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The Hedge Episode 11: Roland Dobbins on Working Remotely

I failed to include the right categories the first time, so this didn’t make it into the podcast catcher feeds correctly…

Network engineering and operations are both “mental work” that can largely be done remotely—but working remote is not only great in many ways, it is also often fraught with problems. In this episode of the Hedge, Roland Dobbins joins Tom and Russ to discuss the ins and outs of working remote, including some strategies we have found effective at removing many of the negative aspects.

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Data, applications, and the meaning of the network

Two things which seem to be universally true in the network engineering space right this moment. The first is that network engineers are convinced their jobs will not exist or there will only be network engineers “in the cloud” within the next five years. The second is a mad scramble to figure out how to add value to the business through the network. These two movements are, of course, mutually exclusive visions of the future. If there is absolutely no way to add value to a business through the network, then it only makes sense to outsource the whole mess to a utility-level provider.

The result, far too often, is for the folks working on the network to run around like they’ve been in the hot aisle so long that your hair is on fire. This result, however, somehow seems less than ideal.

I will suggest there are alternate solutions available if we just learn to think sideways and look for them. Burning hair is not a good look (unless it is an intentional part of some larger entertainment). What sort of sideways thinking am I looking for? Let’s begin by going back to basics by asking a question that might a bit dangerous to ask—do applications really add business value? They certainly seem to. After all, when you want to know or do something, you log into an application that either helps you find the answer or provides a way to get it done.

But wait—what underlies the application? Applications cannot run on thin air (although I did just read someplace that applications running on “the cloud” are the only ones that add business value, implying applications running on-premises do not). They must have data or information, in order to do their jobs (like producing reports, or allowing you to order something). In fact, one of the major problems developers face when switching from one application to handle a task to another one is figuring out how to transfer the data.

This seems to imply that data, rather than applications, is at the heart of the business. When I worked for a large enterprise, one of my favorite points to make in meetings was we are not a widget company… we are a data company. I normally got blank looks from both the IT and the business folks sitting in the room when I said this—but just because the folks in the room did not understand it does not mean it is not true.

What difference does this make? If the application is the center of the enterprise world, then the network is well and truly a commodity that can, and should, be replaced with the cheapest version possible. If, however, data is at the heart of what a business does, then the network and the application are em>equal partners in information technology. It is not that one is “more important” while the other is “less important;” rather, the network and the applications just do different things for and to one of the core assets of the business—information.

After all, we call it information technology, rather than application technology. There must be some reason “information” is in there—maybe it is because information is what really drives value in the business?

How does changing our perspective in this way help? After all, we are still “stuck” with a view of the network that is “just about moving data,” right? And moving data is just about exciting as moving, well… water through pipes, right?

No, not really.

Once information is the core, then the network and applications become “partners” in drawing value out of data in a way that adds value to the business. Applications and the network are but “fungible,” in that they can be replaced with something newer, more effective, better, etc., but neither is really more important than the other.

This post has gone on a bit long in just “setting the stage,” so I’ll continue this line of thought next week.

This topic is a part of my talk at NXTWORK 2019—if you’ve not yet registered to attend, right now is a good time to do so.

(Effective) Habits of the Network Expert

For any field of study, there are some mental habits that will make you an expert over time. Whether you are an infrastructure architect, a network designer, or a network reliability engineer, what are the habits of mind those involved in the building and operation of networks follow that mark out expertise?

Experts involve the user

Experts don’t just listen to the user, they involve the user. This means taking the time to teach the developer or application owner how their applications interact with the network, showing them how their applications either simplify or complicate the network, and the impact of these decisions on the overall network.

Experts think about data

Rather than applications. What does the data look like? How does the business use the data? Where does the data need to be, when does it need to be there, how often does it need to go, and what is the cost of moving it? What might be in the data that can be harmful? How can I protect the data while at rest and in flight?

Experts think in modules, surfaces, and protocols

Devices and configurations can, and should, change over time. The way a problem is broken up into modules and the interaction surfaces (interfaces) between those modules can be permanent. Choosing the wrong protocol means choosing a different protocol to solve every problem, leading to accretion of complexity, ossification, and ultimately brittleness. Break the problem up right the first time, and choose the protocols carefully, and let the devices and configurations follow.

Choosing devices first is like selecting the hammer you’re going to use to build a house, and then selecting the design and materials used in the house based on what you can use the hammer for.

