We analyze the impact of continuous integration and deployment and how implementing the CI/CD methodology optimizes software development.
We analyze how to apply the fundamental principles of sustainable development in different programming languages. We also discuss the importance of sustainable development in the software industry and how to promote innovation.
We tell you which programming languages are the most sustainable and how they contribute to improving energy efficiency and reducing the carbon footprint.
In this article we analyze the challenges that organizations face when they need to train professionals in Mainframe and Cobol, and some effective solutions. In addition, we evaluate the IT talent industry landscape and how to overcome the challenges.
In this article we tell you what CICS is, how it works and what its benefits are. We also identify use cases and strategies to improve performance and increase mainframe availability.
In this article we break down the concept of disaster recovery: what it is, why it is important for the continuity of organizations, and what are the best strategies to develop a solid plan.
Do you know what IDz tools are, what their features are and how they allow you to modernize development within a mainframe? In this article we analyze these aspects of this IBM proposal and why to use it.
Modernizing legacy applications: impact, approaches and techniques; and how to choose the right path
We propose a change of approach: moving from a technical, tool-based perspective to a decision-making approach based on impact, trade-offs, and measurable results. We present criteria for evaluating applications, defining differentiated strategies, and building a progressive modernization roadmap aligned with business objectives.
In this article we analyze what the carbon footprint is, how it is generated, how it is measured and what measures can be taken to reduce the negative impact of the IT industry on the environment.
We analyze what the implementation of AIOps entails in organizations that must manage large data infrastructures and address the impact that AI and machine learning have on these processes.
