Cloud Computing Overview: Part Two

listened to that, go check that out. It is a bonus episode. This is also a bonus episode. I am in Las Vegas, Nevada. Since that's the correct way it's pronounced, I've learned, and I am covering Sweet World eighteen. It's a big cloud computing conference held by net Sweet and so as part of that, I thought I would do a couple of episodes about cloud computing, and in this one, we're going to look a little bit more into what

cloud computing can do these days. Turns out it is a big, big business, a multibillion dollar business these days, and I'll talk a little bit more about that and uh enjoy So the ability to connect computers together also gave rise to computing models similar to cloud computing. For example, there's cluster computing. That's where you couple lots of different machines together to work as a unified system. Typically, I

mean the coupling can be loose or tight. It doesn't really it doesn't necessitate tightly coupling machines together, but frequently that is the way it's done. And often these machines are all in the same location, so they may all be in the same data center. Clusters just tend to be more tightly connected than other computer models. So there's also grid computing. Grid computing is less tightly coupled than

cluster computing. You may have computers that are part of this grid in remote locations there and nowhere close to each other, and they're all working together to solve various problems. But typically they're working kind of the way a multi core processor works. And by that I mean that the various computers in the grid are working on different parts

of a problem. You could have the problem divide it up into various segments, and the various grid computers are working on each of them are working on a segment of that problem. This you can see examples of this, and things like the various at home projects like folding at Home or set at Home that use user computers as uh as units in a grid computing system to solve very difficult problems that would normally take a supercomputer ages to complete if it were working on it just

by itself. So both cluster computers and grid computers, both of those models are sort of like virtual supercomputers because they are grouping the assets of various regular powered machines together to make it more than what it was, so you can create kind of a virtual supercomputer now. In Professor Ramna Chilapa at Emory University here in Atlanta described cloud computing as a method that would be defined not

by technological limits, but rather by economic factors. So, in other words, the professor was saying that the costs associated with scaling processes would make it imperative for businesses to offload that burden by making use of cloud computing providers, and that this would in turn create the opportunity for such providers to kind of coalesce and become the partner

these companies needed to grow and do work. In other words, he was saying the economic environment out there is such that there is a need for services that can provide these sort of cloud computing processes and storage. Uh So, because there's a need, sooner or later, they're going to be businesses filling that need. It's it's like nature of

whorring a vacuum kind of concept. So cloud computing isn't just about technology but also the bottom line, and that should not come as a surprise since many factors that we frequently associate with technological advances are actually tied closely

to economic factors. For example, Moore's law, which we frequently simplify by saying processing power doubles every two years or so, was originally an observation about how economic factors would drive the necessity to develop a means to double the number of transistors on a square inch of silicon substrate. In other words, money makes the world go round. In Evan

Goldberg founded a company called net Ledger. The company was offering up software as a service, which means it's a good time to tackle a few common buzzwords associated with cloud computing. I'll get back to Mr Goldberg in just a minute. Now. For one thing, you'll find a lot of as a service buzz terms associated with cloud computing. Software as a service is a big one that is also known as S A A S, with both s as capitalized in the lower A the as in lower

case UM. And this model, you don't sell software packages to a customer. Instead, you set up essentially a subscription service so that the customer can access the software. You maintain ownership of the software itself. You as the provider. You own the software. You're not selling instances of it to people. You provide access to the software in return for money. Then there's platform as a service that's P A A S. Again the P and the S or upper case the a's or lower case. That's the case

for all of these as a service buzzwords. With platform as a service, you create a virtual platform for the customer for the purposes of developing programs or apps. So developers use the virtual platform them when creating whatever app they're working on at the time, and it can serve as a place where developers share tools and processes to

help speed up development. There's a variant of this called mobile back end as a service that, as the name suggests, performs the task of being the back end operations of a mobile application. But this is all about creating the tools the developer needs in order to create and test and then deploy the software they are making. Next, you've got the infrastructure as a service or i a a S. This is even more robust than the platform as a service,

and it's really meant for businesses for enterprises. So let's imagine that you start your own business and you're making toys, and you start out small, maybe you're even working out of your own home, and you're doing all of this by hand. But your business grows, your demand increases, and you are physically incapable of meaning that demand all by yourself. So you need to scale up operations. And this kind of starts slowly. You know, at first it's not too hectic.

