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The software development economy

There are a series of allegories that encapsulate the murkier, more confusing part about producing software — the human part:

“Culture eats strategy for breakfast” — Peter Drucker¹

“Organizations which design systems …​ are constrained to produce designs which are copies of the communication structures of these organizations.” — Melvin Conway²

Recently a team I have been working with has been evaluating and architecting a shift from a monolith to a microservice architecture with the goal of isolating domains of the business within their own failure boundaries and increasing the aggregate availability of all services.

This in an of itself is not a particularly remarkable journey; the number of companies that have made this transition is so vast it borders on cliche. There are even books written about the topic³. However, it has raised some significant and contentious issues in the company around:

  • CI/CD
  • Authentication
  • Logging
  • Monitoring

And so on. I’m confident these problems will get solved — they’re not particularly complex, there are well documented specifications and an abundance of literature and the company is motivated to execute the transition well.

However, what struck me as the “elephant in the room” was the disconnect between our intended implementation of microservices and subsequent assumptions about our skills, budget and ability to execute versus our historical implementation effort. The conversation about how to implement microservices is interesting but requires us to suspend our own assessment of the problems we have, imagining we are instead the sort of high performing engineers I’ve only encountered thus far in books.

This juxtaposition highlights some of the issues that we’re likely to have when planning any sort of ambitious work.

The fallacy that we are rational

When considering ourselves in our assessments of anything we invariably consider ourselves “rational agents”. From Wikipedia⁴:

A rational agent is an agent that has clear preferences, models uncertainty via expected values of variables or functions of variables, and always chooses to perform the action with the optimal expected outcome for itself from among all feasible actions.

The problem is humans are decidedly not rational. There are an abundances of biases⁵ that represent areas in which, given an objective view of our decision our decision is not rational. Some of my favourites include:

  • Sunk cost: Your decisions are tainted by the emotional investments you accumulate, and the more you invest in something the harder it becomes to abandon it⁶ ⁷.
  • Comparative Bias: When you think about your future health, career, finances, and even longevity — you imagine a rosy, hopeful future. For everyone else, though, you tend to be far more realistic.
  • Diffusion of Responsibility: You are less likely to take responsibility for action or inaction when others are present.

These biases stack the proverbial deck when we are designing our technical systems; we are both destined for a much harder road than we are planning but are by nature blind to the risk.

Given the truism that we think in the ways that we are motivated to and that we are govern by our economic environment the success or failure is much more likely to be determined by those economics.

Or, paraphrased, our culture eats ours strategy for breakfast.

Modelling daily tasks in economic terms

To understand further the impact of economics on software design its worth exploring how different situations play out in less than ideal ways simply due to the economic constraints of the problem.

As software developers we are beholden to the business and product development teams who concentrate on delivering value to consumers. However, occasionally we can receive some request that violations our conceptual model of what the business domain consists of; broadly, it seems nonsensical.

I have seen various of these requests over the years;

  • Sharing passwords between systems
  • Enforcing uniqueness on a comment field — sometimes
  • Encoding business information such as region, organisation in a users identifier
  • Inserting analytics software into a system that ludicrously degrades the performance of the system being analysed

However, the results of each of these examples have been different. In the case of sharing passwords between systems we replied with a flat “No”. In the case of uniqueness of comment field we were instructed “please just do it”. Business information in IDs was discussed perhaps 20 times in various different ways. Analytics were eventually inserted by another team.

In the cases where we “gave in” to business this had demonstrable negative effects on that same business. However, communicating this to stakeholders was so prohibitively expensive we decided that we often elected to “strategically lose” this battle — a euphemism for deciding we couldn’t be fucked.

Occasionally there are things that will yield a high return on investment if completed immediately. Things like:

  • Changes to adhere to new legal requirements
  • Changes to make a new client, very large and expensive happy
  • Changes to introduce a widely demanded market feature or keep with competition

However, these changes come at a cost. This has been discussed under the banner of “technical debt”, though that metaphor has been stretched so thin it is all but useless.

