Node and Scaling in the Small vs Scaling in the Large

Terminology is part of the problem here. Comparing "threaded" vs. "evented" may have made sense in, say, Windows in 2003 or some context where we are clearly talking "select loop" vs. "pthreads", but there are a lot of things that could be called "threading" models now. Well, sort of a lot of things, because they're all converging now on the same core primitive, leaving us with two basic cases here: 1. Old, synchronous code and 2. code running on the local select-like primitive that freely composes with other such code.

Node.js clearly wins to the extent that it is code of type 2 replacing code of type 1. But when you compare Node.js against other technologies of type 2, I find it hard to conclude that it really stands out on any front except hype. All the type 2 technologies tend to converge on equal performance on single processors, driven by the performance of the underlying select-like primitive, so what's left is two things: comparing the coding experience, where "evented" really loses out to thread-LIKE coding that actually under-the-hood is transparently transformed into select-like-primitive-based code, but is not actually based on threads, and two, dispatching the tasks to multiple processors, where Node.js doesn't even play.

A great deal, if not nearly all, pro-Node.js arguments persistently argue against systems of type 1... but they don't get that that's not actually the competition. It's the other type 2 systems that they are really facing, and Javascript isn't really helpful there. Events are a hack around the fact that Javascript's heritage is pure type 1, not a glorious feature, and I think you really ought to stick with the languages that are natively type 2, or functional enough that they made a smooth transition. Node.js is forever going to be a platform that spent a lot of its engineering budget just getting Javascript to straddle the divide from 1 to 2 with some degree of success, and that's going to be engineering budget you can't spend on your project.

I completely agree. Further, as he points out, code using events is fundamentally different than code that uses threads, in ways that aren't immediately clear to someone writing a "hello world" app. Complexities arise in ways that don't in threaded code. I think many of the more naive "event-driven" boosters haven't gotten far enough to see the real potential for pain.

That's not saying threaded code doesn't have its own set of issues; but having written a tool that saw very high traffic, was written an event-driven style, and suffered performance reliability issues, I can say that the event-driven approach is no panacea.

That said, for certain applications, one or the other approach is clearly appropriate. But to make that decision requires an understand of the strengths and drawbacks of each.

IMHO you may be able to scale node 'in the big' if you plan to scale on a level above node (i.e. in node instances and inter-node communication) instead of changing the code running in node to scale big.

When it comes to the Go language, bare-metal performance certainly seemed to be something Pike was giving a shit about when he spoke last week at OSCON and the Emerging Languages Camp I organized. Go in its current fairly young stage has performance that's not too terrible; they've mostly optimized for raw complication speed so far, which is interesting, and uniquely suited to Google's development problems. Pike has said that he wants Go to be a replacement for other systems languages. That's going to mean competing with those languages, performance-wise.

I think Clojure's concurrency model ends up more concisely and correctly expressing the "parallelism of the real world" when you consider the dimension of time. Rich Hickey has done some really important thinking there.

Finally, I think you'll find that anyone with a fixed budget for servers isn't going to think that making the most of "local physical concurrency" on every machine in their cluster is a "fool's errand". Hardware is cheaper than it used to be, but it isn't free, and deploying and maintaining it is costly and time consuming. If you can make the most of your hardware and operations investements with a little more thought-work, why not do so?

One of the traditional threads-don't-scale arguments, which led to the early-2000s wave of evented competitors to Apache (lighthttpd, nginx), was that threads have per-thread call-stack overhead that's hard to minimize without either OS support for dynamically sized call stacks, or choosing really small static stack sizes that make writing code that doesn't stack-overflow tricky.

A different issue was that OSs used to be very bad at scheduling large numbers of threads--- if you spawned 10,000 threads, the system scheduler blew up. I believe that's mostly much improved these days.

Most of the threads-don't-scale arguments also assume OS threads; user-level threads are another story.