Bound warm workers' host memory and account local RAM

A worker over FLOW_WORKER_MAX_RSS_MB (--worker-max-rss) when its node
returns is retired instead of kept warm, in the shared pool and in every
declared one; 0, the default, keeps them all. The engine now accounts its
own memory (FLOW_RAM / --ram, else the box or the cgroup limit less 1 GB),
so a node's `ram` declaration holds locally. A declared environment the
shared pool already has is that pool rather than a duplicate set of warm
workers.

docs/getting-started/data-science.md

@@ -315,6 +315,13 @@ given `CUDA_VISIBLE_DEVICES`, and leaves a warm worker holding whatever it
 preallocated. Declaring the card is what makes it a worker the engine knows
 to retire, and what stops two such nodes running at once in the first place.
 
+Host memory is held the same way, and there the declaration is not needed. A
+worker that fitted a model keeps what it allocated, and on a laptop a few warm
+ones are the machine. `fluksio serve --worker-max-rss 1024` retires any worker
+holding more than that when its node returns, whichever pool it is in. A
+node's `ram` is counted against this machine's memory, so declaring it is what
+stops three large fits from starting at once.
+
 Declaring nothing is the default and is right for most nodes: a poll, a
 threshold, a message on its way somewhere. Those share the engine's worker pool
 and are given a fair share of `FLOW_CPUS` as a thread cap, which is what stops