EVPN Designs: VXLAN Leaf-and-Spine Fabric

In this series of blog posts, we’ll explore numerous routing protocol designs that can be used to implement EVPN-with-VXLAN L2VPNs in a leaf-and-spine data center fabric. Every design will come with a companion netlab topology you can use to create a lab and explore the behavior of leaf- and spine switches.

Our leaf-and-spine fabric will have four leaves and two spines (but feel free to adjust the lab topology fabric parameters to build larger fabrics). The fabric will provide layer-2 connectivity to orange and blue VLANs. Two hosts will be connected to each VLAN to check end-to-end connectivity.

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1000BASE-T Part 3 – Autonegotiation

In this post, we’ll take a closer look at auto negotiation. Auto negotiation has the following characteristics:

  • It is required to be supported.
  • Transmits capabilities for speed/duplex.
  • Negotiates Energy Efficient Ethernet (EEE) capabilities.
  • Determines the leader/follower relationship on the link.
  • Needed for PHY Control, a PMA subfunction.
  • Performed when initializing the link.
  • Auto-MDIX.

The Auto Negotiation transmitter and receiver is actually a separate system in its own right.  In multi-speed PHY devices, auto negotiation is used to select the highest speed that both sides of the link are capable of, before the link is trained.  However, it is important to understand that auto negotiation is not optional to be supported, but the standard does not require it to be implemented (thanks to Eric Peterson for clarifying this). A leader and follower must be decided so that clock synchronization can take place. Without auto negotiation, this would have to be manually configured. On some devices it is possible to configure speed on 1000BASE-T interface. However, this does normally not disable auto negotation, but rather limit what capabilities get advertised.

Auto negotiation is performed using Fast Link Pulses (FLP). Historically, 10BASE-T used Link Test Pulse (LTP) to verify the integrity Continue reading

Continuing our work with CISA and the Joint Cyber Defense Collaborative to keep vulnerable communities secure online

Internet security and reliability has become deeply personal. This holds true for many of us, but especially those who work with vulnerable communities, political dissidents, journalists in authoritarian nations, or human rights advocates. The threats they face, both in the physical world and online, are steadily increasing.

At Cloudflare, our mission is to help build a better Internet. With many of our Impact projects, which protect a range of vulnerable voices from civil society, journalists, state and local governments that run elections, political campaigns, political parties, community networks, and more, we’ve learned how to keep these important groups secure online. But, we can’t do it alone. Collaboration and sharing of best practices with multiple stakeholders to get the right tools into the groups that need them is essential in democratizing access to powerful security tools.

Civil society has historically been the voice for sharing information about attacks that target vulnerable communities, both online and offline. In the last few years, we see governments increasingly appreciating how cyberattacks affect vulnerable voices and make an effort to identify the risks to these communities, and the resources available to protect them.

In March 2023, the US government launched the Summit for Democracy Continue reading

Leveling up Workers AI: general availability and more new capabilities

This post is also available in 简体中文, 繁體中文, 日本語, 한국어, Deutsch, Français and Español.

Welcome to Tuesday – our AI day of Developer Week 2024! In this blog post, we’re excited to share an overview of our new AI announcements and vision, including news about Workers AI officially going GA with improved pricing, a GPU hardware momentum update, an expansion of our Hugging Face partnership, Bring Your Own LoRA fine-tuned inference, Python support in Workers, more providers in AI Gateway, and Vectorize metadata filtering.

Workers AI GA

Today, we’re excited to announce that our Workers AI inference platform is now Generally Available. After months of being in open beta, we’ve improved our service with greater reliability and performance, unveiled pricing, and added many more models to our catalog.

Improved performance & reliability

With Workers AI, our goal is to make AI inference as reliable and easy to use as the rest of Cloudflare’s network. Under the hood, we’ve upgraded the load balancing that is built into Workers AI. Requests can now be routed to more GPUs in more cities, and each city is aware of the total available capacity for AI inference. If the request Continue reading

Running fine-tuned models on Workers AI with LoRAs

This post is also available in 简体中文, 繁體中文, 日本語, 한국어, Deutsch, Français and Español.

