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- shadow IT
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- TV
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Complexity and simplicity are friends
How many applications is too many? 100? 200? 1,000? 7,000?
I have worked for many different organisations with different numbers of applications. Whatever the numbers, though, they all had one thing in common: somebody, somewhere thought that we had too many applications.
I have always found this belief puzzling. We build applications because we believe that they have value (otherwise we wouldn’t put so much effort into writing those business cases). We celebrate our success when we implement them. And then we record their existence in our great big list of applications, lament that we have so many, and wish that we had fewer. Is there any other field of endeavour where what we have built moves so quickly from asset to liability (whatever our accounting rules say)?
I believe that people worry about the number of applications in their estate because of an inherent fear of complexity, and because the number of applications is a visible signal of complexity. They perceive that their technology is becoming too costly, too slow and too risky, and they also see that these factors rise in sync with the number of applications. The more stuff they have, the harder it seems to get
Seek solutions that can be understood by anyone - even yourself
“No.”
It wasn’t the answer we were expecting. I was sitting alongside my colleague, in the office of a very senior sponsor and stakeholder. We had just pitched our plan for a complicated, urgent piece of corporate restructuring: the divestment of nearly a fifth of the organisation. It was a time sensitive, strategic and difficult project. My colleague was in charge of the business change plan, and I was in charge of the technology change plan. Between us, we thought we had come up with the best route to success. But our sponsor wasn’t buying it.
“No,” he said again, but this time he elaborated.
“The plan that you have come up with is inventive and clever. If we execute it well, we might just pull this off. It’s efficient, and makes the best use of our limited resources. But there’s a problem. It’s too complicated. I can’t explain this to the thousands of people we’ll need to do the work and expect everybody to keep it straight through months and years of delivery. You’ll have to go away and think of a plan that costs more and takes longer - but is simpler.”
Laziness and improvisation: two programming superpowers
Programming is a superpower.
In comics and films, there are several superheroes whose power is to control machines. Programmers can control machines too, except, rather than extending their hands and screwing up their faces in concentration, they do it by typing on keyboards. (Alright, they may screw their faces up in concentration too.)
Moreover, just like the comics, there are many variants of the programming superpower. Lots of superheroes can fly, but they don’t all fly in the same way: some ride on magnetic waves, some raise winds to lift them and others . . . can just fly, without any attempt at explanation. Similarly, some programmers are great at front ends, some are great at back ends, some are great at performance, and others are great at reliability.
Keeping the lights on
Do you have a line in your IT budget which says something like ‘keep the lights on’ or ‘keep the show on the road’, or ‘maintenance’ or ‘support’ - or even just ‘run?.
Over the years, I have put together IT budgets with at least one of these lines in. They’re a convenient way of signalling to finance people, hovering over their printouts and spreadsheets, ready to wield the red pen or press the delete key, that they’d better not strike out this item. They don’t have to understand technology to understand that, without this money, something will break. They’ll probably ask us to swallow inflation, or to trim around the edges, but they’re unlikely to cancel it altogether.
While this arrangement can be convenient (the IT department gets its money; the finance department does not have to understand technology), I do not believe that it is healthy or helpful. I believe that we would do a better job if we explained exactly what we spend this money on, why it matters, and why it gets more complex and more difficult every year.
Three reasons to learn to code
There’s no point in learning to code: In a few years’ time, we won’t need programmers any more.
I’ve heard people say that a lot in the last couple of years. But that’s nothing new: I’ve heard people say this every year throughout a long career in technology.
On my very first day in my very first paid programming job, I was told that we wouldn’t need programmers any more, because fourth generation languages (4GLs) would enable us to express user requirements in a structured way. In that case, ‘expressing user requirements in a structured way’ turned out to mean using clumsy abstractions that needed to be supplemented with code. Thirty years later, that particular 4GL is forgotten, but we still produce billions of lines of code.
It *is* about the technology (and all of the other stuff too)
It’s not about the technology.
Have you ever said those words? I have said them several times in my career, and heard them many more times. They are usually followed with something like . . . it’s about culture / user experience / business outcomes / customers / change management.
I think that there are good reasons to use these words, and bad reasons to use these words.
They are useful words when we are in danger of losing sight of all the other factors. When building software solutions, it is easy to get lost in the details of tools, components, services and other technical considerations. It is not unusual for technical teams to lose weeks arguing about frameworks and languages, while forgetting about the outcomes that those frameworks and languages are intended to deliver.
