Model-Driven DevOps: Increasing agility and security in your physical network through DevOps

di Steven Carter (Autore)

Jason King (Autore)

Mike Younkers (Autore)

Pearson Education (US), 2022

Develop Network Infrastructure More Rapidly, and Operate It More Effectively Using model-driven DevOps and the Infrastructure as Code (IaC) paradigm, teams can develop and operate network infrastructure more quickly, consistently, and securely--growing agility, getting to market sooner, and delivering more value. Now, two leading practitioners walk you step by step through successfully implementing model-driven DevOps for infrastructure. In this practical guide, they share lessons learned, help you avoid common pitfalls, and illuminate key differences between DevOps for infrastructure and conventional application-based DevOps. You'll learn why network infrastructure operations must change, what needs to change, and how to work together to change it. The authors guide you through creating consistent data models to manage massive numbers of network elements, organizing huge quantities of network data, and applying DevOps to infrastructure repeatably and consistently. Your journey includes a complete, hands-on reference implementation, detailed use cases, many examples based on open source tools, and sample code downloadable at GitHub. * Normalize and organize network infrastructure data consistently, to gain the same benefits from DevOps as cloud operators do * Replace legacy command lines with APIs, then leverage and scale them * Use configuration management, templates, and other tools to program infrastructure without coding * Safely implement Continuous Integration/Continuous Deployment for infrastructure Succeed with key human factors: break down silos, change culture, and address skills gaps Whether you're a network or cybersecurity engineer, architect, manager, or leader, this guide will help you suffuse all your network operations with greater efficiency, security, responsiveness, and resilience.

• Autore: Steven Carter, Jason King, Mike Younkers
• Editore: Pearson Education (US)
• Anno: 2022
• Rilegatura: Paperback / softback
• Pagine: 192 p.
• Dimensioni: 230 x 178 mm
• Peso: 340 gr.
• EAN: 9780137644674

Testo in English