Inference from fine-tuned LLMs with LoRAs is now in open beta

Today, we’re excited to announce that you can now run fine-tuned inference with LoRAs on Workers AI. This feature is in open beta and available for pre-trained LoRA adapters to be used with Mistral, Gemma, or Llama 2, with some limitations. Take a look at our product announcements blog post to get a high-level overview of our Bring Your Own (BYO) LoRAs feature.

In this post, we’ll do a deep dive into what fine-tuning and LoRAs are, show you how to use it on our Workers AI platform, and then delve into the technical details of how we implemented it on our platform.

What is fine-tuning?

Fine-tuning is a general term for modifying an AI model by continuing to train it with additional data. The goal of fine-tuning is to increase the probability that a generation is similar to your dataset. Training a model from scratch is not practical for many use cases given how expensive and time consuming they can be to train. By fine-tuning an existing pre-trained model, Continue reading

Using wemulate with netlab

An RSS hiccup brought an old blog post from Urs Baumann into my RSS reader. I’m always telling networking engineers that it’s essential to set up realistic WAN environments when testing distributed software, and wemulate (a nice tc front-end) seemed like a perfect match. Even better, it runs in a container – an ideal component for a netlab-generated virtual WAN network.

wemulate acts as a bump in the wire; it uses Linux bridges to connect two container interfaces. We’ll use it to introduce jitter into an IP subnet:

┌──┐   ┌────────┐   ┌──┐
│h1├───┤wemulate├───┤h2│
└──┘   └────────┘   └──┘                       
◄──────────────────────►
     192.168.33.0/24
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Using wemulate with netlab

An RSS hiccup brought an old blog post from Urs Baumann into my RSS reader. I’m always telling networking engineers that it’s essential to set up realistic WAN environments when testing distributed software, and wemulate (a nice tc front-end) seemed like a perfect match. Even better, it runs in a container – an ideal component for a netlab-generated virtual WAN network.

wemulate acts as a bump in the wire; it uses Linux bridges to connect two container interfaces. We’ll use it to introduce jitter into an IP subnet:

┌──┐   ┌────────┐   ┌──┐
│h1├───┤wemulate├───┤h2│
└──┘   └────────┘   └──┘                       
◄──────────────────────►
     192.168.33.0/24
Read more …

1000BASE-T Part 2 – Deepdive

In 1000BASE-T Part 1, we reviewed the layers and what their purpose is. Now we’re going to go much deeper into the layers that relate to the PHY, which is PCS, PMA, and Autonegotiation. First though, let’s review the objectives of 1000BASE-T:

  • Support the CSMA/CD MAC.
  • Comply with specifications for GMII (Clause 35).
  • Support 1000 Mbit/s repeater (Clause 41).
  • Provide line transmission support full and half duplex operation.
  • Meet or exceed FCC Class A/CISPR or better operation.
  • Support operation over 100 meters of copper balanced cabling (defined in 40.7).
  • Bit Error Ratio less than or equal to 10^-10.
  • Support Auto negotiation (Clause 28).

How does 1000BASE-T achieve a bandwidth of 1000 Mbit/s? As you probably know, the twisted pair cable consists of four pairs, eight wires in total, where transmit and receive are separated to achieve full duplex operation:

The meaning of hybrid in this context is that transmit and receive is performed on the same pair. Every pair is capable of 250 Mbit/s data rate, for a total of 1000 Mbit/s. As PAM-5 encoding is used (more on this later), the baud rate is 125 MHz. This means that the PHY receives 8-bit words to send every Continue reading

Tech Bytes: Simplifying Network Deployment & Operations With Nile (Sponsored)

Today Austin Hawthorne from Nile joins us to dig into the company’s Network as a Service (NaaS) approach and how it differentiates from traditional networking solutions. Nile aims to streamline network deployment and operations by providing a complete network service: It performs the site survey, provides the switches and access points, brings the gear on... Read more »

