What Is Measured Service?

The trend that everyone is following right now is measured services. You can see exactly how much of a particular service you consume during a specified period by looking at these bills, which function similarly to restaurant menus but are sent to you by your utility supplier. The only significant difference is that, rather than selecting from various dishes and paying per dish, you can choose from multiple energy providers and pay according to the amount of energy you use. Just as when you go out to eat at a restaurant and take pictures of everything you eat so that you can post them on Instagram later, measured services give utility providers insight into resource consumption and give customers transparency into how they are billed for the services they consume. In other words, measured services are a lot like Instagram photos. You may calculate the amount of water flowing through a pipe in terms of volume or pressure to get an idea of how much water is moving through the pipe. The same holds when evaluating service quality. For instance, if you are a cloud customer and want to know how much storage you've used, you can easily find out by keeping track of how many gigabytes (or even terabytes) of data you have stored on the servers of the cloud provider. Another example would be if you are a business and you want to know how much storage you've used. Metering based on volume is straightforward, making it easy to implement: one byte is equal to one byte, and so forth. What happens if you wish to find out how much computing power your cloud service provider has allocated to you? This is a more difficult task, but it may be accomplished by measuring the amount of work that your virtual machines are performing over time and then dividing that total by the number of cores contained in each machine. Your firm may be interested in knowing how each consumer uses network bandwidth. That is an even tricky nut to crack: the best approach to quantify this would be by sampling, gathering samples from different customers' networks over time and comparing those results to historical averages for firms that are analogous to the one being studied (e.g., "Telecom Provider X").