• Align security strategies with organizational goals • Implement AI-assisted Continuous Security across teams • Select and integrate AI-powered tools for vulnerability detection, automated compliance checks, and real-time incident response • Transition from reactive to proactive security to continuously adapt to emerging threats • Apply best practices to mitigate risks and avoid breaches

324 pages. Guiding principles and pillars that underpin continuous testing, quality, security, and feedback. Knowledge to integrate testing into every stage of the software development life cycle, adopt a proactive approach to quality and security, and foster a culture of continuous feedback and improvement. Practical insights and strategies for overcoming common challenges and leveraging best practices to achieve high-quality, secure, and user-centric software products.

Artificial intelligence is neither a savior nor a threat by nature. It reflects the values, structures, and intentions of the systems that deploy it. When respect and trust are absent, AI accelerates despair, disconnection, and inequity. When they are deliberately engineered, AI becomes a force for clarity, dignity, and shared progress. The difference is not technical. It is human.

SDSE challenges that paradigm. Rather than treating testing as a downstream activity, SDSE moves behavioral validation to the forefront. It emphasizes modeling, simulating, and validating system behavior before implementation begins. This is not simply an incremental improvement to existing practices. It represents a structural change in how engineers think about correctness, risk, and system design. What makes this approach particularly relevant today is the scale and speed at which modern systems operate. Distributed architecture, asynchronous interactions, and dynamic runtime conditions make it increasingly difficult to reason about system behavior using traditional methods alone. At the same time, AI, particularly the rise of agentic systems that can observe, decide, and act autonomously—is accelerating development and operational cycles at an unprecedented pace.

A practical guide to mastering DevOps through strategy, discipline, and continuous improvement. Written by award-winning engineer Marc Hornbeek.

The principles of Avalon respect, courage, compassion, integrity, and the pursuit of wisdom: lead us toward a more meaningful, harmonious, and noble life. They help us align with our highest selves, strengthen our relationships, and contribute to a more just and beautiful world. Living by these principles creates inner peace, fosters trust, and invites others to rise with us.

“The Avalonian Way representa un rico tapiz tejido a partir de varios hilos religiosos y filosóficos, enfatizando temas de continuidad, curación e interconexión. Este sincretismo refleja el deseo de una comprensión holística de la existencia que trascienda los límites tradicionales, invitando a una visión más inclusiva y compasiva de la vida, la muerte y el viaje del alma”.

This document is an introduction to intelligent, adaptive systems   from generative foundations to swarms of autonomous agents

In the book Engineering DevOps by Marc Hornbeek, DevOps is organized in Nine Pillars.  These are permanent structural parts of DevOps engineering, no matter where you are trying to do DevOps. The Nine Pillars of DevOps provides a comprehensive framework to describe DevOps and DevSecOps practices, focusing on leadership, culture, design, integration, testing, delivery, monitoring, security, and infrastructure.

Las estructuras de Arco y Fundación cruzan los Nueve Pilares horizontalmente porque son relevantes para unir todos los pilares. Las estructuras de Fundación son “Orquestación y Automatización” y “Gobernanza” porque todos los pilares dependen de ellas. Los Arcos son “Entrega Continua CI/CD Pipeline”, “Automatización de Liberación de Aplicaciones” y “Gestión de la Cadena de Valor” que hacen uso de las prácticas de los Nueve Pilares.

28 pages. This book is a starter guide, introducing this concept and equip you with the knowledge of AI Based Automated testing. In the next chapter, you will take a deep dive into the types of testing, their disadvantages and how they pave the way for innovation using AI. Once the need is established, the book will delve deep into the processes, techniques, challenges, best practices and strategies associated with AI Based Testing. At the end, the reader will have a good understanding of the concept and will be equipped to start their own journey into the world of AI Based Testing.