A design is a set of bets. Writing down which bets you are making — and what would have to be true for them to be wrong — costs an afternoon and saves a rewrite.
This piece walks through how we think about it at Paycux, what we have changed our minds about, and where the sharp edges are.
How it breaks
How it breaks deserves its own treatment. Make the boundary explicit. When one part of the system can only talk to another through a named interface, you can change either side without a meeting; when it cannot, every change becomes a negotiation.
Measure before you optimise, then measure the thing users feel rather than the thing that is easy to instrument. A p50 that looks fine while the p99 is unusable is a reporting failure, not a performance one.
What to do instead
What to do instead is where this gets concrete. Make the boundary explicit. When one part of the system can only talk to another through a named interface, you can change either side without a meeting; when it cannot, every change becomes a negotiation.
Make the boundary explicit. When one part of the system can only talk to another through a named interface, you can change either side without a meeting; when it cannot, every change becomes a negotiation.
- Name the boundary before you cross it
- Measure what users feel, not what is easy to instrument
- Make every retried operation idempotent
- Write down the assumption that would invalidate the design
Measure before you optimise, then measure the thing users feel rather than the thing that is easy to instrument.
Where this leaves us
Where this leaves us deserves its own treatment. Make the boundary explicit. When one part of the system can only talk to another through a named interface, you can change either side without a meeting; when it cannot, every change becomes a negotiation.
Make the boundary explicit. When one part of the system can only talk to another through a named interface, you can change either side without a meeting; when it cannot, every change becomes a negotiation.
Where this leaves us
The pattern repeats across every system we have looked at: the hard part is not the mechanism, it is keeping the mechanism honest as the surrounding assumptions change.
If you are working through the same problem and want to compare notes, the docs cover the mechanics and the console shows the behaviour on your own data.
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