You can hire on some people and take on that responsibility. But if demand continues to increase, you have to take the next step. You have to start forming relationships with factories to make your toys. And this is both to increase the supply as well as to reduce the cost. By producing them in bulk, you can reduce the cost on a per unit basis to produce and also still meet the demand that your customers have. You have to

manage supply chains. Though you have to make sure all the components you need to make your toys are getting to the factories. You have to figure out how to get the manufactured toys to retailers or to customers. You have to manage all the money that's involved in those transactions, whether it's payments to services like the factories or accepting payments from customers. And for some businesses, this becomes a

barrier to growth because it's so overwhelming. The transformation of small company to mid size company or mid size company to large company can be really daunting. So the lure of infrastructure as a service is that companies that have already designed systems, usually suites of programs that streamlined various processes, will share that knowledge and capability with you for a price.

So you pay a subscription and then you get all access to all these tools that may help you do things like track your supply chain, to track production and even see how things have changed over time. Like there are some very sophisticated programs out there that allow you

to get very granular with data. Data analysis is a huge part of cloud computing services because it provides another value to the customer if you can say, not only will we show you what the UH you know where you are at any given time, will show you trends and will even start to predict risks that might be in place, like maybe we see that because of this one element in the supply chain, you're going to have a bottleneck in the manufacturing process, which might mean you

need to be able to communicate out to customers that there's currently a shortage of whatever the product is and that you will be turning this around as soon as you can. Or it might even be something about how producing UH your product in one region might be more economically viable than another region, even within the same country, so that you can get your products to market with

a lower cost, not just economic, but environmental. It could be something as as UH intrinsic as how many miles have to be traveled in order to get your product to market. So it gets really really complicated, and you can see how if you're running your own business, once you start layering on these different considerations, it rapidly gets outside of most people's comfort zone, so that that's kind

of the selling point for infrastructure as a service. There's a more recent off ring that's called function as a service or f a a S. This creates a level of abstraction between the developer and virtual machines, so that developers only have to worry about creating very narrowly functional blocks of code, and essentially they're just creating the instructions that sit on top of this service, and the service

does everything else. Like it removes the necessity to program for a specific stack of technology, so the developer just has to worry about the code that he or she needs to do whatever it is they want to do. And typically this kind of service executes upon a real world event happening. So something happens in the real world that triggers the function, and the function then gets executed

by this service. So an example it would be, let's say you go to a website and there's a form you want to fill out in order to get access to something. So you fill out the form, you can complete it, and you submit it. That submission could be the real world event that then triggers this function, this hypothetical function I'm making up now. Unlike infrastructure as a service that's a perpetual model that means you have to keep paying a subscription for as long as you are

relying upon that infrastructure. It is a day today thing. Function as a service typically only triggers a fee whenever the function itself gets triggered, so you're not paying every single day for this thing to exist. You're paying only when people are using it, which means that you can save money if it's not something that people are going crazy and using all the time. If it is, then maybe you have to look at a different model for

economic purposes. But in general, it means that you can save a lot of money this way because it's very lightweight. It just exists on the top of the provider's services. Now there are other service models out there. I'm getting really tired of saying the word service, but it's that's just the term used. So there's storage as a service, that's what sounds like. That's your online document databases or photo albums or file storage or whatever. There's also video

as a service. There's compute as a service. There's probably half a dozen more, but it all comes down to the concept of someone else running a process on lots of computers. You pay that someone a fee to make use of those assets, and it frees you up from having to build out your own massive computer system. Hey guys, before we go any further, I need to take a quick break to thank our sponsor. Let's get back to

net Ledger and Evan Goldberg. The company ran accounting software that had a web enabled user interface, so customers could pay to use the service over the Internet rather than purchase a full software package and installed on their own machines. And one of the selling points of this approaches there's

never a need to upgrade your software. And by that I mean if you buy a software package, like a conventional traditional software package, chances are sooner or later there's going to be an updated version coming along, which creates a lot of pressure on customers. So do you upgrade to the latest version? If so, you probably have to

spend more money to do it. If you don't upgrade to the latest version, you might find that some of your data you work with becomes incompatible with your older legacy systems because it's meant for the newer versions of the software. So there could be features that the newer version has that your old version does not have and it doesn't support, and so you start running into compatibility issues.

