Networking

This learning path on foundational Border Gateway Protocol (BGP) provides a comprehensive introduction and deep dive into the core aspects of BGP, the backbone of the internet's routing architecture. It starts by explaining the basics of BGP, including its purpose, operation, and fundamental concepts such as Autonomous Systems (AS), BGP sessions, and the BGP routing table. The series progresses to cover more advanced topics, such as BGP path selection, route advertisement, and the implementation of various BGP attributes like Local Preference, AS Path, and MED. Through practical examples, configurations, and troubleshooting scenarios, viewers gain a thorough understanding of how BGP facilitates global data exchange and the techniques network engineers use to optimize and secure BGP networks. The series aims to equip network professionals with the knowledge needed to manage and optimize BGP in real-world environments, emphasizing best practices and common pitfalls.

This Learning Path is designed to Discover and Experience Cisco (Viptela) SD-WAN. The lab environment that supports this Learning Path is virtual and dedicated to each individual consumer.

Previously, the Cisco day 2 operations suite of MSO, NAE, NIR, and NIA ran separately on computing as a .ova in vSphere or on the APIC as an application. The architecture never allowed for sharing data between the apps or correlations with errors and telemetry views of packet loss. With the roadmap moving, we had applications and a shared data lake for all applications to draw from and correlate between application errors, changes to the policy, and deep flow telemetry, all visual as an epoch. For all the applications to run and have sharable databases, Cisco NEXUS Dashboard (ND) was created. The ND platform allows all the Cisco Day 2 apps and third-party applications to run on a single appliance. Secondly, the ND has to be an expandable CPU and storage-intensive platform; today, the platform can scale with 3 master nodes and 4 worker nodes with the apps and their data residing on the ND cluster. As ND matures, more ND servers can join the cluster, and they can be separated regionally if within TTL requirements to distribute applications and provide DR strategies.

Cisco ACI is a policy-driven CLOS or Spine/Leaf based switching fabric utilizing layer 3 ECMP routing in the underlay and VXLAN encapsulation in the overlay to transport layer two and layer three traffic East/West across the fabric and North/South in and out of the fabric. ACI consists of the Application Policy Infrastructure Controller (APIC), a centralized controller that manages all aspects of the ACI fabric. The leaf switches are ToR switches that provide connectivity between servers and external networks, and the spine switches are Layer 3 switches that provide ECMP high-bandwidth connectivity between leaf switches. An ACI fabric can be expanded East/West by adding leafs, cabling to the spines, and registering them. ACI was designed to operate as "One Big Switch" (like a chassis-based NEXUS 7K) with the controllers acting like the Supervisors, the spines as fabric modules, and leafs acting as blades. We can decouple these elements from the chassis and place them anywhere in the data center by taking this approach. The leafs (blades) can be placed anywhere in the data center, so you are not limited to a chassis.

Before a core network can provide advanced services and traffic engineering, it must first establish basic transport connectivity between its nodes. In this course, you will learn how interior routing protocols are used to establish dynamic routing within the core, how MPLS technology is used to enhance packet transport across the underlay, and how Segment Routing is changing the way we think about transport paths. In each module you will watch a brief video describing the underlying technology and then walk through a hands-on lab to dive deeper into the relevant protocols and configurations that make underlay routing work.

Today, network engineers, especially in the data center space, must acquire AI/ML infrastructure skills and be able to discuss the required infrastructure upgrades and the reasoning for the upgrades with upper management. At WWT, we are committing $500 million to help our customers with AI/ML, and we have launched a new series of Learning Paths to help the reader navigate complex AI topics. By mastering these areas, data center network engineers can effectively contribute to successfully implementing and managing advanced AI and HPC infrastructure, aligning technological capabilities with business objectives while maintaining a robust and secure network environment.