Experts think about tradeoffs

State, optimization, and surface is an ironclad tradeoff. If you increase state, you increase complexity while also increasing optimization. If you increase surfaces through abstraction, you are both increasing and decreasing state, which has an impact both on complexity and optimization. All nontrivial abstractions leak. Every time you move data you are facing the speed of serialization, queueing, and light, and hence you are dealing with the choice between consistency, availablity, and partitioning.

If you haven’t found the tradeoffs, you haven’t looked hard enough.

Experts focus on the essence

Every problem has an essential core—something you are trying to solve, and a reason for solving it. Experts know how to divide between the essential and the nonessential. Experts think about what they are not designing, and what they are not trying to accomplish, as well as what they are. This doesn’t mean the rest isn’t there, it just means it’s not quite in focus all the time.

Experts are mentally stimulated to simulate

Labs are great—but moving beyond the lab and thinking about how the system works as a whole is better. Experts mentally simulate how the data moves, how the network converges, how attackers might try to break in, and other things besides.

Experts look around

Interior designers go to famous spaces to see how others have designed before them. Building designers walk through cities and famous buildings to see how others have designed before them. The more you know about how others have designed, the more you know about the history of networks, the more of an expert you will be.

Experts reshape the problem space

Experts are unafraid to think about the problem in a different way, to say “no,” and to try solutions that have not been tried before. Best common practice is a place to start, not a final arbiter of all that is good and true. Experts do not fall to the “is/ought” fallacy.

Experts treat problems as opportunities

Whether the problem is a mistake or a failure, or even a little bit of both, every problem is an opportunity to learn how the system works, and how networks work in general.

 

Is it planning… or just plain engineering?

Over at the ECI blog, Jonathan Homa has a nice article about the importance of network planning–

In the classic movie, The Graduate (1967), the protagonist is advised on career choices, “In one word – plastics.” If you were asked by a young person today, graduating with an engineering or similar degree about a career choice in telecommunications, would you think of responding, “network planning”? Well, probably not.

Jonathan describes why this is so–traffic is constantly increasing, and the choice of tools we have to support the traffic loads of today and tomorrow can be classified in two ways: slim and none (as I remember a weather forecaster saying when I “wore a younger man’s shoes”). The problem, however, is not just tools. The network is increasingly seen as a commodity, “pure bandwidth that should be replaceable like memory,” made up of entirely interchangeable parts and pieces, primarily driven by the cost to move a bit across a given distance.

This situation is driving several different reactions in the network engineering world, none of which are really healthy. There is a sense of resignation among people who work on networks. If commodities are driven by price, then the entire life of a network operator or engineer is driven by speed, and speed alone. All that matters is how you can build ever larger networks with ever fewer people–so long as you get the bandwidth you need, nothing else matters.

This is compounded by a simple reality–network world has driven itself into the corner of focusing on the appliance–the entire network is appliances running customized software, with little thought about the entire system. Regardless of whether this is because of the way we educate engineers through our college programs and our certifications, this is the reality on the ground level of network engineering. When your skill set is primarily built around configuring and managing appliances, and the world is increasingly making those appliances into commodities, you find yourself in a rather depressing place.

Further, there is a belief that there is no more real innovation to be had–the end of the road is nigh, and things are going to look pretty much like they look right now for the rest of … well, forever.

I want you, as a network engineer, operator, or whatever you call yourself, to look these beliefs in the eye and call them what they are: nonsense on stilts.

The real situation is this: the current “networking industry,” such as it is, has backed itself into a corner. The emphasis on planning Jonathan brings out is valid, but it is just the tip of the proverbial iceberg. There is a hint in this direction in Jonathan’s article in the list of suggestions (or requirements). Thinking across layers, thinking about failure, continuous optimization… these are all… system level thinking, To put this another way, a railway boxcar might be a commodity, but the railroad system is not. The individual over-the-road truck might be a commodity, and the individual road might not be all that remarkable, but the road system is definitely not a commodity.

The sooner we start thinking outside the appliance as network engineers or operators (or whatever you call yourself), the sooner we will start adding value to the business. This means thinking about algorithms, protocols, and systems–all that “theory stuff” we typically decry as being less than usefl–rather than how to configure x on device y. This means thinking about security across the network, rather than as how you configure a firewall. This means thinking about the tradeoffs with implementing security, including what systemic risk looks like, and when the risks are acceptable when trying to accomplish as specific goal, rather than thinking about how to route traffic through a firewall.

If demand is growing, why is the networking world such a depressing place right now? Why do I see lots of people saying things like “there will be no network engineers in enterprises in five years?” Rather than blaming the world, maybe we should start looking at how we are trying to solve the problems in front of us.