But with software as a service, the provider makes all the upgrades to the service on their end on the on the back end, So you're accessing the software through the Internet, whether it's through the web or through an app, whatever it may be. You don't have to worry about installing upgrades or patches necessarily. I mean sometimes you do, but that's what the app world. If you're talking about web browsers, you typically don't. So all you're doing is

just accessing the service. All of the upgrades are being done behind the scenes on the provider side. So one of the benefits of this model is that you always have access to the latest version of the service as long as you remain a customer. Net Ledgers features grew the company evolved into net Suite, which better indicated that

the company was offering up multiple internet based services. A short time after Goldberg found a net Suite, there was another cloud based services company that popped up called Salesforce dot Com. The founders of salesforce dot Com included one former Oracle executive named Mark bennie Off and three software developers named Frank Dominguez, Parker Harris, and Dave Mollenhoff, who

had come from Left Coast Software. Their first product was a type of sales automation software, and Salesforce rapidly gained attention as it was offering up enterprise level services over a relatively simple web based interface. The company became incredibly successful and was able to weather the dot com crash and grow into a multibillion dollar global company. Net Suite also made it through the crash and became a much larger organization over time, and in two thousand and sixteen,

the company was acquired by Oracle. I'll talk more about both net Suite and Oracle in upcoming episodes. But in two thousand two, Amazon made a move to maximize company efficiency. The standard practice at the time was to have enough capacity, like computer capacity, to do your work while only using ten of your capacity. But that's not very efficient. It means that nine cent of your computer capacity goes unused, and so Amazon began to explore other options that would

allow them to leverage that. The answer turned out to be cloud storage and cloud computing, and in two thousand six they expanded this by introducing Amazon Web Services, which had a whole bunch of different web based services that companies can use, including mechanical turk so quick side note about Mechanical Turk because I just love this story. So Amazon markets it as a tool that allows customers to leverage human intelligence for specific tasks because humans tend to

be better at certain things than computers. And by better, I mean we can do that particular type of work much more quickly and reliably. But it can be expensive to hire humans to do those tasks, especially if the tasks are very simple, and if you only need people for a short amount of time, then hiring a huge workforce, a temporary workforce, that's that's an an enormous expense, and not just money, but also in time. And so Amazon

Mechanical Turk is an on demand workforce service. It's kind of like a group of people employed by Amazon to do whatever it is you need them to do with your human task issues. And then then once that's, once that projects done, they go on to do something else. And it sounds a little creepy if I'm being totally honest, But the reason why I wanted to talk about them was because of what mechanical Turk is a reference to.

It's actually referencing an old piece of clockwork chicanery. The original device was called simply the turk, and it appeared to be a clockwork automaton that had the figure of a turk sitting at a chessboard. It was made by a guy named wolf Gang Fawn Kimberland. He built it in the late seventeen hundreds, like in the seventeen seventies, and upon casual glance you would think it was a robot of ingenious design, capable of defeating even skilled players

in chess. But in reality, there was a human being hidden within the cabinet of the machine who was guiding the turk's movements, and a playing chess against a human opponents. So really it was just two humans playing chess, only one of the humans was hidden out of sight. Just I love that story, so I wanted to tell it quickly. Around the same time the Amazon was introducing web services, Google debuted Google Docs, which was actually based off two

earlier products. One of them was Google Spreadsheets, which Google acquired. They bought it from a company called two Web Technologies, and they also acquired a company called Rightly that ended up being the basis for the Google Docs part, the actual document offering of the product. How those moves began to bring cloud computing into the world of the home

user for the first time. Earlier implementations were almost completely focused on business to business operations, which means most of us never see it right when we talk about business to business stuff, it's interesting because it tells us how the stuff we interact with, how that happens, how it gets done in the background, but we don't see it directly.

