Systems | Development | Analytics | API | Testing

Your testing team, from developers to testers, has put out a great amount of work to design test cases. Knowing that an error-free testing process simply does not exist, when it comes to the test execution, this one fails, while the rest passes. Or, is one of them is taking much longer to complete compared to previous runs? How do you determine if your tests have slowed down or increased their probability of failing? This requires context–historical logs from past sessions to be more specific.

Building on the promise to offer a swift testing experience to the testing community, Katalon is thrilled to announce the release of TestOps April 2021! This release adds multiple features such as integration with Pytest, Kobiton, the ability to execute Test Suites in parallel and more!

In this post, we take a look at 5 pub/sub examples that will help us understand how companies and organizations across all types of industries are leveraging this architectural design pattern to solve common engineering challenges and improve their architecture.

PHP has been one of the top (if not best) server-side scripting languages in the world for decades. However, let’s be honest – error logging in PHP is not the most straightforward or intuitive. It involves tweaking a few configuration options plus some playing around to get used to.

ISO 25010 helps you to ensure that your software is high quality. Read along or jump ahead to the section that interests you the most.

Testing in production simply means testing new code changes in production, with live traffic, in order to test the system’s reliability, resiliency, and stability. It helps teams solve bugs and other issues faster, as well as effectively analyze the performance of newly released changes. Its overall purpose is to expose problems that can’t be identified in non-production environments for reasons that may include not being able to mimic the concurrency, load, or user behavior.

As COVID-19 vaccinations continue to roll out, organizations across industries prepare to return employees to the workplace. It’s a journey fraught with anxieties, uncertainty, and unknowns. In a recent poll of Appian webinar participants, a mere 17% reported that their companies feel fully prepared to reopen facilities, and only 51% said they felt even “somewhat” prepared. The good news is that a safe return to the workplace is not uncharted territory.

MongoDB and MySQL are similar is some ways, but they also have some obvious differences. Perhaps the most obvious one is that MongoDB is a NoSQL database, while MySQL only responds to commands written in SQL. Potential users may want to examine MongoDB vs. MySQL in the areas of performance and speed. The following article will help you understand the differences, as well as the pros and cons of each database.

In this article, I will be focusing on the contribution that a multi-cloud strategy has towards these value drivers, and address a question that I regularly get from clients: Is there a quantifiable benefit to a multi-cloud deployment? That question is typically being asked when I explain the ability to leverage container technology that offers a consistent deployment environment across multiple clouds and form factors (public, private, or hybrid cloud).