The End of Specialization?

There is a rule in sports and music about practice—the 10,000 hour rule—which says that if you want to be an expert on something, you need ten thousand hours of intentional practice. The corollary to this rule is: if you want to be really good at something, specialize. In colloquial language, you cannot be both a jack of all trades and a master of one.

Translating this to the network engineering world, we might say something like: it takes 10,000 hours to really know the full range of products from vendor x and how to use them. Or perhaps: only after you have spent 10,000 hours of intentional study and practice in building data center networks will you know how to build these things. We might respond to this challenge by focusing our studies and time in one specific area, gaining one series of certifications, learning one vendor’s gear, or learning one specific kind of work (such as design or troubleshooting).

This line of thinking, however, should immediately raise two questions. First, is it true? Anecdotal evidence seems to abound for this kind of thinking; we have all heard of the child prodigy who spent their entire lives focusing on a single sport. We also all know of people who have “paper skills” instead of “real skills;” the reason we often attribute to this is they have not done enough lab work, or they have not put in hours configuring, troubleshooting, or working on the piece of gear in question. Second, is it healthy for the person or the organization the person works for?

To make matters worse, we often see this show p in the job hunting process. The manager wants someone who can “hit the ground running” on this project, using this piece of equipment, and they want them on board and working tomorrow. In response, we see job descriptions and recruiting drives for specific skill sets, down to individual hardware and software.

I recently ran across two articles that push back on this 10,000 hours10,000 rule way of learning does not work.

Over time, as I delved further into studies about learning and specialisation, I came across more and more evidence that it takes time to develop personal and professional range – and that there are benefits to doing so. I discovered research showing that highly credentialed experts can become so narrow-minded that they actually get worse with experience, even while becoming more confident (a dangerous combination). And I was stunned when cognitive psychologists I spoke with led me to an enormous and too-often ignored body of work demonstrating that learning itself is best done slowly to accumulate lasting knowledge, even when that means performing poorly on tests of immediate progress. That is, the most effective learning looks inefficient – it looks like falling behind.

Re-read that last sentence—what turns out to be the most effective learning strategy often looks just like falling behind. Another recent article pointed out that deep expertise seems to be losing its sway in many workplaces. The author spends time around a new United States Navy littoral ship, which are designed to operate with much smaller crews—one-half to one-third of a comparably sized ship staffed in the traditional way. How do these ships operate? By cross training crew members to be able to do many different tasks.

One of the interesting things this latter article points out is this ability to do many different tasks requires fluid intelligence, which is a completely different set of skills than crystallized intelligence. Fluid intelligence, it seems, becomes stronger over time, peaking much later in life. While the article does not discuss how to develop the kind of fluid intelligence that will serve you well later in life, when this kind of thinking overtakes your narrower skill sets, it makes sense that building a broader set of skills over time is a more likely path than following the 10,000 hour rule.

There is, however, one question that neither author spends a lot of time discussing: if you are not focusing on learning one thing, then how, and on what, should you focus your time spent learning on? For the top athletes in the sports article, it seems like they spent a lot of time in different kinds of physical activity. There was an area of focus, but it was not the kind of narrow focus we normally associate with being excellent at one sport. In the same way, the sailors in the second article were all focused in a broader area—anything required to run a ship. Again, there is focus, but not the kind of narrow focus you might have expect on more standard boats, where one set of sailors just focus on working the lines, while another just focus on navigating, etc. The focus is still there, then—it is just a broader focus.

Why and how does this work? My guess is it works because the skills you learn in dancing, for instance, will help you learn better footwork in boxing and other sports (an example given in the sports article linked above). The skill you learn in handling the lines will help you understand the lay and movement of the boat in ways that are helpful in navigation. These skills, in other words, are somewhat adjacent.

But these skills are more than adjacent. Many of them are also basic, or theoretical, in ways we do not value in the network engineering world. The point I often hear made is: I don’t care about how BGP really works, so long as I can write a script that configures it, and I can troubleshoot it when it breaks. Or: I actually work on vendor x model 1234 all day, what I really need to know to be effective is how to configure it… when I need to replace that piece of gear, I will learn the next one so I can keep doing my job.

My point is this: this way of building skills, this way of working, does not “work” in the long term. There will come a point in your life, and in the life of your company, when point skills will weaken and lose their importance. The research, and experience, shows the better way to learn is to take on the long game, to learn the theory, and to practice the theory in many different settings, rather than focusing too deeply on one thing.

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