Category: Tags

The netlab tool will help you be more proficient once you decide to drop GUI-based network simulators and build your labs using CLI and infrastructure-as-code principles.

You can also use netlab (potentially together with GitHub Codespaces) to build online, easy-to-consume, hands-on training solutions. I used that approach to build the BGP labs.

I firmly believe that you cannot be a good networking engineer¹ without a firm grasp of the networking fundamentals, and I couldn’t resist pointing that out a few times (see also certifications-related posts):

• You Must Understand the Fundamentals to Be Successful
• Learning Networking Fundamentals at University?
• Grasp the Fundamentals before Spreading Opinions
• Appreciating the Networking Fundamentals
• When You Find Yourself on Mount Stupid

Regardless of how far down this page you’ll get, these blog posts are a must-read:

• Management, Control, and Data Planes in Network Devices and Systems
• Relationships between Layer-2 (VLAN) and Layer-3 (Subnet) Segments
• On the Usability of OSI Layered Networking Model

I would also suggest exploring these series of blog posts as well as textbooks and other resources I collected:

• Interfaces and Ports
• Packet Forwarding Basics
• Integrated Routing and Bridging (IRB) Designs
• IP Anycast and Anycast Gateways
• Site and Host Multihoming
• High Availability Switching
• Fast Failover
• Unnumbered IPv4 Interfaces
• CLI versus API
• Network State Consistency

The rest of the fundamentals-related blog posts are collected on this page.

Network Addressing

Addresses and routes are the basic concepts anyone dealing with a network must (eventually) grasp. These blog posts describe how we got a hierarchy of addresses:

• Names, Addresses, and Routes
• Addresses in a Networking Stack
• Why Do We Need Source IP Addresses in IP Headers?
• Early Data-Link Layer Addressing
• Fibre Channel Addressing
• LAN Data Link Layer Addressing
• Can We Skip the Network Layer?
• Network Layer: Interface or Node Addresses

Deep Dives

These blog posts dive deeper into interesting topics:

• Why Is OSPF not Using TCP?
• Chasing CRC Errors in a Data Center Fabric
• IBGP, IGP Metrics, and Administrative Distances
• Is Switching Latency Relevant?
• Response: Is Switching Latency Relevant?
• Routing Protocols: Use the Best Tool for the Job
• From Bits to Application Data
• On Routing Protocol Metrics
• OSI Layers in Routing Protocols

If you like them, it’s probably time you start exploring the deep-dive series I already mentioned.

A Bit of a History

These blog posts might help you figure out some less obvious details or give you a historical perspective on why networking technologies evolved to where we are right now:

• TCP/IP Lacks a Session Layer
• The Awful Socket API
• How Did We End With 1500-Byte MTU?

If you want to dive deeper into historical technologies, you might enjoy the comparison of TCP/IP and OSI (CLNP) protocol stacks:

• Finding Adjacent Nodes
• Reaching Off-Subnet Nodes
• Network State Summarization

There Be Rants

Long-time readers know I can’t resist a good rant:

• Lies, damned lies and product marketing
• Bridges: a Kludge that Shouldn't Exist
• How Did We Ever Get Into This Switching Mess?
• Response: The OSI Model Is a Lie
• The World in Which IPv6 Was a Good Design
• IPv4, IPv6, and a Sudden Change in Attitude
• Was IPv6 Really the Worst Decision Ever?

Everything Is a Graph

You can represent every network as a graph of network devices (nodes) and links². Rachel Traylor covered the graph theory in the (free) Network Connectivity, Graph Theory, and Reliable Network Design and Graph Algorithms in Networks webinars; these blog posts might provide some extra details:

• OMG, It's Graphs Everywhere
• Everything Is a Graph
• Real-Life Network-as-a-Graph Examples

Networking Fundamentals Videos

Finally, I published dozens of videos describing the networking concepts as part of the How Networks Really Work webinar that got at least some minor positive feedback. The videos describe:

Business aspects of networking technologies

Some people liked the non-technical take on networking I recorded in 2019 and 2020:

• Define the Problem Before Searching for a Solution
• Know Your Users' Needs
• Should You Build or Buy a Solution?
• High-Level Technology Guidelines

Fallacies of distributed computing

• Fallacies of Distributed Computing
• The Network Is Not Reliable
• End-to-End Latency Is Not Zero
• Bandwidth Is Neither Infinite Nor Cheap
• Networks Are (Not) Secure
• Internet Has More than One Administrator
• Networks Are Not Homogenous

Networking challenges and the importance of a layered approach

• Overview of Networking Challenges
• Introducing Transmission Technologies
• Beyond Two Nodes
• The Need for Network Layers
• Retransmissions and Flow Control in Computer Networks
• Putting the Networking Layers Together
• Breaking the End-to-End Principle

Network Addressing

• Introduction to Network Addressing
• Theoretical View of Network Addressing
• Early Data-Link-Layer Addressing
• Local Area Network Addressing
• Network Layer Addressing
• Comparing TCP/IP and CLNP
• Combining Data-Link- and Network Layer Addresses
• Network Address Assignments
• Network Address Scopes
• The Basics of Network Address Translation (NAT)

