Let’s talk about baking cakes. Cakes are great! Not everyone likes sweets but once in a while a cake can taste great. Carrot, apple, boysenberry. Dang, now I want to eat cake.
In design, it can be frustrating to receive a cake. What do I mean by that? A baked cake can’t change. If I make a carrot cake for your birthday only to find out you prefer Devil’s Food… well, nothing we can do about that now.
If I finish writing a design to solve some problem, only to find when we’re reviewing the design that one of the central design decisions doesn’t make sense, it’s too late.
Instead, I find it more effective to include examples of the forks in the road and alternatives. Helping your audience chart the path you’ve taken as you’ve investigated the blind alleys can be helpful for driving alignment on a design.
In some ways, it’s the old adage of “show your work”. If you’re like me, you’ve had it drilled into your head from years of math classes. The instructor wanted to see the work so they could help correct mistakes made in the fundamental assumptions. It’s much the same way in engineering.
As an example, I once worked on a design for rearchitecting engineering infrastructure. I had a blank check. I could choose any tools. That freedom had its own cost. Dealing with ambiguity about how to build devops from scratch felt tough. And overwhelming.
As I worked through the ambiguous parts of the design, I made sure to get incremental buy-in, both on the goal and on the individual decisions along the way. For example, how would we manage standing up servers?
Well, we could use Ansible, which has a set of AWS modules, CloudFormation, or any other number of tools. In a design document, I would write something like this:
The infrastructure pipeline will use Terraform to create, manage, and update servers with a manual review and approval step after generating the planned diff.
And, in an appendix, a comparison (which I’ve omitted some details from) like:
- Explains planned execution before making changes
- Infrastructure built via code
- Supports many cloud platforms, including Google Cloud and Azure
- Active and sizable developer community
- Terraform can store shared state in AWS S3
- Terraform cannot alter existing infrastructure and thus needs a migration plan and new accounts.
- No current way to import existing resources; will need to generate from scratch.
- Some advanced features only available through subscription
This design favors Terraform because…
- Can manage servers and provision them after creation
- Python-based tooling; can customize if needed
- No built-in roll-back functionality
- AWS-managed and supported product
- Runs as a service rather than a tool on a developer’s desktop
- Only supported in AWS
- Required using a JSON / YML generator such as X or Y
- No clear way to do iteration over resources
I’d include some context as well, such as rationale for final choices and the trade-offs we’re making, which I’ve omitted here for the sake of brevity.
Showing Your Work
Let’s talk about short term and long term horizons on why this matters.
For the short term, it helps drive alignment on the immediate decision. Have you ever given a presentation and had someone, after you’ve completed, say “Have you looked at X or Y?”. Showing your work in the document will help people know that you’ve done your research. If you researched something then you’ll wind up talking about it anyway, so you may as well document it.
Also, you might’ve missed something! One of those alternatives may have something valuable that you didn’t consider. For example, something I appreciate more now about CloudFormation is that it will roll back for you on failure. It’s nice to have that option.
In the long term, I can’t count the number of times I’ve looked at a service and asked “Why is this built this way?”. Having a document to help understand it helps with archaelogical discoveries. Like it or not, most of us will not be around for the entire life of project. At some point, we’ll need to introduce the service to someone else or transition it to the next maintainers. Providing a historical narrative of why you’ve built it in a certain way can be helpful.
Lastly, the constraints you worked with at the start of a design may change. For example, some service may support a max of 100 transactions per second and, years later, support greater throughput (see: AWS S3).
PS: This works for code reviews too! Introducing the code review with details about the context and alternatives I considered can be helpful.
So, in conclusion, don’t just bake a cake. Chart the path from A to Z. Show the work. Your audience will appreciate it and they may be able to help you better achieve your goals if they know what you considered.