Network engineering is not “going away.” Network engineering is not less important than it was yesterday, last year, or even a decade ago.
But there still seems to be a gap somewhere. There are fewer folks interested than we need. We need more folks who want to work as full-time network engineers, and more folks with network engineering skills diffused within the larger IT community. More of both is the right answer if we’re going to continue building large-scale systems that work. The real lack of enthusiasm for learning network engineering is hurting all of IT, not just network engineering.
How do we bridge this gap? We’re engineers. We solve problems. This seems to be a problem we might be able to solve (unlike human nature). Let’s try to solve it.
As you might have guessed, I have some ideas. These are not the only ideas in the world—feel free to think up more!
If you walk into a robotics class, even an introductory robotics class, you see people … building robots. If you walk into a coding class, even an introductory one, you see people … writing software. If you walk into a network network engineering class you Continue reading
A networking engineer with a picture-perfect implementation of a dual-homed enterprise site using BGP communities according to RFC 1998 to select primary- and backup uplinks contacted me because they experienced unacceptably long failover times.
They measured the failover times caused by the primary uplink loss and figured out it takes more than five minutes to reestablish Internet connectivity to their site.
A networking engineer with a picture-perfect implementation of a dual-homed enterprise site using BGP communities according to RFC 1998 to select primary- and backup uplinks contacted me because they experienced unacceptably long failover times.
They measured the failover times caused by the primary uplink loss and figured out it takes more than five minutes to reestablish Internet connectivity to their site.
docker run hello-worldRun the hello-world container to verify that Docker in properly installed and running before proceeding.
git clone https://github.com/sflow-rt/containerlab.gitDownload the sflow-rt/containerlab project from GitHub.
cd containerlab ./run-clabStart Containerlab.
containerlab deploy -t clos5.ymlStart the 5 stage leaf and spine topology shown at the top of this page. The initial launch may take a couple of minutes as the container images are downloaded for the first time. Once the images are downloaded, the topology deploys in around 10 seconds.
./topo.py clab-clos5Push the topology to the sFlow-RT analytics software. An instance of the sFlow-RT Continue reading
Yes, the weekend has pretty much already passed, but still …
The Atomic Stealer, also known as “AMOS,” first Continue reading
All the Large Language Models videos from the AI/ML in Networking webinar with Javier Antich are now public. Enjoy!