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Added some explanatory text on node in general

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+That should take a little while, so I'm going to take advantage of the time we have now to answer one of the questions
+that has popped up in the comments for this series. Specifically, I want to talk about what makes Node just so good at
+serving hundreds and thousands of simultaneous requests with a single thread of execution versus the more traditional
+method of serving each request with its own thread.
+
+I'm going to try and explain this concept with simple example. Visualize a very small restaurant, say one that can
+serve up to three tables at a time, so this restaurant is very small indeed. Now let's assume that this restaurant has
+one waiter to serve all of the guests, but that waiter must stay with each table until they have finished their
+meal. Into our restaurant walks a couple looking for a relaxing lunch. Our waiter seats them, takes their order, and
+brings them their meal and then sits with them taking care of their every beckon call until they have finished their
+meal, and all is well with our fine eating establishment.
+
+Now assume that another couple comes to lunch. Our waiter again seats them, takes their order, brings them their food,
+remains with them throughout their entire meal. While the new couple is enjoying their lunch, however, a second couple
+comes to the restaurant. Unfortunately for them, our waiter is already occupied and so they must wait until the current
+couple finishes their meal before they can be seated. This is obviously a problem, as we have three tables in our
+restaurant and so we could be serving up to three couples at a time! We must hire more waiters. So we bring on a second
+waiter to handle another couple. The only problem is that our restaurant is very small and can barely fit two waiters
+at the same time, so the two waiters start bumping into each other and slowing each other down a bit. We have improved
+our service by being able to serve multiple meals in parallel, but we've slowed down each individual meal ever so
+slightly and we still can't serve our full capacity since we only have two waiters.
+
+The solution of course is to hire a third waiter. Now we can serve up to three diners at the same time, but
+unfortunately our restaurant will not fit three waiters at a time. So now we have an issue and we need to figure out
+how we can resolve it. One way to do it is to have one waiter waiting in the kitchen at all times and then alternate
+between who's on the floor and who's in the kitchen. This is a brilliant idea on our part as it allows us to serve up
+to our capacity simultaneously. Every time one of our waiters sees a small break (say the dining couple is having an
+intimate conversation) they can run back and trade places with the waiter in the kitchen giving them some time to look
+after their customers.
+
+Not a bad solution, eh? But can we do better? We are currently serving our full capacity, yes, but at what cost? We
+have to hire three waiters total (an expensive thing to do) and since only two can be on the floor at a time we are not
+getting our full money's worth out of each employee. Not to mention that having even two waiters on the floor at one
+time is pretty tight causing overall service to slow with just the two. Finally, what happens if we have only two
+customers? I definitely think we can do better than that.
+
+Let's take a look at the process of enjoying a meal. A customer comes in, is seated, looks over their menu shortly,
+orders a meal and eats that meal. The first few minutes of a customers visit is busy for our waiter, but for the
+majority of the meal, the customer is eating or conversing with their companions. Really the only time the waiter is
+needed again is whenever the customer needs a drink refilled or wants their check (or perhaps to order a coffee and
+desert). Do we really need to have a waiter sit with the customer for the entire time? Of course not, so, why don't we
+change our approach. Let's get rid of two of our waiters (sorry guys) and instead of having our sole waiter sit with
+each customer, now we'll have them sit them and get their order and then they can go off and serve another
+customer. Then we can either have the customer signal our waiter when they need further assistance or we could have the
+waiter check on each customer from time to time or a combination of the two methods. Now that's an efficient setup. We
+can serve all three tables at the same time with a single waiter and since we have extra space without the other two
+waiters we can even add a fourth table for more patrons which our single waiter user the new method can handle without
+any issues.
+
+This scenario is fantastic. Our customers are very happy and we are raking in the money now, but there is one problem
+though. What happens if one of our customers takes up all of our waiters time. Assume that one of our customers comes
+in and nothing is good enough for them. Their steak is too well done the first time and undercooked the next. They
+order drink after drink and constantly need their waters refilled. You get the idea, our waiter basically has to spend
+all of their time serving this one customer and since we have no other waiters, the line of customers begins to back up
+until this one customer is finished and leaves.
+
+I think this example gives you a good intuitive understanding for how Node works and it's typically how I like to think
+of it. Obviously the waiters represent a thread in our system and each customer a request, the size of the restaurant
+is supposed to represent the constraints of our system, and the tag team effort of the waiters trading places in the
+kitchen represents the cost of doing a context switch in the OS. Given this example, it's easy to see just how a system
+can quickly become bogged down with too many threads. The solution, of course, is to reduce the number of threads, but
+to do so we must have customers (requests) that need very little attention from our waiter. I/O is like that in our
+system. Performing I/O does not need the attention of a CPU since it is taken care of at the hardware level and using
+techniques like polling and/or signaling our process can essentially answer the request and then only needs to come
+back to it once the response is ready to be returned. It's like our waiter seating and serving our customers and then
+only coming back once the meal is finished to bring the check. The one problem being a customer that needs a lot of our
+attention. The demanding customer represents a request that does very

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