Switching, Routing, and Bridging

• Review Questions: Switching, Bridging and Routing
• What Are Bridging, Routing, and Switching?
• Getting a Packet Across a Network
• Multi-Layer Switching and Tunneling
• Finding Paths Across the Network
• Path Discovery in Transparent Bridging and Routing
• Transparent Bridging Fundamentals
• IP Routing Fundamentals
• Comparing Routing and Bridging
• Typical Large-Scale Bridging Use Cases

Routing Protocols

• Routing Protocols Overview
• Link State Routing Protocol Basics
• Link State Routing Protocol Implementations

Lessons Learned from 35 Years of Networking

• Technology Still Matters
• Fundamentals Haven't Changed
• Complexity Will Kill Your System
• Some Services Are Not Worth Delivering
• The Way Forward

Artificial Intelligence (AI) and Machine Learning (ML) are the next big hype in networking following Software-Defined Everything and Intent-Based Everything. Like with the previous hype bubbles it’s worth figuring out

• How much of the hype is real (TL&DR: not much)?
• Whether the technology is ready to be used in production networks (TL&DR: some of it)
• How you could use the technology to make your life easier

How Real Is It?

Like with the previous hype tsunamis I’ll do my best to help you figure out the answers to the above questions with a hefty dose of skepticism and snark¹, starting with:

• Will ChatGPT Replace Stack Overflow?
• Is ChatGPT an Efficiency Multiplier?

I also decided to “kick the tires” and document my (often less-than-stellar) experience with the most-overhyped products:

• Real-Life Not-Exactly-Networking AI Use Case
• ChatGPT on BGP Routing Security
• Kicking the Tires of GitHub Copilot
• Building a Small Network with ChatGPT
• ChatGPT Explaining the Need for iSCSI CRC
• Source IP Address in Multicast Packets

AI/ML in Networking: The Good, the Bad and the Ugly

Javier Antich created a wonderful AI/ML in Networking in 2021. If you know nothing about AI/ML and wonder whether you should care about it, you MUST watch these videos from his webinar:

• Introduction to AI/ML Hype
• Machine Learning 101
• Machine Learning Techniques
• Use Cases for AI/ML in Networking
• The Long Tail of AI/ML Problems
• Ugly Challenges of Using AI/ML in Networking
• Language Models in AI/ML Landscape
• Language Model Basics

In 2023, Javier published a book covering the same set of topics in way more details. I would highly recommend you read it if you want to know more.

What Others Are Saying

I keep collecting interesting articles talking about AI in general and (lately) ChatGPT. I found these interesting enough to mention them in worth reading blog posts:

• MUST READ: ChatGPT Is Bullshit (2024)
• Machine Learning Explained (2020)
• AI Makes Animists of Us All (2022)
• The AI Illusion (2022)
• Collections: On ChatGPT (a Historian Perspective) (2023)
• Putting Large Language Models in Context (2023)
• The Dangers of Knowing Everything (2023)
• Building Trustworthy AI (2023)
• Cargo Cult AI (2023)
• Building Stuff with Large Language Models Is Hard (2023)
• Worth Reading: AI Does Not Help Programmers (2023)
• Eyes that glaze over. Eyes like saucers. Eyes that narrow. (2023)
• Networking for AI Workloads (2023)
• Looking Inside Large Language Models (2023)
• Where Are the Self-Driving Cars? (2023)
• AI Risks (2023)
• State-of-the-Art AI (2023)
• The AI Supply Paradox (2023)
• ChatGPT Does Not Summarize (2024)
• You Probably Don't Need AI (2024)
• GitHub Copilot Workspace Review (2024)
• AI Is Still a Delusion (2024)
• AI and Google’s Quarterly Results (2024)
• Hard Truths about AI-assisted Coding (2024)
• Worth Reading: Drunken Plagiarists (2025)
• Worth Reading: The Generative AI Con (2025)

These are not bad either:

• What Is ChatGPT Doing … and Why Does It Work?
• We Can’t Build a Hut to the Moon
• The Delusion at the Center of the A.I. Boom (aka AI Solutionism)
• ChatGPT and Chemistry
• Cal Newport on ChatGPT
• Ruby Development with ChatGPT
• ChatGPT Is Your New Intern
• Using ChatGPT as a Technical Writing Assistant
• Why OpenAI is the new AWS
• Overemployed Hustlers Exploit ChatGPT To Take On Even More Full-Time Jobs

Finally, a few real-life uses of large language models:

• An Exploration of Embeddings and Vector Databases
• How GPT and LLMs will affect documentation
• I Built an AWS Well-Architected Chatbot with ChatGPT
• Building Boba AI – how to build a custom user interface in front of a large language model.
• Using Langchain to interact with ChatGPT

Blog Posts I Forgot to Categorize

• PCAP Analysis with Generative AI