[JohnBooty]

    To support that 1:10000 transaction that takes 
    the most time and needs the most scaling?

Done in the most naive way possible (just adding more servers to one giant pool) yes, it's as ineffective as you say.

What can be effective is segregating resources so that your 1:10000 transaction is isolated so that it doesn't drag down everything else.

Imagine:

- requests to api.foo.com go to one group of servers

- requests to api.foo.com/reports/ go to another group of servers, because those are the 99th percentile requests

They're both running the same monolith code. But at least slow requests to api.foo.com/reports can't starve out api.foo.com which handles logins and stuff.

Now, this doesn't work if e.g. those calls to api.foo.com/reports are creating, say, a bunch of database contention that slows things down for api.foo.com anyway up at the app level due to deadlocks or whatever.

There are various inefficiences here (every server instance gets the whole fat pig monolith deployed to it, even if it's using only a tiny chunk of it) but also potentially various large efficiencies. And it is generally 1000x less work than decomposing a monolith.

Not a magic solution, just one to consider.

[brodouevencode]

Importing code paths that are never executed in a service is a security risk at best, a development/management nightmare on average, or an application crippling architectural decision at worst, especially when working with large monoliths. That is not a smart trade off - I would not recommend this pattern unless the cost to break off is so exorbitant that this would be your only choice.

[JohnBooty]

For a monolith of any nontrivial size, you're talking anywhere from weeks to months of years of engineer work, and those are engineers who also won't be delivering new value during that time. And if other teams are still delivering new features into the monolith during that time, now that's more work for the team whose job it is to break apart the monolith.

So anywhere from tens of thousands to millions of dollars is the cost.

Whether you call that exorbitant is up to you and your department's budget, I guess.