Note also that the lock blocks readers, and that writes are given priority over reads. Consequently even small volumes of writes can have major effects on readers.

High volume of writes from MANY producers.

From 1 producer, it doesn't matter.

Though the point of mongo is to be webscale which implies to me many writers.

What makes the single producer (writer?) case different from multiple, in the context of the effect on readers?

If there is a single high-volume data pump, for example machine generated data, will readers be affected by a continuous "fire hose" of incoming data?

In my experience, even 1 producer caused a full database lock for hours on our production server. We have 1 mongo server and an erroneous scheduled task of ours started at about 6am. It's only one process but the task basically re-syncs an entire collection (which was about 80,000 writes).

That single producer caused wide-scale locking/hanging for all readers on the website and I had to manually stop the task during business hours because of that. Oy!

Isn't that supposed to be the ideal use case for Mongo though?

Not for single-server performance. The database level lock severely limits MongoDB's single server performance. Just look up the sysbench benchmark comparing MongoDB with TokuMX (which I work on)