Links:

• Unconventional Guide to AWS Cost Management: https://www.duckbillgroup.com/resources/unconventional-guide-to-aws-cost-management/
• Migrate from Oracle to Amazon Aurora: https://aws.amazon.com/getting-started/hands-on/migrate-oracle-to-amazon-aurora/

Transcript

Corey: This episode is sponsored in part by LaunchDarkly. Take a look at what it takes to get your code into production. I’m going to just guess that it’s awful because it’s always awful. No one loves their deployment process. What if launching new features didn’t require you to do a full-on code and possibly infrastructure deploy? What if you could test on a small subset of users and then roll it back immediately if results aren’t what you expect? LaunchDarkly does exactly this. To learn more, visit launchdarkly.com and tell them Corey sent you, and watch for the wince.

Pete: Hello, and welcome to the AWS Morning Brief: Fridays From the Field. I am Pete Cheslock.

Jesse: I’m Jesse DeRose.

Pete: We’re coming at you again with some more listener questions from the Unconventional Guide to AWS Cost Management. I’m excited. People are listening to us, Jesse.

Jesse: This is fantastic. I’m really excited that we have one fan. I’ve always wanted one fan.

Pete: Well, two fans now. Maybe even more because we keep getting questions. And you can also be one of our Friends of the Pod by going to lastweekinaws.com/QA. And you can give us some feedback, you can give us a question and, like, will totally answer it because we like Friends of the Pod.

Jesse: We may or may not enter you into a raffle to get a Members Only jacket that’s branded with ‘Friends with the Pod.’

Pete: We should get some pins made, maybe.

Jesse: Ohh…

Pete: I think that's a good idea.

Jesse: Yeah.

Pete: So, what are we answering today, or attempting to answer for our listener, Jesse?

Jesse: So today, we’ve got a really great question from [Godwin 00:01:20]. Thank you, Godwin, Godwin writes, “I truly believe that the system that I support is, like, a data hoarder. We do a lot of data ingestion, we recently did a lift-and-shift of the system to AWS, we use an Oracle database. The question is, how do I segregate the data and start thinking about moving it out of traditional relational databases and into other types of databases? Presently, our method is all types of data goes into a quote-unquote, ‘all-purpose database,’ and the database is growing quite fast. Where should I get started?”

Pete: Well, I just want to commend you for a lift-and-shift into Amazon. That’s a Herculean feat, no matter what you’re lifting and shifting over. Hopefully, you have maybe started to decommission those original data centers and you don’t just have more data in twice as many locations.

Jesse: [laugh]. But I also want to call out well done for thinking about not just the lift-and-shift, but the next step. I feel like that’s the thing that a lot of people forget about. They think about the lift-and-shift, and then they go, “Awesome. We’re hybrid. We’re in AWS, now. We’re in our data center. We’re good. Case closed.” And they forget that there’s a lot more work to do to modernize all those workloads in AWS, once you’ve lifted and shifted. And this is part of that conversation.

Pete: Yeah, that’s a really good point because I know we’ve talked about this in the past, the lift-and-shift shot clock: when you don’t start migrating, start modernizing those applications to take advantage of things that are more cloud-native, the technical debt is really going to start piling up, and the folks that are going to manage that are going to get more burnt out, and it really is going to end poorly. So, the fact you’re starting to think about this now is a great thing. Also, what is available to you now that you’re on AWS is huge compared to a traditional data center.

Jesse: Yeah.

Pete: And that’s not just talking about the—I don’t even know if I’ve ever counted how many different databases exist on Amazon. I mean, they have a database for, at this point, every type of data. I mean, is there a type of data that they’re going to create, just so that they can create a database to put it into?

Jesse: Wouldn’t surprise me at this point.

Pete: They’ll find a way [laugh] to come up with that charge on your bill. But when it comes to Oracle, specifically Oracle databases, there’s obviously a big problem in not only the cost of the engine, running the database on a RDS or something to that effect, but you have licensing costs that are added into it as well. Maybe you have a bring-your-own-license or maybe you’re just using the off-the-shelf, but the off-the-shelf, kind of, ‘retail on-demand pricing’ RDS—I’m using air quotes for all these things, but you can’t see that—they will just have the licensing costs baked in as well. So, you’re paying for it—kind of—either way.

Jesse: And I think this is something also to think about that we’ll dive into in a minute, but one of the things that a lot of people forget about when they move into AWS says that you’re not just paying for data sitting on a piece of hardware in a data center that’s depreciating, now. You’re paying for storage, you’re paying for I/O costs, you’re paying for data transfer, to Pete’s point, you’re also paying for some of the license as well, potentially. So, there’s lots of different costs associated with keeping an Oracle Database running in AWS. So, that’s actually probably the best place to start thinking about this next step about where to get started. Think about the usage patterns of your data.

And this may be something that you need to involve engineering, maybe involve product for if they’re part of these conversations for storage of your product or your feature sets. Think about what are the usage patterns of your data?

Pete: Yeah, exactly. Now, you may say to yourself, “Well, we’re on Oracle”—and I’m sure people listening are like, “Well, that’s your problem. You should just move off of Oracle.” And since you can’t go back in time and undo that decision—and the reality is, it probably was a good decision at the time. There’s a lot of businesses, including Amazon, who ran all of their systems on Oracle.

And then migrated off of them. Understanding the usage patterns, what type of data is going into Oracle, I think is a big one. Because if you can understand the access patterns of the types of data that are going in, that can help you start peeling off where that data should go. Now, let’s say you’re just pushing all new data created. And we don’t even know what your data is, so we’re going to take some wild assumptions here on what you could possibly do—but more so just giving you homework, really—thinking about the type of data going in, right?