Ian Lawson

Learn how to create and manage your virtual machines (VMs) using Red Hat

Over 80% of enterprises will have used generative AI (gen AI) APIs or deployed generative AI-enabled applications by 2026, according to Gartner. The barriers for joining these enterprises and integrating generative AI into the application development process are lower than ever. No need for extra funding or complex environments, just the know-how this video provides.

Dive into the end-to-end process of building and managing machine learning (ML)

Understand how to breakdown a monolith into Quarkus based microservices

Using API Management for applications during modernization

Rehosting, a cornerstone in the evolution of software development and deployment, has traditionally enabled the concurrent operation of multiple operating systems and applications on the same physical hardware. This approach, often employed through virtual machines (VMs), enhances efficiency, scalability, and resource utilization.

Data refactoring unlocks the potential for adaptable, resilient applications. Consider these techniques when migrating monolithic applications to microservices.

Developers frequently work with monolithic applications. However, the popularity of these monolithic applications has waned due to their lack of flexibility. Scaling a specific component requires scaling the entire application. Transitioning to a microservice architecture, with modular, independently scalable units addresses these challenges and is well-suited for cloud environments. This article focuses on moving a monolithic application, exemplified by a Java™-based e-commerce app called Pedal, to the cloud, offering guidance for this complex task.