Brenda Surra

In the world of software development, the architecture of an application can determine its long-term success or failure. One of today’s most relevant debates is between microservices and monoliths—two architectural approaches, each with advantages and disadvantages depending on the type of company and its specific needs. While monoliths have been the standard for decades, microservices […]

The manufacturing industry is undergoing an unprecedented transformation thanks to artificial intelligence (AI). Technologies such as automation and predictive maintenance are revolutionizing production, optimizing machine performance, and reducing operational costs. Companies that implement AI can improve their efficiency, minimize errors, and increase their competitiveness in an increasingly demanding global market. In this article, we’ll explore

Biometric authentication has become a key tool for enhancing security across various digital and physical platforms. By leveraging unique individual characteristics, such as fingerprints or facial recognition, this technology enables faster and more reliable identification compared to traditional methods. In this article, we will discuss how it works, its advantages and disadvantages, and some examples

Cross-platform mobile app development has gained enormous popularity in recent years, allowing developers to create efficient apps without the need to write separate code for iOS and Android. Two of the most prominent technologies in this field are React Native and Flutter. In this article, we will compare React Native and Flutter, analyzing their differences,

The software development process involves different environments that enable the efficient building, testing, and deployment of applications. The three main environments are development, staging, and production, each serving a specific purpose to ensure software quality and stability before its final release. In this article, we will explore the differences between these environments, their importance in

AI adoption is revolutionizing the business landscape, optimizing operations, and enabling more efficient decision-making. However, transitioning to this technology can present significant challenges. In this article, we discuss the main barriers and effective strategies to overcome them and achieve successful AI adoption. 1. Knowledge gap and technical skills Many companies struggle to integrate AI due

Software development is full of critical decisions, and one of the most common is whether to use a framework or not. These tools are powerful and can speed up the development process while improving the final product’s quality. However, they also have limitations that may affect certain types of projects. In this article, we will

Agile frameworks have revolutionized the way teams approach their work. These methodologies allow teams to adapt to rapid changes, collaborate effectively, and deliver value continuously. Among the most popular frameworks are Kanban, Scrum, and Extreme Programming (XP). Although they all share the agile philosophy, each has unique characteristics that make it ideal for different contexts

A significant part of a project’s success depends on its ability to be deployed efficiently in production. The process known as deployment is not just a final phase of development but an ongoing practice that ensures applications reach users quickly, securely, and reliably. In this article, we’ll explore what deployment is, the essential elements for

The rise of AI and machine learning has brought an increasing dependence on data. However, not all data is useful in its raw form. This is where the ETL process in machine learning comes into play a key methodology that transforms raw and unstructured data into information ready for analysis and predictive model development. In