Python for .NET Developers Transcripts
Chapter: Deploying Python web apps
Lecture: The cost of cloud hosting compared
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0:00
Let's talk a little bit about the benefits of deploying directly on Linux and the choices that we're making here. I told you about some, the features
0:08
how you're going to learn basically more if you do all the steps and then you can roll it back to use some platform as a service. The way I see it
0:15
there's, like, two really good getting started places. We have DigitalOcean and we have Linode. And these places are super affordable, super flexible.
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They have tons of data centers. They're really, really good options. There are certain circumstances where deploying on Azure
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or deploying on EC2 makes more sense. If your company's all in on those, fine. Let your company foot the bill. But if you care about the price
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and you care about the flexibility you probably want to come over here. So we'll look at those options. Linode's a great option.
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We're not going to deploy to it just because I have more experience with DigitalOcean. Another good option in addition to Azure and AWS is Heroku
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and it's very common in the Python world. You can create one of these Heroku dynos which is basically a little virtual machine app hosted app thing.
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It's not a dedicated virtual machine that you get but you can, like, run and scale it and so on. Pretty cool.
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It's super easy to get started with Heroku. Like I said, if you want to get done let's see, we go over here. So once you're in if you have a git repo
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you can just type, once you have the API command line interface installed just type Heroku create
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and that will set up another endpoint for your git repo. And then to deploy you simply do a git push Heroku master
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and that does it. And it does all this cool stuff. You can see it actually gets all the bits gets it running, and then boom
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there it is off and deployed. You can even scale it. That's super. So the challenge here with this is it's kind of expensive.
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So you pay for this tradeoff, right? If you want to run those, that sort of code here's a passable minimum web instance, right? This one is $25.
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This one is probably what you really need and the M&L change prices there, as well as those, right? So these can get pretty pricey pretty quickly.
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And then you don't directly get to put databases there. You've got to, you know, like use the Postgres as a service which also adds on to features.
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So you don't have a ton of control and you get sort of bought in deeply to kind of, like a lot of commitment over here. A lot of people love Heroku.
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I told you why I'm not particularly using it here, right? You totally do what you want. Let's look at DigitalOcean. Okay, so DigitalOcean is great.
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They let you create virtual machines. They have awesome networking. Lots of data centers throughout the world. They have load balancers.
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They also have Kubernetes and hosted Postgres and stuff if you want to use it but you don't have to. But, so let's check this out.
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Let's go to pricing real quick. So let's go to compute real quick here. So we have some nice options. Here's some shared CPU
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but dedicated virtual machines that you can run into or you could get dedicated CPUs if you really want to go bigger. So here, check this out.
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We've got, like, two gigs with one CPU and two terabytes of traffic and a 50 gig SSD for $10 a month flat. That's pretty interesting. That's good.
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Let's go over here, like, to the Azure calculator. I'm going to choose Azure 'cause I'm guessing
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that a lot of folks who are .NET developers are familiar or considering or whatever something like that. So let's say we want a virtual machine
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we're going to add that and we cannot forget about bandwidth because that's a super important consideration.
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Let's go over here and say we're going to run Linux. I don't really think it changes the price here.
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Yeah, we'll go, I guess we could go with a low priority. We'll go with that character right there. I don't really know all the options that well
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but let's just say that this one it's pretty close to this option that I pulled over here. It's not two gigs, but it's pretty close.
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1.75. Let's say that's good enough. And this is the time for one month. So it's $8 and 76 cents versus $10. Oh, well, why don't we pick this?
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Maybe this is a great option. Well, let's go down to the bandwidth side of things. Did you notice over here
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that this comes with two terabytes of free bandwidth? Do you know how much two terabytes of bandwidth costs over here? Well, let's put two in there.
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Oh, 177 additional dollars. So we go down to our total. Our total is now $186. When it looked like, oh
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this one is actually $150 more expensive than the other one. No, it is not. Not in practice. I find, like, EC2 has the same type of pricing.
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It seems great until, like you start to put all the pieces together and you're like, whoa this is super pricey. And you might say, well, Michael
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who's going to need two terabytes? That's ridiculous. Well, let me just show you over here. I pulled up the price on my system.
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So right now I have eight servers doing a ton of stuff. So running the Talk Python to Me podcast running the Python Bytes podcast
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running a whole bunch of little services behind the scenes and running the training websites and the only thing not accounted for in DigitalOcean
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is the video streaming. That's completely separate, okay? Completely separate. So the video traffic doesn't count here
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but MP3s, HTML, XML all that kind of stuff shows up here. And because I'm paying for those eight servers I have some high end ones.
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We're paying $83 so far this month and it's mostly, it's close to the end of the month, okay? So, say two thirds of the way through the month.
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Now check this out. If we scroll down a little bit oh yeah, here we are. So, up to the 22nd. We can break this out into the charges.
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So droplets are 75 and I have, like, some backups and other stuff going on. So it's 75 bucks. But look at this. Look at that number. That's crazy.
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Remember, this is not videos from the courses. This is not videos. Now, last month we used 14 terabytes of traffic without videos.
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And how much did we pay? A little bit less than $100. Let's go back here and adjust this for, like, my situation
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'cause this is the two you got for free. Over here, we said actually we're not going with this minimum one.
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I've got, like, this is probably running about that's probably what I'm running over there. And I have eight of these.
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So 140, which doesn't look that bad until you add in the bandwidth of 14 to 15. And now what's our subtotal? Subtotal is $1,455.
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Last month at DigitalOcean, I paid under 100. That is 14 times more to do the same over here. And if I went to EC2, it's the same.
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You know, slightly different but the pricing is almost the same. That's why I recommend you try something like DigitalOcean
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or Linode or something like that if you're going to be doing a decent amount of traffic or they're just, they're really nice, as you'll see.
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So I wanted to share some actual concrete experience. I know other people may be having wonderful experiences with Azure
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and maybe you've had a bad experience with DigitalOcean or Linode or something like that and that's fine. You know, take that into account.
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But my experience is basically what I laid out here for you. For that reason, we're going to go with DigitalOcean or something like Linode.