On a practical level, violating the design constraints makes software unpredictable. Unpredictable software is exponentially more difficult to develop, massively driving up the ongoing maintenance cost of software and making future “quick changes” difficult to do.

However, the cost of this is sometimes paid by different teams. Business teams are optimized for seeking as much value as possible; development teams should be optimizing to keep development as cheap and as reliable as possible. But both explaining the risks associated with violating design constraints and pushing back on business demands is an expensive process; the conversations will invariably be difficult and someone will walk away disappointed.

Often this yields a development team that simply implements whatever business says and software that is impossibly complex to maintain.

In the ideal world developers would create software that benefits their teams, even should it not benefit themselves. However, like all industries developers do not generally get promoted as a team.

In an environment in which “technical excellence” is rewarded and technical excellence is measured by a magpie like collection of “technical merits” such that one might be “the most technical” as opposed to solving business problems developers will make changes that maximise the appearance of their own “technical merits”.

This can include things like:

  • Introducing new tools that solve a problem that doesn’t affect business
  • Introducing new policies that advantage them over their colleagues
  • Gatekeeping access to systems with concerns their colleagues are “not skilled enough”
  • Increasing the complexity of systems in a way that is “risk tolerable” in the condition they remain employed

These things can be rewarded within a technical scope so long as developers rate their colleagues evaluation of technical competence as more important than being able to deliver on business goals. In the worst case a developers influence and salary is based on these technical markers.

In the world of systems administrations there has traditionally been a culture derived of the communication boundary between systems administrators, developers and the business team that imply the systems administrators are heroic in their battle to keep systems running despite bizarre implementations from developers and impossible demands from business.

Developers in turn were previously encouraged to throw software “across the wall”; to build it and delegate actually running it to the systems team.

The notion that systems administrators are somehow heroic for being able to deal with these impossible pressures creates a situation in which the administrator can yield a certain amount of prestige and command a given amount of organisational power from being the one who is able to unfuck the system under high pressure.

However, while that prestige exists that engineer may choose to make the tradeoff that, though they have to do things other disciplines do not it is somehow worthwhile given the power they command. This means that developers will either defer or choose not to address structural issues in such systems, instead enjoying their status as a hero developer.

Strategies to encourage a “healthy” software architecture

Given our understanding that:

  1. Humans are fallible and will deceive themselves into their thinking their correct within the bounds of an economic system, and
  2. These systems can be structured to produced negative company results

It stands to reason that we as software architects must not only factor in the concrete business and technical problems, but factor in how humans will behave within that system.

There are a vast number of organisational “dials” that can be addressed but the following are the ones I considered while reflecting on this post:

Melvin Conway made an observation who’s implications have yet to be fully understood in his reflection about software design and communication boundaries.

Communication boundaries become the borders at which decisions are made; the silos in which decision making power is concentrated. These boundaries spring up of their own accord for seemingly legitimate reasons; the most common of which is a “special interest group”.

Becoming aware of both the number of tools that are used to communicate (Slack, Whatsapp, Facebook, Jira, Confluence) as well as who’s using these tools and how is an excellent way to understand the dynamics of an organisation. Further, its often possible to reduce the number of these tools as well as the different “channels” within the scope of the tools by establishing rules as to how the tool should be used.

Reducing the number of tools and increasing the quality of communication in each tool cuts the cost of communication significantly and allows raising risk and reconciling ideas much more cheaply.

A company is essentially a social group dedicated to a single person. The ownership and financials of a company aside, those within a company should be able to understand the direction of the company and how their work fits into that direction.

If this is unclear team members can invent their own stories as to the direction of a company. These stories will be different than the stories of their colleagues and the colleagues will clash and work against each other where those stories are in violation with one another.

