Collaborative Learning Application for Kids: Math, English and Arts

     Compared to traditional web-serving techniques where each connection or request spawns a new thread, taking up system RAM and eventually maxing-out at the amount of RAM available, Node.js operates on a single-thread, using non-blocking I/O calls, allowing it to support support tens of thousands of concurrent connections as show in figure2. 

     A quick calculation: assuming that each thread potentially has an accompanying 2 MB of memory with it, running on a system with 8 GB of RAM puts us at a theoretical maximum of 4000 concurrent connections, plus the cost of context-switching between threads. That’s the scenario you typically deal with in traditional web-serving techniques. By avoiding all that, Node.js achieves scalability levels of over 1M concurrent connections (as a proof-of-concept).There is, of course, the question of sharing a single thread between all clients requests, and it is a potential pitfall of writing Node.js applications. Firstly, heavy computation could choke up Node’s single thread and cause problems for all clients (more on this later) as incoming requests would be blocked until said computation was completed. Secondly, developers need to be really careful not to allow an exception bubbling up to the core (topmost) Node.js event loop, which will cause the Node.js instance to terminate (effectively crashing the program).The technique used to avoid exceptions bubbling up to the surface is passing errors back to the caller as callback parameters (instead of throwing them, like in other environments). Even if some unhandled exception manages to bubble up, there are mutiple paradigms and tools available to monitor the Node process and perform the necessary recovery of a crashed instance (although you won’t be able to recover users’ sessions), the most common being the Forever module, or a different approach with external system tools upstart and monit.