Comment by whstl
8 hours ago
It's nice to see someone else preaching this:
> Production Lesson: Never let exceptions dictate the norm. Handle them explicitly, in isolated paths or tiers, instead of polluting the mainline logic. What looks like "flexibility" is often just deferred fragility waiting to surface at scale.
I've seen this pattern far too often in production systems. In the name of "covering edge cases", a huge amount of complexity is moved over to configuration languages, interfaces, APIs, etc, to be more flexible. Not only this doesn't free up the developers time (because it overcomplicates it all), it also makes things worse on the other side for the users of such structures. We already have something "flexible": source code itself, no need to reinvent the wheel.
I see something similar with AI generated code where it tries much too hard to handle all the exceptions and ends up swallowing or obfuscating them instead of making things more reliable. Claude seems particularly bad unless you prompt it to minimize complexity
The configuration complexity clock: https://mikehadlow.blogspot.com/2012/05/configuration-comple...
I wish people would realize that moving back to code is possible, though.
It rarely happens because at this point the codebase is so littered with problems that things start requiring long QA, code freezes and once-a-month deployments, and it's impossible to get anything done.
Better never stray from code.
My faviourite configuration pattern for SaaS code: all the configuration for all targets, from local development setup, to unit tests, to CI throwaway deployments, to production is in a single Go package. The current environment is selected by a single environment variable.
Need something else configured beyond your code? Write Go code to emit configs for the current environment, in "gen-config some-tool && some-tool" stanza.
Config values and a configurable plugins system completely solve the problem, dominating over the entire clock.
Iterating further from config values is a great predictor that a project will become a disaster to use, and probably fail completely.
Ah, but what happens when your plugins need to themselves be configured for different client deployments?
You add a few flags, then you need to figure out backwards compatibility as your plugin evolves (which involves defining prioritization rules between options), then those rules get complex enough to have conditionals (say, for granular traffic patterns), which means you have a DSL. And when the DSL gets complex enough, it needs an entire Software Development Lifecycle, which means it's effectively hard-coded. Or, you have people fork the plugin, which is a hard-code in and of itself.
All in all, you don't avoid the "configurability clock," you just decentralize it!
The real problem is that clients inevitably have conflicting needs that cut across any modularization barriers you might think to build. When a configured plugin can have spooky action at a distance, perhaps under-tested due to configuration, is it truly modular? Thus, the clock emerges.