When we think of automation—and more broadly tooling—we tend to think of automating the configuration, monitoring, and (possibly) the monitoring of a network. On the other hand, a friend once observed that when interviewing coders, the first thing he asked was about the tools they had developed and used for making themselves more efficient. This “self-tooling” process turns out to be important not just to be more efficient at work, but to use time more effectively in general. Join Nick Russo, Eyvonne Sharp, Tom Ammon, and Russ White as we discuss self-tooling.
The modern world craves our attention—but only in short bursts. To give your attention to any one thing for too long is failing, it seems, because you might miss out on something else of interest. We have entered the long tail of the attention economy, grounded in finding every smaller slices of time in which the user’s attention can be captured and used.
Innovation and disruption are part the air we breath in the information technology world. But what is innovation, and how do we become innovators? When you see someone who has invented a lot of things, either shown in patents or standards or software, you might wonder how you can become an innovator, too. In this episode of the Hedge, Tom Ammon, Eyvonne Sharp, and Russ White talk to Daniel Beveridge about the structure of innovation—how to position yourself in a place where you can innovate, and how to launch innovation.
The OSI model is perhaps the best-known—and perhaps the most-loved—model in the networking world. It’s taught in every basic networking course, and just about every blog (other than this one) has some article explaining the model someplace or another (for instance, here is one of the better examples).
This week is very busy for me, so rather than writing a single long, post, I’m throwing together some things that have been sitting in my pile to write about for a long while.
From Dalton Sweeny:
A physicist loses half the value of their physics knowledge in just four years whereas an English professor would take over 25 years to lose half the value of the knowledge they had at the beginning of their career. . . Software engineers with a traditional computer science background learn things that never expire with age: data structures, algorithms, compilers, distributed systems, etc. But most of us don’t work with these concepts directly. Abstractions and frameworks are built on top of these well studied ideas so we don’t have to get into the nitty-gritty details on the job (at least most of the time).
In the argument between OSPF and BGP in the data center fabric over at Justin’s blog, I am decidedly in the camp of IS-IS. Rather than lay my reasons out here, however (a topic for another blog post?), I want to focus on something else Justin said that I think is incredibly important for network engineers to understand.
I think whiteboards are the most important tool for network design currently available, which makes me sad. I wish that wasn’t true, I want much better tools. I can’t even tell you the number of disasters averted by 2-3 great network engineers arguing over a whiteboard.
For those not following the current state of the ITU, a proposal has been put forward to (pretty much) reorganize the standards body around “New IP.” Don’t be confused by the name—it’s exactly what it sounds like, a proposal for an entirely new set of transport protocols to replace the current IPv4/IPv6/TCP/QUIC/routing protocol stack nearly 100% of the networks in operation today run on. Ignoring, for the moment, the problem of replacing the entire IP infrastructure, what can we learn from this proposal?
We’re actually pretty good at finding, and “solving” (for some meaning of “solving,” of course), these kinds of immediately obvious tradeoffs. It’s obvious the street sweepers are going to lose their jobs if we replace them with a robot. What might not be so obvious is the loss of the presence of a person on the street. That’s a pair of eyes who can see when a child is being taken by someone who’s not a family member, a pair of ears that can hear the rumble of a car that doesn’t belong in the neighborhood, a pair of hands that can help someone who’s fallen, etc.
Post-mortem reviews seem to be quite common in the software engineering and application development sides of the IT world—but I do not recall a lot of post-mortems in network engineering across my 30 years. This puzzling observation sprang to mind while I was reading a post over at the ACM this last week about how to effectively learn from the post-mortem exercise.
The common pattern seems to be setting aside a one hour meeting, inviting a lot of people, trying to shift blame while not actually saying you are shifting blame (because we are all supposed to live in a blame-free environment now—fix the problem, not the blame!), and then … a list is created on a whiteboard, pictures are taken, and everyone walks away with a rock-solid plan to never do that again.
This is the first of the ironies of automation Lisanne Bainbridge discusses—and this is the irony I’d like to explore. The irony she is articulating is this: the less you work on a system, the less likely you are to be able to control that system efficiently. Once a system is automated, however, you will not work on the system on a regular basis, but you will be required to take control of the system when the automated controller fails in some way. Ironically, in situations where the automated controller fails, the amount of control required to make things right again will be greater than in normal operation.
In the case of machine operation, it turns out that the human operator is required to control the machine in just the situations where the least amount of experience is available. This is analogous to the automated warehouse in which automated systems are used to stack and sort material. When the automated systems break down, there is absolutely no way for the humans involved to figure out why things are stacked the way they are, nor how to sort things out to get things running again.