IT systems testing *

A story about evolving our CI process for a monolithic Python repo with tests, challenges faced, and solutions. Discussing Docker, linters, Allure TestOps, and more.

Hi, I’m Nastya, the Product Owner of EXANTE’s desktop and web trading terminals. I began working at the company nearly five years ago as a Junior QA Engineer. Since then, I’ve advanced to QA Lead and ultimately to Product Owner. In this article, I’d like to share my growth journey within the company and the steps that helped me progress. I hope that my story will be helpful to those seeking to advance their careers but are unsure where to start.

In today's fast-paced world of software development, integrating third-party APIs and services is a common practice. These integrations can enhance functionality, improve user experience, and provide additional features that would be time-consuming and costly to develop in-house. However, ensuring these integrations work seamlessly with your software is crucial, and this is where the importance of a test environment, or sandbox, comes into play.

A sandbox environment allows developers to test the integration between their software and third-party services without risking the stability and security of the production environment. This controlled setting enables thorough testing, helping to uncover issues before they affect end-users. By covering as many test cases as possible, developers can ensure robust and reliable integrations.

But what if your third-party provider, such as a bank or government e-system, does not offer a sandbox environment? This scenario can pose significant challenges, but there are several strategies you can employ to mitigate these issues.

Hello everyone, my name is Denis, I am Software Developer Engineer in Test (SDET) at Bimeister. I am in charge of test software development - frameworks, automated tests, CI Pipelines configuration, and much more.

In this article, I will tell you how we defeated the Stale Element Reference Exception while developing our framework using Selenium WebDriver and C#.

The common combination of JUnit5, Selenide and Allure has proven to be stable and reliable for autotesting. The remaining issue, however, lies in test length increase up until the rise of overall test numbers. The resulting video files turn out to be over an hour. Alexander Kochergin, Lead engineer at Innotech, has found a way to simplify the process.

The Positive Hack Days 11 forum, which took place May 18–19, 2022, was truly epic. The bitterly fought ATM hacking contest featured no fewer than 49 participants. How cool is that? The winner of this year's prize fund of 50,000 rubles, with the handle Igor, was the first to hack the virtual machines. And he wasn't even at the event! :)

Besides Igor, eight other participants picked up prizes this year for their VM-hacking skills. They were: drd0c, vient, vrazov, durcm, zxcvcxzas7, asg_krd, hundred303, and drink_more_water_dude. A big thank-you to everyone who took part, and for those who weren't at PHDays, here are the links to the virtual machines.

Testing is one of the key processes in development. However, without analysis it is tough to say how effective testers really are. Innotech’s lead tester-engineer Pavel Petrov shared a number of metrics that are being used in project work.

A tester is one of the most stressful roles in IT. You constantly need to be concentrated and report bugs to developers in your team. Lidiya Yegorova, Innotech’s “Scoring conveyor” team QA-Lead shared her practices on how to minimize the stress while testing.

A website with bugs could be a real pain in the neck for business. Just one 404 or 500 error could end up costing an obscene amount of money for the company and hurt a good reputation. But there is a way to avoid this issue: the website testing. That's sort of what this article is about. After reading this article, you will learn how to test code in Django, create your "own website tester" and much more. Welcome to the article.

Test automation, with product built in microservice architecture could be very situational in context of testing goals and ways to achieve them. You got an easy life if you testing a service, that is an isolated entity, which is receiving some data and providing a result of it's work in a response, by callback or through additional endpoint. In this case all you need to do is cover all the endpoints of the service, and probably learn to catch it's callbacks. However, it's not the only case. Sometimes you need to test service which isn't totally isolated, but a part of a chain of interactions. This service could send some data to other services within your infrastructure or even to third parties. This time you got plenty of additional things to bother of:

Nothing and nobody will escape oblivion. Whatever you may say, the history of mankind is a history of automation and the subsequent evolution of workers. This happened both during the first industrial revolution and during the second. The same thing happened with digital revolution. Now machine learning and artificial intelligence are being implemented everywhere. What is the future of software testing?

I have already written about AIOps and machine learning methods in working with IT incidents, about hybrid umbrella monitoring and various approaches to service management. Now I would like to share a very specific algorithm, how one can quickly get information about functioning conditions of business applications using synthetic monitoring and how to build, on this basis, the health metric of business services at no special cost. The story is based on a real case of implementing the algorithm into the IT system of one of the airlines.

Currently there are many APM systems, such as Appdynamics, Dynatrace, and others, having a UX control module inside that uses synthetic checks. And if the task is to learn about failures quicker than customers, I will tell you why all these APM systems are not needed. Also, nowadays health metrics are a fashionable feature of APM and I will show how you can build them without APM. 

What happens to your MongoDB replica set when it comes to failures like network partitioning, restarting, reconfiguration of the existing topology, etc.? This question is especially important these days because of the popularity gained by the multi-cloud model where chances of these scenarios are quite realistic.

However, is there a solution, preferably a free one, for testing such cases that would obviate the need of writing manual scripts and poring over the official documentation? As software developers, we would be better off preparing our applications in advance to survive these failures.

Before we start, I'd like to get on the same page with you. So, could you please answer? How much time will it take to:

• Create a new environment for testing?
• Update java & OS in the docker image?
• Grant access to servers?

It will take longer than you expect. I will explain why.

It is the translation of my speech at DevOps-40 2020-03-18:

After the second commit, each code becomes legacy. It happens because the original ideas do not meet actual requirements for the system. It is not bad or good thing. It is the nature of infrastructure & agreements between people. Refactoring should align requirements & actual state. Let me call it Infrastructure as Code refactoring.

Recently I had to add python3.8 for our Python linter (the strictest one in existence): wemake-python-styleguide. And during this straight-forward (at first look) task, I have found several problems with test coverage that were not solved in Python community at all.

Let's dig into it.