Sunday, October 1, 2017

Rainy Days

When first we practice to code, we do, of course, worry most about branching between different instructions and repeating similar blocks of work over and over again.

In time, we move on to longer and more complex manipulations.

Once those start to build up, we work to cobble them together. Continually building up larger and larger arrangements, targeting bigger features within the software.

That’s nice and all, but since we’ve usually only focused on getting the code to run, it really is only reliable on ‘sunny’ days. Days when there are no clouds, no rain, no wind, etc. They are warm and pleasant. When everything just works.

Code, however, needs to withstand all of the elements; it runs in a cruel, cruel world where plenty of unexpected things occur at regular frequencies. Storms come often, without warning.

Rainy day coding is a rather different problem to solve. It means expecting the worst and planning for it. It also means building the code in a way that its rainy day behavior is both predictable and easily explainable.

For instance, any and all resources might be temporarily unavailable. And they might go down in any number of permutations. What happens then should be easily explainable, and it should match that explanation. The code should also ensure that during the outages no data is lost, no user uninformed, no questions unanswered. It needs to be trustworthy.

Any data coming from the outside might be wrong. Any events might occur in a weird order. Any underlying technology might suddenly behave erratically. Any piece of hardware might fail. Anything at all could happen...

If that sounds like a lot of work, it is! It is at least an order of magnitude harder than sunny day coding. It involves a lot of digging to fully understand rainy days, or tornadoes, or hurricanes or even earthquakes. You can’t list out the correct instructions for a rainy day if you’ve never thought about or tried to understand them.

As software eats the world, it must live up to the cruelties that exist out there. When it doesn’t, it might be temporarily more convenient on the sunny days, but it can actually spawn off more work than it saves when it rains. The overall effect can be quite negative. We were gradually learning how to write robust systems, but as the underlying complexity spiraled out of control these skills have diminished. Too many sunny days and too little patience have driven us to rely on fragile systems while deliberately ignoring the consequences. If we want to get the most out of computers, we’ll have to change this...

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