That's why when we talk about companies like IBM, most of us have very little experience working directly with IBM products unless it's within the realm of the office, because IBM doesn't really make products for the home consumer. The same sort of thing here was that cloud computing for the longest time was not for the home consumer. It was for businesses. But with the emergence of these kind of applications, we were starting to see people get access to that sort of stuff for the first time in

a big way. And that's when it became necessary to figure out how to explain that technology to people. And that's when cloud computing really became a buzzword, and also how I came to write sixteen articles about the stuff. These days, many companies are involved with cloud services, along with net Suite and Salesforce there's Amazon, Google, Microsoft has its Azure platform, IBM is a big one, and there's tons of others. And the services being offered by these

companies have grown significantly over time as well. For example, i EM offers you the chance to work on a quantum computer over the cloud, which still blows my mind. We got just a bit more to talk about with cloud computing, but before I get into it, let's take another quick break to thank our sponsor. One thing I feel we should talk about is the different types of cloud computing models. And I almost said different types of clouds, but I need to be more serious. That's a cloud joke.

One type is the public cloud model. Now, these are services in which all the assets are run by a third party. So I talked about Google Docs. That's a great example of a public cloud computer model. So if your company relies on Google Suite for all of its processes, really, then you'll be relying on a public cloud. Then you've

got private clouds and those models. The company itself, whatever company it is that's running the processes, it actually owns all the equipment and the services that run on that equipment. So let's say you work for a company ABC, The private cloud is also owned by ABC, and it's got all these different data centers and they're running all these processes. So you're still accessing apps and programs and storage that exists on other computers. It's just that you work for

the same company that owns those computers. It's not owned by a third party. Now, you would want to use the private cloud approach if you had mission critical applications that you wanted under your full control and you didn't want to entrust that to a third party. So if you're handling really sensitive information or the processes you rely upon, or really big trade secrets, that might be the way

you want to go. Or if your needs are just so particular that there's not really a provider out there that can meet your needs because they're so different from what everyone else needs, this would be the way you would go. There's a third model called the hybrid cloud that merges those two. You have both public and private

cloud entities. So a company with a hybrid cloud approach would have a public cloud stuff to do to handle certain tasks, private cloud to handle other tasks, and as you might imagine, the more critical elements to the company's operations would probably run on the private cloud, while more mundane processes might be pushed to the public cloud service, and there's some sort of layer of communication and automation that allows for the exchange of data between those two

clouds in a controlled manner so that the output from one can work with the information on the other. In fact, without that communication channel between the two clouds, you do not actually have a hybrid cloud. You would instead have what is called a multi cloud approach. You would have two distinct cloud services that do not communicate with each other. And there are valid reasons to go with a multi cloud approach where there is no communication between clouds. So again,

let's talk about a really big company. Really big companies could have departments. They're so large and have such specific needs they do not need to communicate directly with other departments to get their their work done. Their their work may not relate directly with other departments, so in those cases it might make more sense to have a separate public or private cloud available to those departments either, so you can have multi cloud approach that uses either private

or public or both. The important element here is that there isn't that communication channel between them. So as companies grow they often find that the departments inside them end up being larger than the original company was when it first got started, and at that size, finding processes that

work and scale is critical. Now, at the top of the show, I mentioned that one of the big concerns about cloud computing was security, and with so many companies in trusting data and processes to third parties, security is an absolute necessity without a company would go out of business. Third parties would collapse if they were found to be insecure, and like I said, that could create a domino effect,

a disastrous result among the third party's customer base. So typically cloud computing applications rely upon profiles that require authentication through some means, most commonly through a user name and password. There are cloud based services that actually managed this as well. It's called identity as a Service or i d a a s NOW. Those services and not only managed user log in information, but can designate different levels of access.