NB472: HPE Adds GenAI to Aruba Central; Intel Eager to Slurp Billions in Subsidies

Take a Network Break! This week we try to peel back the layers on HPE’s announcement about new GenAI capabilties in Aruba Networking Central, parse Broadcom’s touting of its AI credentials, and feel conflicted about Intel sucking up billions in taxpayer dollars. South Korean chipmaker SK Hynix dangles a $4 billion investment promise to the... Read more »

Nornir Network Automation

Nornir Network Automation

Nornir is a Python library designed for Network Automation tasks. It enables Network Engineers to use Python to manage and automate their network devices. Unlike tools like Ansible which rely on domain-specific languages, Nornir leverages the full power of Python, giving you more flexibility and control over your automation scripts.

Nornir feels like what you'd get if Ansible and Python had a baby. If you're used to Ansible, you know that you first set up your inventory, write tasks, and execute them on all or selected devices concurrently. Nornir operates similarly, but the big difference is you use Python code instead of any Domain Specific Language.

My Life Without Nornir

Before I discovered Nornir, my approach to Python automation involved manually setting up a list of devices, specifying each one's vendor, and credentials. This setup could be a simple Python list or a dictionary. Then, I'd loop through each device with a for loop, using libraries like Netmiko or Napalm to execute tasks. These tasks ranged from getting data from the devices to sending configurations. Here is a very simple snippet of managing the devices and using them with Netmiko. This method can get complicated very easily once you start Continue reading

Repost: EBGP-Mostly Service Provider Network

Daryll Swer left a long comment describing how he designed a Service Provider network running in numerous private autonomous systems. While I might not agree with everything he wrote, it’s an interesting idea and conceptually pretty similar to what we did 25 years ago (IBGP without IGP, running across physical interfaces, with every router being a route-reflector client of every other router), or how some very large networks were using BGP confederations.

Just remember (as someone from Cisco TAC told me in those days) that “you might be the only one in the world doing it and might hit bugs no one has seen before.”

Read more …

Repost: EBGP-Mostly Service Provider Network

Daryll Swer left a long comment describing how he designed a Service Provider network running in numerous private autonomous systems. While I might not agree with everything he wrote, it’s an interesting idea and conceptually pretty similar to what we did 25 years ago (IBGP without IGP, running across physical interfaces, with every router being a route-reflector client of every other router), or how some very large networks were using BGP confederations.

Just remember (as someone from Cisco TAC told me in those days) that “you might be the only one in the world doing it and might hit bugs no one has seen before.”

Read more …

HN727: Kubernetes Networking Essentials

Where there are containers, there is networking. Today we dig into the networking that underlies Kubernetes, the open source orchestration platform for container-based applications. Our guest Karim El Jamali takes us through the essential concepts: Nodes, pods, clusters, CNIs, virtual ethernet pairs, ingress controller, eBPF, and service meshes. As container-based applications grow in popularity, it’s... Read more »

Copilot Not Autopilot

I’ve noticed a trend recently with a lot of AI-related features being added to software. They’re being branded as “copilot” solutions. Yes, Microsoft Copilot was the first to use the name and the rest are just trying to jump in on the brand recognition, much like using “GPT” last year. The word “copilot” is so generic that it’s unlikely to be to be trademarked without adding more, like the company name or some other unique term. That made me wonder if the goal of using that term was simply to cash in on brand recognition or if there was more to it.

No Hands

Did you know that an airplane can land entirely unassisted? It’s true. It’s a feature commonly called Auto Land and it does exactly what it says. It uses the airports Instrument Landing System (ILS) to land automatically. Pilots rarely use it because of a variety of factors, including the need for minute last-minute adjustments during a very stressful part of the flight as well as the equipment requirements, such as a fairly modern ILS system. That doesn’t even mention that use of Auto Land snarls airport traffic because of the need to hold other planes outside Continue reading

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