Systems | Development | Analytics | API | Testing

When choosing to build or buy, consider whether the following challenges are worth the squeeze.

Salesforce is one of the most popular CRM applications globally, used by thousands organizations across all industries and segments. It enables organizations to manage their customer and revenue focused business processes, functions, and data in a central location, thereby improving planning, customer satisfaction, and overall business performance.

Integration Testing (or I&T: Integration & Testing) is a type of software testing in which various units, modules, and components of the software are integrated and tested as a cohesive unit. With Integration Testing, testers want to find defects that surface due to code conflicts between software components when they work together. This level of testing is higher than unit testing, which only validates if software components function well as a single unit.

Katalon’s January release adds Robot Framework integration with Katalon’s AI-enabled Visual Testing. We have also updated our API documentation for those teams needing to create their own custom integrations to the Katalon Platform via API’s.

Brain Reed from NowSecure explains the core ideas of the Mobile DevSecOps Framework: Learn how to quickly release high-quality mobile apps while simultaneously building in the necessary security and privacy.

As a senior Flutter developer, a big part of my daily job consists of reviewing code, mentoring other developers, and helping them with their problems. One mistake that I noticed developers repeating on many occasions is misusing BuildContext. I analyzed why this happens and came to the conclusion that it is because of an incomplete understanding of what BuildContext is, how it works, and its scope and lifecycle.

Testing Kubernetes Ingress resources can be tricky, and can lead to frustration when bugs pop up in production that weren’t caught during testing. This can happen for a variety of reasons, but with Ingress specifically, it often has to do with a misalignment between the data used in testing and the traffic generated in production. Tools like Postman can be a great way of generating traffic, but they have the drawback of being manually created.

It’s remarkable how many systems can manage unexpected performance demand, scaling resources and continuing operations. Yet truly unexpected demand can still apply enough stress to a system that it crashes. Here, we’re going to examine two failures that resulted from a single corporate controversy.

As every data engineer and analyst can attest, generating reports is one of the most time-consuming and human error prone activities in the day-to-day life of data analysts. Luckily, with the development of technology, data reporting can now be done automatically, which saves you time and reduces mistakes. In this article, you will learn.

Data quality is fairly simple nomenclature to describe the state of the data being processed, analyzed, fed into AI, and more. But this modest little term belies an incredibly critical and complicated reality: that enterprises require the highest level of data quality possible in order to do everything from developing product and business strategies, and engaging with customers, to predicting the weather and finding the fastest delivery routes.