Modulbeschreibung

The students can:

• Recall the fundamental terminology of Intent-Based Networking (IBN).
• Explain the core concepts of IBN.
• Analyze use cases and requirements to determine the applicability of learned IBN principles and related concepts.
• Apply learned principles to design and develop suitable IBN-based solutions for given network scenarios.
• Implement practical solutions for modern networking challenges by utilizing learned techniques.
• Evaluate the effectiveness and suitability of different concepts and the underlying learned networking techniques for specific network requirements and workloads.

Required:

• Linux
• Networking (especially BGP, MPLS)
• Programming principles

Helpful:

• Go
• Network automation concepts

Präsentation der wissenschaftlichen Publikationen

35 % Semesternote

65 % schriftliche Prüfung

This module offers a comprehensive and highly applied exploration of techniques essential for building Intent-Based Networking (IBN). Intent-based networking (IBN) fundamentally changes network management. Instead of manually specifying how to configure devices, the focus shifts to defining what the network should achieve. The IBN system automatically fulfills these goals and adapts constantly to meet those goals. This concept is a crucial paradigm for the next generation of engineers as it represents the future of networking, offering simpler management, greater agility, and the power to build intelligent, self-optimizing automated networks.

Beyond theoretical foundations, the curriculum delves into the practical application of established and emerging technologies. Key areas of focus include:

• Network Monitoring and Observability: Examination of various approaches and protocols for gaining deep insights into network behavior.
• Network Programmability: Exploration of programmable networks and data plane programming techniques for dynamic network control.
• Modern Systems Building: Practical aspects of collecting, processing, and making network data readily available for intelligent automation.
• Network Optimization: Strategies and techniques for tailoring network performance to specific use case requirements.

The learning experience provides hands-on experience with these technologies and includes labs with different network operating systems and components. Furthermore, a hands-on project will allow students to apply their knowledge and skills in a real-world scenario, with the project outcome contributing to the final grade.