In the article “From Data to Insights: An Introduction to Product Analytics”, we walk you through the basics of product analytics, providing you with a high-level approach to get started with it. This time, we’d like to dig in deeper to dissect every step of the product analytics process, assuming that the main goal is to improve user engagement and retention.

How many times have you heard the sentence that starts with “This software is compatible with Windows 8 and above” or “Only compatible with Android version 6.0 and above”? I am sure this would ring a bell for all gamers as games are highly sensitive to the platform they are run on. But for non-gamers too this would be the first thing they need to check if they know they are operating on an older version of the operating system.

Imagine you’re planning a road trip across the country. You’ve got your car, a map, and plenty of snacks for the journey. But there’s one crucial thing missing – a functional engine that will get you from point A to point B without any issues. That’s exactly why API functional testing is so important. APIs are the engines that power our software applications. They allow different systems to communicate with each other and transfer data seamlessly.

Today, all applications run on API. It connects one microservice to another, clients with servers, and runs the most basic yet essential application services. Clearly, a well-oiled API is imperative to ensure the smooth functioning of every system. If API breaks down, the complete user experience and application are put at risk. And only proper API testing can secure the system from such downtime possibilities.

In today’s data-driven world, businesses must deal with complex challenges related to managing, integrating, and properly using massive amounts of data housed in multiple locations. Organizations that unlock the right data architectural approach empower themselves with much better decision-making and strategic insights. Two popular approaches — data mesh and data fabric — have surfaced as prominent and innovative solutions for handling data at scale.

Flaky tests are one of the most common and frustrating issues in software testing. These are tests that pass or fail sporadically, even if the code being tested has not changed. This can cause confusion and wasted time for developers who are trying to fix issues that may not even exist.

Today we’re pleased to announce a new strategic partnership and resale agreement with Imperva. Imperva customers will now be able to directly license Kong Enterprise, the fastest, most feature-rich, and secure API management solution. In addition, Kong customers will be able to use the Imperva API Security plugin within Kong Enterprise. This allows developers to comprehensively secure their APIs and protect their business applications and data against unauthorized access.

Despite its many advantages, Node.js comes with a set of potential pitfalls if you don't maintain your application properly, such as: In this post, we'll explore these pitfalls and how to avoid them. Let's dive straight in!

There are many ways to load code and access file-related constants in Ruby. We can create a clear architecture by separating and handling concerns into classes and pulling in only the classes we depend on. Many full-stack frameworks like Rails and Hanami offer a built-in method to access the classes we want, as long as we stick with a certain convention. How does this work? In this post, we will explore three different options for loading code: using load, require, and autoload.

Gaetano DiNardi shares what many companies get wrong when they analyze website performance and traffic, and steps you can take to better know and serve your visitors.