I stumbled upon an article with an interesting title (and worth reading): To Make Self-Driving Cars Safe, We Also Need Better Roads and Infrastructure… and thought about the claims along the lines of “if they managed to solve the self-driving cars challenge, it’s realistic to expect self-driving networks” made in Self-Driving Networks podcast episode. Turns out the self-driving cars problem is far far away from being solved.
Here are a few obvious truths from the article:
The designers of self-driving systems simply cannot foresee every possible combination of conditions that will occur on the road.
Over time, learning will take place and the number of situations that systems cannot recognize will decrease.
Absolutely true. The interesting AI problems (like image recognitions) have huge standardized learning sets that the researchers can use to test and train their algorithms, and companies working on self-driving cars invested into millions of miles driven in real-life conditions. How far along are we in creating learning sets for self-driving networks?
Finally, there’s the “slight” challenge of funding. How much are the Waymos of the world investing into self-driving cars, and how much do you think the networking vendors are investing into self-driving networks (apart from burning the marketing budget)?
As much as I love the concept of self-driving networks, I remain as skeptical as I was when we were recording the podcast that we’ll see a universal solution any time soon. You can make enormous progress with a small team (like what Facebook described at RIPE71), but there’s no substitute for hard work and understanding what infrastructure your business really needs.
As always, the choice is yours: take the blue pill and believe in a vendor-delivered silver bullet, or take the red pill and get your hands dirty. Hundreds of network engineers deciding to go down the red pill path took the Building Network Automation Solutions course to get them started. Will you join them?