In software, use is better than reuse
If I drink from a plastic bottle of water, and put the bottle in the recycling bin when it is empty, the plastic in the bottle can be used again. This reduces the impact on the environment, but requires a process to collect the bin, sort the contents, process them, and insert any reclaimed materials back into the supply chain.
By contrast, if I drink water from a glass, then I can simply wash it up and put it back in the cupboard. And it is there when I want another drink of water.
This is the difference between reuse and use.
Reuse is a frequently stated goal of technology strategies and architectures. It makes intuitive sense. We spend a lot of money building and buying technology solutions. Different parts of our organisation have similar needs: why not reuse the solutions in more than one place? Some architecture teams even have goals and metrics to measure and encourage reuse. (Like many examples in these articles, this is a mistake that I have made more than once.)
Who puts the V in your MVP?
We’ve been doing it since before the beginning.
In 1943 Donald Michie and Jack Good were working at Bletchley Park on a machine known as the Heath Robinson, after the cartoonist who drew outlandish contraptions. They were attempting to break the Lorenz cypher used by the German high command, an even greater challenge than the Enigma cypher broken by the team which included Alan Turing.
The machine was known as a Heath Robinson because of its complex and unlikely appearance: paper tapes running at high speed around an apparatus called a ‘bedstead’, connected to a maze of wires, mechanical relays and, crucially, a few electronic valves. Getting the Heath Robinson to work reliably was an enormous challenge - such a challenge that it led to the creation of the Colossus, the first digital computer, by Tommy Flowers and team.
When is the full stack too full?
Which prefixes would you like with your Ops?
Would you like some DataOps, some FinOps, some GitOps, some ChatOps, some DevSecOps, or would you prefer to go with classic DevOps? (You may, not, by the way, simply choose Ops.)
Since the dawn of the DevOps movement, the technology profession has seized on the idea that capabilities which were previously siloed and separated should be held by empowered teams with full accountability for what they build and what they run. This is a good idea. The alternative is to have diffuse accountability, degraded quality, teams that communicate with each other by queues and messages, long wait times and fragile systems.
DevOps and the case of the non-fungible DBA
The problem with many traditional, but wrong, ways of organising technology work is that they appear so reasonable.
If you have never organised the work to build a software system before, then it seems reasonable to organise it in the way that you would build a physical building, such as a house or a bridge. You make your plan out of tasks, dependencies and milestones, with blueprints written in advance, planning permission obtained, and predictable estimates for predictable work. Then you wonder why your plans are in pieces, your estimates are blown, and your bridge looks like a cross between a tunnel and a spaceport.
Similarly, if you are defining the operating model for a technology organisation, then it seems reasonable to group scarce, expert resources into pools, so that they can serve multiple needs at the same time. You create all the constructs that go with such a team: ticketing systems, SLAs, queues and prioritisation mechanisms. Then you wonder why everyone is waiting on everybody else, and no-one takes accountability when things go wrong.
Have we overloaded the term ‘technical debt’?
What do we mean by technical debt?
These days, we seem to mean a lot more than Ward Cunningham did when he first coined the term in 1992. As Cunningham has helpfully clarified, he was specifically referring to coding choices made in the absence of full information - information that could only be gained by releasing a version of the code and learning how it was used. The technical debt incurred in this way could be paid down by refactoring the code as its full feature set became apparent - or could be ignored, at the risk that, just as with financial debt, servicing the debt would become all-consuming: developers would spend all their time navigating an ever more complex code base, full of incrementally added and contradictory concepts.
Thinking at lightspeed
Some science fiction writers ignore relativity and don’t treat the speed of light as an absolute limit. This is understandable from a narrative perspective: it allows them to tell stories spanning many worlds, in which fleets of space ships flit across the galaxy, and in which events that happen on one planet can meaningfully be said to happen at the same time as events on another planets.
However, I think that some of the more interesting stories are those which use the concept of relativity and the weird effects it produces. By allowing their fictional vessels to accelerate to near, but not beyond, the speed of light, they create stories in which time moves differently for different characters. In such stories, a character who travels a lot may live a normal human lifetime while millenia pass on the places they visit, and events ripple across the galaxy in lightspeed jumps.