In its most rudimentary terms, a digital twin in the realm of networking is the concept of emulating or simulating a like-for-like topology of a production...
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netlab release 1.7.0 added the fabric plugin that simplifies building lab topologies with leaf-and-spine fabrics. All you have to do to build a full-blown leaf-and-spine fabric is:
For example, the following lab topology builds a fabric with Arista cEOS containers having two spines and four leaves:
During the load balancer deployment process, we define a virtual IP (a.k.a front-end IP) for our published service. As a next step, we create a backend (BE) pool to which we attach Virtual Machines using either their associated vNIC or Direct IP (DIP). Then, we bind the VIP to BE using an Inbound rule. Besides, in this phase, we create and associate health probes with inbound rules for monitoring VM's service availability. If VMs in the backend pool also initiate outbound connections, we build an outbound policy, which states the source Network Address Translation (SNAT) rule (DIP, src port > VIP, src port).
This chapter provides an overview of the components of the Azure load balancer service: Centralized SDN Controller, Virtual Load balancer pools, and Host Agents. In this chapter, we discuss control plane and data plane operation.
Figure 20-1 depicts our example diagram. The top-most box, Loadbalancer deployment, shows our LB settings. We intend to forward HTTP traffic from the Internet to VIP 1.2.3.4 to either DIP 10.0.0.4 (vm-beetle) or DIP 10.0.0.5 (vm-bailey). The health probe associated with Continue reading
In a previous post, I discussed how Maximum Flow problems can be used for network optimization. We focused on a scenario where demands were already routed in the network, and our objective was to determine the maximum demand that could be handled between a given source and a destination metro. We solved this problem by calculating the residual bandwidth for the graph, creating fake demand nodes for each metro with high-capacity edges to avoid them being bottlenecks, and applying Dinic’s algorithm between the source and the destination metro. This is also called a Single Commodity Flow Problem.
We then extended the problem to consider two metros sending traffic to the same destination sink and used the Network Simplex algorithm to determine the maximum traffic the network could accommodate. This is also known as a Multi Commodity Flow Problem. Finally, we validated our findings by routing the results through a network model.
In this post, we will discuss another constraint-based problem called Minimum Maximum Link Utilization (MMLU). The primary goal of MMLU is to route traffic demands in a network to minimize the maximum link utilization. In other words, we aim to distribute the traffic evenly across the network links to Continue reading
Every time someone tries to persuade you to buy (expensive) big-buffer data center switches, take an antidote: the Things we (finally) know about network queues article by Avery Pennarun.
All Routing Protocol Convergence videos from the How Networks Really Work webinar are now public. Enjoy!
At the start of the year a very interesting (and some would say inevitable) event happened involving internet routing security, the first case study of a large-scale victim o
Most providers will only accept a /24 or shorter IPv4 route because routers have always had limited amounts of forwarding table space. In fact, many hardware and software IPv4 forwarding implementations are optimized for a /24 or shorter prefix length. Justin Wilson joins Tom Ammon and Russ White to discuss why the DFZ might need to be expanded to longer prefix lengths, and the tradeoffs involved in doing so.
Last time, we discussed the first line of defense against fat finger incidents: limiting the number of BGP prefixes your router accepts from a BGP neighbor. However, you can do much more without deploying customer-specific filters (which might require a customer database) or ROV/RPKI.
You can practice the default filters you should always deploy on EBGP sessions with your customers in the Stop the Propagation of Configuration Errors lab exercise.