There are many devices that can be used to express a story, such as:

  • Vision & Mission
  • OKRs
  • Purpose

But be clear as to what the company's purpose is, and how colleagues should think about their position within that. Without this it's impossible to set up the “correct” incentives for moving forward and colleagues will instead prefer the stories they write themselves, in which they see themselves as the hero.

In my experience it is far more important to people that they’re recognized for the hard work they do and that they feel they’re contributing in the best way to the shared group vision than any notions of money. Money is only a mechanism of evaluating the next job.

However, there are behaviours that may be well intentioned or not considered that are not good for the company. Further, there are things that might not be immediately obvious but that will benefit the company.

For example, while the hero systems administrator earlier is well intentioned and works hard to keep the systems up the hero behaviour should not be celebrated. Doing so creates the wrong incentives; rather, that administrator should be encouraged to push work back to the development team and the development team required to take a pager for their work.

Further, a developer who takes the time to understand a business problem to a greater degree and offers a solution that requires no development should be rewarded as opposed to one who takes and implements the work — no matter the technical elegance of that work.

By being deliberate in picking and reinforcing behaviours that encourage the company goal we create a system in which all colleagues can work together and trust their colleagues have their best interests at heart; at least in relation to the company goal.

Psychological safety is a nebulous topic that has come into public view recently thanks to speakers such as Benè Brown Google’s excellent ReWork studies. Broadly, it is the capacity to raise a controversial or unpleasant idea, make a mistake or otherwise potentially cost the team some utility without personal consequence.

An environment without psychological safety optimizes for safety above all else. This works for a while, but in short order ends up with “defensible silos”; sections of the business attempting to shift responsibility to another part of the business and vise versa.

This environment is unproductive. There is an inherent risk to all work; psychological safety is the acceptance of that risk and the capacity of the team for forgiveness and shared learning from the mistakes that invariably occur. An environment that tolerates such mistakes as far more productive than one that does not.

While implementing development work its tempting to try and imagine all use cases of software and create a model that will factor in all such uses and have no shortcomings.

However, such models generally only work in concept. While in theory they do indeed have no shortcomings or there are things in place to address them the practicality of working with other humans who have different ideas about how software and systems should work mean these new abstractions are misunderstood.

This creates systems of stacked complexity as one developer attempts to reconcile their model against an incorrect understanding of someone else model.

In order to address this developers need to be attempting to keep systems as simple as possible. This, ironically, is not a simple task but doing things such as:

  • Following established patterns
  • Sharing literary and other educational material
  • Writing extensive documentation
  • Keeping new abstractions to an absolute minimum

Reduce the risk of misunderstandings and keep our software as cheap to understand and maintain as possible.

Conclusion

Technical systems are exceedingly complex and with the shift to cloud and cheap compute the systems are distributed, and reconciling them has become even more so. However, when considering how a system arrives at its current level of complexity and unpredictability it is useful to investigate the economic constraints of the team that implemented the software. Further, by being aware of both the inherent fallibility of humans and structuring the software development lifecycle to address some of these shortfalls a skilled software architect can address a vast swathe of problems before they emerge toward the end of software development.

  1. “Culture Eats Strategy For Breakfast. So What’s For Lunch?” https://www.forbes.com/sites/andrewcave/2017/11/09/culture-eats-strategy-for-breakfast-so-whats-for-lunch/#346aa87a7e0f , Nov-2017.
  2. “Conways Laws.” https://en.wikipedia.org/wiki/Conway%27s_law .
  3. S. Newman, “Microservice Architecture.” .
  4. “Rational Agent.” https://en.wikipedia.org/wiki/Rational_agent .
  5. “List of cognitive biases.” https://en.wikipedia.org/wiki/List_of_cognitive_biases .
  6. “Sunk Cost.” https://en.wikipedia.org/wiki/Sunk_cost .
  7. D. McRaney, “The sunk cost fallacy.” https://youarenotsosmart.com/2011/03/25/the-sunk-cost-fallacy/ , Mar-2011.