So for example, the head of a department might need administrator level access to that department's data, while an employee further down the organizational chain might only require limited access. So you need to have a way of denoting that so that you don't have some low level employee suddenly have access to say, everyone's pace stub. That would be bad. Cloud providers take security seriously and it shows because they

might prove to be attempting target to hackers. But the big providers of technically been more resilient to attacks than private enterprise centers have been in the past. The weak spot tends not to be the data centers or the providers or the security around them, but rather that tenuous link between provider and customer. It's that old problem where you find out that the weakest link in the security

system is the people. It's always the people, because people might choose really bad passwords, which creates a security vulnerability that's difficult to protect against. You might use something like two factor authentication to help fight against that problem. That can help. That's where a person needs not only a password but some other form of authentication like a physical

token in order to access the services. And at that stage and an authorized person would need to get hold not just to the password, but also of some sort of physical object a token or a cell phone or something that the target owns. So it doesn't eliminate risk, but it cuts down on it significantly. There are a lot of other buzzword like topics that tie in with cloud computing. There's big data that's all about how to leverage the huge amounts of information that's being mined on

a daily basis. How do you do that in a way that's meaningful and efficient. That's frequently associated with cloud computing. Artificial intelligence and machine learning also get thrown into the mix. There are services that use machine learning to sort through big data on the cloud, for example. That way you get a big, heaping handful of buzzwords all at once, that's all in an effort to produce a particular result. Sometimes you use machine learning and big data for legitimate

research purposes that can further our scientific understanding. Sometimes it's for less lofty reasons. It might be to find the best way to advertise to different groups of people in order to more effectively sell products to them. Sometimes you can get downright creepy, which as the recent Cambridge Analytical story. Have to do a full episode about what that was all about. Why raised such a fuss at some point,

But that's that's for another time. It's a complicated issue that I can't just if I ran into it here, we would easily go another hour, and UH actually have to be at the conference keynote in a little bit,

so I can't do that now. At the top of the show, I also mentioned that there can be an issue about ownership, like who owns the data on these services, and usually there's some pretty complicated terms of service that lays all this out, where you're essentially granting a license to the third party to have a sort of physical

possession of all that information. And the reason that's necessary is because the way cloud computing works, the way you can access it through different devices and in different places, you have to give the company permission to be able to show that information. So if I store a file on my personal computer and I'm the only one who has physical access to my personal computer, I'm reasonably assured

that I'm the only person who can see it. There's no real permissions that need to be made or anything like that. If I'm storing my data on someone else's machine and I want it to be clear that still my data even though it's sitting on someone else's machine, then we have to draw up these agreements. And one of those agreements might be well, if you request to see and work with this data, I need to have

the permission to actually serve it to you. If you choose to share it with someone, I have to have the permission that allows me to share it so that I'm not legally responsible If you later on say, oh I didn't I don't want that person to have it. Well, if you chose to share it, by the nature of the cloud computing model, then you know that that's what happened,

that it got shared. So it's largely to protect the third party providers, but it's also just this very complicated language that gives them the permission they need to do the business as they do it. So it can get pretty complicated. On casual glance, it looks like you're signing over all your data to another party, um, and you're not really doing that, at least not in most agreements. Any ethical agreement would not include that sort of information

in it. But that's pretty much the overview of cloud computing. Will conclude our story on that. It's a fascinating model that has its roots all the way back in the early days of of of mainframe computers. I hope you found this episode helpful and understanding what the heck that buzzword meant in the first place. If you have suggestions for future episodes of tech Stuff, whether it is to explain something within tech, to talk about a specific technology

or a company or a person in technology. Maybe you have someone in mind that I should interview or have on as a guest. Reach out and let me know. You can send me and email the addresses tech Stuff at how stuff works dot com or draw me a line on Facebook or Twitter. The handle for both of those is text stuff hs W. Follow us on Instagram. We've got an Instagram account that we post to regularly, so check that out. And remember, on normal weeks, I

record this show on Wednesdays and Fridays. You can actually watch me record it live in the studio. You can just go to the link Twitch dot tv slash tech Stuff. You'll see the schedule there, and there's a chat room and everything. You can join in be part of the crowd. And I look forward to seeing you and I'll talk to you again really soon. For more on this and bouthands of other topics, is it how staff works dot com