The Mother-in-Law’s Guide to Cloud Computing

This is part of my “Mother-in-Law’s Guide to Technology.” My Mother-in-Law is a very smart woman even if she isn’t a “computer person.” The goal of this post is to take a very big and treacherous sounding idea and bring it down to earth. I tried this before in a post which I’ve now renamed The Mother-In-Law’s Guide to Chaos Engineering.

Dearest Mother-in-Law,

You know when we visit a Target or a Wal-Mart in the suburbs and they have 30 checkout lanes and only 3 are open at any time? I always wondered why that happens. It even sparked someone to write a funny blog post about the phenomenon: Target Store Opens More than Three Checkout Lanes; Shoppers Confused.

On a Normal Day, the Store Has Full Time Cashiers to Manage the Base Volume. When More People Come In, Part-Time Cashiers Will Be Engaged.

How many checkout lanes should Target build? At first, I thought about how many customers Target has on an average day and that they built that number of cash registers. If they have 300 customers in a day they would need enough cashiers to serve 300 people. The problem is that the flow of people into the store isn’t constant. For example, if the peak time of day is at 4PM and there are 10 people in line, Target can’t tell those people to come back at a less busy time. So on a daily basis, they need to plan for this by making sure they have enough checkout counters (and cashiers) available to keep the lines down to a reasonable level even when it gets busy. The way most retailers do this is to have only a few full-time dedicated as cashiers for the slow times and some other part-time cashiers that mainly do another job but can jump in when the store gets busy.

But that doesn’t answer the question of how many checkout lanes they need to build. Target needs to have enough checkout lanes so that even on the busiest days, they can hire enough part-time cashiers to keep lines relatively short. This means that Target needs to build the number of checkout lanes that they need for the busy time of the year, not for the peak time of day. At Target, this is the Christmas shopping season starting with Black Friday. On Black Friday the store is filled with shoppers struggling to check out. This is the day that Target opens up all their checkout lanes. So even though they’re not used a good portion of the year, Target still needs to build the number of checkout lanes they need for Black Friday.

The Number of People on Black Friday is Much Greater Than That of a Normal Day. This Drives the Total Number of Checkout Lanes.

So what does this have to do with cloud computing? Cloud computing is like Target having these checkout lanes only where they’re needed, like on Black Friday. They wouldn’t have to pay for the cost of having these checkout lanes at less busy times of the year. They would be able to create new ones during the Christmas season and get rid of them at other times of the year. How does this work? Instead of buying checkout lanes (or in the case of cloud computing, computers), they just rent what you need. This means that Target can increase or decrease their capacity based on the actual need from your customers.

Now let’s make the jump from Target to Cloud Computing by defining a few Let’s define a few things:

  • Servers: These are computers that “serve up” the information you need. Just like the cashiers at Target, if a server isn’t available you’re going to have to wait in line.
  • Server Capacity: This is the total number of servers that can be available to provide information. Just like the number of checkout lanes at Target, once you’re out of checkout lanes, you can’t have any more cashiers.
  • Peak Request times: This is your Black Friday time when you the most requests.

Now you can understand one of the key benefits of cloud computing:

Cloud computing provides flexible server capacity to meet demand during peak request times and release that capacity at during other periods.

So there you have it. In the real world, Target needs to build enough capacity (checkout lanes)  to meet demand during peak request times (Black Friday). But the cloud computing model allows companies to greatly reduce their capacity during non-peak times because they can easily turn on or turn off this capacity.

Note: You can actually see a checkout model like this (sans the physical checkout lanes) at Apple stores. They can easily increase or decrease capacity because they don’t have any physical checkout aisles. This allows for flexibility by just adding or removing salespeople to the store with their mobile checkout devices. 

Additional Resources: For more information on managing lines check out this quick overview from FiveThirtyEight. For more on Cloud Computing, take a look at Google Cloud Platform training or Amazon Web Services training. You can audit classes for free.