IO scalling problem and IO Source

IO scalling problem and IO Source

Please complete all 3 basic tasks

Task 1

Please read the following stamen and answer in at least 250 words

One of the advantages of Node.js is in relationship to the I/O scaling problem. In your own words, please describe the I/O scaling problem and compare common I/O sources.

Task two

Please read the statement below, and provide feedback on the stamen in at least 150 words.

MG.

The input and output process does exactly what you think it does. This process is just the information that is being sent or received through a network. When large requests are sent through a network, it develops a input and output scaling problem. Since many people can access networks and attempt to receive information from a server, the problem occurs when too many people are attempting to access the same information. This is when you have input and output scaling.

Traditional web servers used to answer each request. Since this would take too much time and take up too much memory, this method was quickly outdated. Modern servers can quickly solve this problem by creating a thread pool. A thread pool basically keep the requests going by keeping your place in line and they do not start and stop the process with saves even more time. Even this method was soon to be replaced by the Nix way. Since Node.js works handling a single thread request, the Nix way uses this to create a single request type server. This server can handle an extreme amount of concurrent requests and also does not use the start and stop method. This method sped up the process is a very good way.

Task 3

SD

Please read the statement below, and provide feedback on the statement in at least 150 words.

The problem that arises with I/O Scaling is the need for the system to be able to handle many tasks simultaneously. The issue that occurs would be similar to when you have an attack on a website and the site crashes. What occurs here is that other systems are constantly querying the website for information which in turn causes an overload of requests the server can not handle. This overload is what causes the system to crash. The system then needs to be rebooted and the queries stopped to ensure future reliability and the way in which the attack was used repaired to prevent future attacks. To make it easier to understand would be if a company put airline tickets on sale for $1 each instead of the regular $200 per ticket price. This would cause a buying frenzy,few websites would have the back end resources to support the internet traffic and the site would temporarily crash.

Using Node.js has the ability to offset these scaling issues in a few different ways. Using a thread pool server to solve the problem helps minimize CPU and memory usage to allow the system to handle large data lots at the same time efficiently. Nginx is the probably the ideal way to handle large scale data because compared to the thread method of a thread for each request it uses a single thread. This reduces CPU usage and makes memory usage minimal which makes the amount of concurrent processes exponential. As you can see with several different ways to handle server traffic choosing the right way for future scalability is important based on company needs. As we can see Node.js helps websites run efficiently and also allows servers to run in a highly optimized manner.

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