Enterprises are investing in data mesh initiatives to accelerate how decisions are made and to create novel experiences based on machine learning models. Similarly, enterprises are investing in API platform initiatives to productize business domains (or bounded contexts in domain-driven design parlance) as self-service digital assets that accelerate innovation and improve business agility. Both initiatives are typically run as separate work streams.

You're overseeing your delivery logistics from your dashboard when an alarming notification surfaces - one of your drivers has had a minor accident and they're unable to finish their route. You start considering your options. Is there a replacement driver close by? Is there a spare vehicle available for the original driver? Just as you're figuring things out, another alert arrives: your driver is okay and the delivery is still on time.

In our last post, we examined the most common ways to organize business logic in Ruby on Rails. They all have advantages and drawbacks, and essentially, most do not leverage the full power of Object Oriented Programming in Ruby. This time, we will introduce another alternative that more naturally fits the mental models we apply when reasoning about the behavior of our applications: DCI.

Dart and Flutter are a powerful duo when building software applications, ranging from mobile apps - Android and iOS; to desktop apps - Linux, Windows, and macOS. Flutter is sufficient to handle most application features. However, some apps involve deeper integration with their platform components. Flutter boasts of smooth and easy-to-setup mechanisms for communication between Flutter and platform hosts.

Puppeteer is a powerful browser automation library for web scraping and integration testing. However, the asynchronous, real-time API leaves plenty of room for gotchas and antipatterns to arise. This article is part of a series, starting with Avoiding Puppeteer Antipatterns and Puppeteer in Node.js: Common Mistakes to Avoid. In this post, we'll add another dozen antipatterns to the list. There will be no overlap with previous installments, so you may wish to start with those.

Do you know that log files in Linux can quickly consume disk space if not managed properly? This can lead to performance issues and even system crashes. Log files? What exactly are they, and why should they matter to anyone using Linux-based systems? Log files are essential components of any Linux-based system. They are text files that contain information about system events, including errors, warnings, and other important messages.

Exploratory Testing is an unscripted, manual software testing type where testers examine the system with no pre-established test cases and no previous exposure to the system. Instead of following a strict test plan, they jump straight to testing and make spontaneous decisions about what to test on the fly.

BDD testing is an Agile approach to software testing where testers write test cases in simple language that even people without technical expertise can understand. The goal of BDD testing is to increase collaboration between the technical side and the business side. The Gherkin language is a unique business-readable language used to describe system behaviors and scenarios. It is structured by 3 primary statements: Given - When - Then, with each statement describing a specific aspect of the system.

Amazon's Relational Database Service (AWS RDS) is a web-based service launched by Amazon Web Services (AWS) that unifies the setup, operation, and scaling of relational databases in the cloud. By using a dependable and feature-rich ETL (Extract, Transform, Load) tool, you can simplify the process of retrieving, transforming, and sending data from the various systems you already use, like AWS RDS.

Choosing one over the other can come down to a few key differences. Let’s take a look at both to help you make an informed decision.