used for proper testing. We are quite satisfied with it at the moment, but note that the agent startup time is much longer on azure than on other providers, you should expect to wait a few more minutes if you are using it.
Learn more about how Decathlon tested its new RFID platform with OctoPerf.
Context Decathlon is a network of innovative retail chains and brands providing enjoyment for all sports people.
At Decathlon, 85,000 of co-workers live a common Purpose on a daily basis: To sustainably make the pleasure and benefits of sport accessible to the many.
Decathlon presently operates in 58 countries in Retail with more than 1654 sport hypermarkets, and in 26 countries with Production.
At Decathlon, innovation is at the heart of all activities: from research to retail, including conception, design, production and logistics.
How to use the AMQP technology to share variables between VUsers during your tests with Octoperf
Introduction Variables, may they be constant or dynamic, are an essential part of load testing.
We already learned how to manipulate these values by extracting and re-injecting them inside one Virtual User.
But what if we need to share these values between several Virtual Users ?
In this blog post, I will show you just how to do that, using the MQ technology.
What is AMQP ? Advanced Message Queuing Protocol (AMPQ) is an open standard protocol that allows messages exchanges between different systems.
How to improve a dynamic Virtual User by using loops, conditional statements and pauses? This articles give you tool to make your load tests even more realistic and meaningful.
This blog post is a guide to help you write Gatling scripts in order to load test web applications efficiently. It follows our second Gatling Simulation scripts parameterization article.
We will continue to load test a fake e-commerce, and so we are going to improve our Virtual User to make it browse the store in a more humanly way. To do it we will cover several topics:
Loops to make it browse several articles of each category, Conditions to change its behavior depending on dynamic parameters, Pauses to simulate a real user think-time.
A deep dive into how SNCF replaced performance center and JMeter with OctoPerf.
Context Most of you have already recognized the name SNCF, it is obviously one that is hard to miss when you live in France. But for everybody else, allow me to do a quick reminder of what SNCF stands for.
The Société Nationale des Chemins de fer Français (Chemin de fer, literally, ‘path of iron’, means railway) is France‘s national state-owned railway company. It operates 32,000 km (20,000 mi) of route and in 2017 had €33.
OctoPerf 11.7 is available, with new pacing/throughput options, improved load agent monitoring, dynatrace integration and many smaller features
Introduction This new release of OctoPerf brings a lot of long awaited features. This is all based on your feedback, so make sure to let us know what you would like to see in OctoPerf next!
Of course we have a few plans of our own for the future, but I strongly believe that a good software can only result from a good collaboration between users and developers.
Improvements Pacing your execution Throughput If you ever had to execute a load test campaign you are probably aware that it’s not only a question of concurrent users, you also need to define the execution rate of each user.