A step by step guide to deploying the InfluxDB/Telegraf/Grafana stack on Kubernetes. How to map configuration files, data folders, and environment variables?
This article follows our first blog post related to Kraken’s deployment on Kubernetes. It is a step by step guide explaining how to deploy the InfluxDb/Telegraf/Grafana stack used to generate load testing reports on Kraken.
More importantly we will se:
How to map a configuration file using a ConfigMap resource? How to map sensitive environment variables using the Secrets object? How to use Kompose to generate declarative K8S configuration?
A step by step guide to deploying an Angular frontend behind an NGinx Ingress on Kubernetes. K8S installation, Ingress controller deployment and frontend application proxying.
Kraken is a load testing solution currently deployed on Docker. In order to use several injectors (Gatling) while running a load test, its next version might rely on Kubernetes.
Kubernetes (commonly referred to as “K8s”) is an open source system that aims to provide a platform for automating the deployment, scalability and implementation of application containers on server clusters. It works with a variety of container technologies, and is often used with Docker.
How to create an Angular 8 project with multiple applications and libraries? This guide uses the Kraken Load Testing IDE front as an Angular 8 workspace example.
OctoPerf’s Load Testing IDE (Kraken) is an application with two frontends:
The Administration UI used to manage Docker containers and images, The Gatling UI to debug and execute load tests with Gatling. Both UI are based on Angular 8 and share many components, CSS and external library dependencies.
This blog post is a guide for every developer that would like to create an Angular Workspace with several applications and libraries.
Looking at ways of managing test data to support performance testing. From general principles to a complete example.
Introduction We are going to talk about data in this blog post, predominately test data required for performance testing.
This is something that makes the life of a performance tester extremely difficult and awkward as because of the huge quantities required, in the right state, that match the criteria required for your test to run.
We often have to approach the use of large quantities data for the purpose of performance testing in a number of ways:
How to create a multi-modules Maven project in the Gradle world? This guide uses the Kraken project as an example to help you get started with complex Gradle builds.
The creation of a Load Testing IDE (Kraken) was for me the opportunity to check on new technologies:
I wanted to try another build solution for my Java backends. I used Maven for several years, both on OctoPerf and in my previous work experiences. Moving from Maven to Gradle is not necessarily easy, as the concepts involved are different
This blog post is a guide for every developer with a Maven background that would like to give a try to Gradle (version 5.
How a proof of concept on some technologies became a full-featured project: Kraken, the load and performance testing IDE.
About 8 months back, after a few years working on the same technology stack used for OctoPerf, I wanted to check if we should follow the latest trends: micro-services and reactive programming.
Re-building OctoPerf with other technologies, just for a POC, seemed way too long. After all, the development of the frontend alone took me a few years, not to mention the backend … OctoPerf comes with really advanced features regarding load-testing!
Non-Functional requirements, what are they, how to define them and how to test them
Introduction What are they?
Well, non-functional requirements are requirements that define the operation of the system under test rather than the behaviour of the system under test, or the functional requirements as these are known.
The categories under which non-functional requirements are grouped are numerous with a degree of overlap, we are going to attempt to demystify some of these whilst attempting to articulate how they can be tested and some of the common pitfalls.
OctoPerf 10.6 is out, you can now connect OctoPerf to your own Microsoft Azure account and use Gitlab CI to run tests, and of course many quality of life improvements.
Improvements Microsoft Azure We are pleased to announce that you can now connect your own Microsoft Azure account to OctoPerf This way OctoPerf starts agents automatically for you inside your Azure environment exactly the same way we do with AWS. It’s a neat option to avoid permanent firewall rules or load agents. Also Azure provides a large number of datacenters. As usual it is also available with your OctoPerf free account.
The subject of this post is a look at whether JMeter is a good alternative to LoadRunner. In-depth comparison oh both load testing solutions.
The subject of this post is ‘Is JMeter, a good alternative to LoadRunner’.
The short answer is yes absolutely, the longer answer is of course a lot more complex and interesting and worthy of discussion.
We will not discuss the more technical aspects of the tools as there are many, many posts talk about this already and it’s not worth repeating the same thing again.
Let’s look at it from a usability in the real world perspective.
Wondering what’s the difference between @Service, @Controller, @Component or @Repository spring annotations? Learn the key differences between those annotations and use them wisely.
If you’re here, it’s probably because you have never really understood the differences between those Spring annotations:
What is the Spring @Service annotation for? What’s the key difference between a class annotated with @Component and @Service? How can I use @PostConstruct and @PreDestroy? The bad news is Your search is over! It’s finally time to get a better understanding of when and how to use those annotations.