For something like in the article, I’m pretty sure a plan mode is overkill though.
Planning mode must involve making a domain specific language or data structure of some sort, which the execution mode will interpret and execute. I’m sure it would add a lot of complexity to a reporting tool where data is only collected once per day.
First, it is hard, especially in at least somewhat portable manner.
Second, serialization only matters if you cannot (storage, IPC) pass data around in-memory anyway. That's not the problem raised, though. Whatever the backing implementation, the plan, ultimately, consists of some instructions (verbs in parent) over objects (arguments in parent). Serializing instructions any other way than dropping non-portable named references requires one to define execution language, which is not an easy feat.
> The only thing you need to do is have a representation for the plan in your program.
That "only" is doing lifting heavier than you probably realize. Such representation, which is by the way specified to be executable bidirectionally (roll back capabilities), is a full blown program, so you end up implementing language spec, godegen and execution engines. In cases of relatively simple business models that is going to be the majority of the engineering effort.
I'm curious what portability concerns you've run into with JSON serialization. Unless you need to deal with binary data for some reason, I don't immediately see an issue.
> Such representation, which is by the way specified to be executable bidirectionally (roll back capabilities), is a full blown program
Of course this depends on the complexity of your problem, but I'd imagine this could be as simple as a few configuration flags for some problems. You have a function to execute the process that takes the configuration and a function to roll back that takes the same configuration. This does tie the representation very closely to the program itself so it doesn't work if you want to be able to change the program and have previously generated "plans" continue to work.
The hard part concerns instructions and it is not technical implementation of serializing an in-memory data structures into serialization format (be it JSON or something bespoke) that is the root of complexity.
> You have a function to execute the process that takes the configuration and a function to roll back that takes the same configuration.
Don't forget granularity and state tracking. The opposite of a seemingly simple operation like "set config option foo to bar" is not a straightforward inverse: you need to track the previous value. Does the dry run stop at computing the final value for foo and leaves possible access control issues to surface during real run or does it perform "write nothing" operation to catch those?
> This does tie the representation very closely to the program itself so it doesn't work if you want to be able to change the program and have previously generated "plans" continue to work.
Why serialize then? Dump everything into one process space and call the native functions. Serialization implies either strictly, out of band controlled interfaces, which is a fragile implementation of codegen+interpreter machinery.
Ansible implementation is okay, but not perfect (plus, this is difficult to implement properly). For cases like file changes, it works, but if you install a package and rely on it later, the --check command will fail. So I am finding myself adding conditions like "is this a --check run?"
Ansible is treated as an idempotent tool, which it's not. If I delete a package from the list, then it will pollute the system until I create a set of "tearing-down" jobs.
Probably, Nix is a better alternative.