BYTE the Cloud

Chris 0:00
Hey everyone, welcome back to another deep dive. Today we're taking a closer look at AWS Compute Optimizer. Yeah, a

Kelly 0:06
very useful service if you're trying to keep your AWS bill under control,

Chris 0:09
exactly. I mean, if you're a mid level cloud engineer like yourself listening, you already know how quickly those costs can get out of hand if you're not careful, definitely you got to stay on top of things. So that's what we're going to do today, dive deep into this AI assistant that helps right size, your EC2 instances, your Lambda functions, even EBS, volumes.

Kelly 0:29
It's amazing how much this service can do. Let's jump

Chris 0:32
right in. For those who haven't used it, what exactly is Compute Optimizer.

Kelly 0:36
So it's all about helping you get the most out of your resources, performance wise and cost wise, both. It's this AI powered tool that studies how you're using your resources in AWS, you know, things like EC2 and

Chris 0:49
Lambda, okay. So like, how much CPU are you actually using?

Kelly 0:52
Exactly CPU, memory, all those metrics. Then, based on all that data, it comes up with suggestions for the best configuration. So

Chris 0:59
it doesn't just tell you to downsize everything to the smallest instance possible.

Kelly 1:04
No, it's way more sophisticated than that. Like it knows that a web server needs a different setup compared to a database server. It factors in what you're trying to do with the resources, right? And what your budget is and even your performance goals. Okay, that

Chris 1:16
makes sense. So do you have any real world examples of like, how Compute Optimizer helps someone save money?

Kelly 1:22
Oh, tons. I remember this 1e, commerce company, their cloud bills were through the roof. They were just, you know, racking their brains, trying to figure out why. That's familiar. They brought in Compute Optimizer, and it found all these instances that were way bigger than they needed to be, just sitting there using hardly any resources. They were over provisioned exactly, and Compute Optimizer recommended downsizing them. They actually ended up saving a whopping 20% on their EC2 costs, 20%

Chris 1:50
that's incredible. Did their website like crash or something? No, no

Kelly 1:55
performance issues at all. They were actually surprised. Some things even got faster because they were on more suitable instances.

Chris 2:02
So, win, win. Okay, we've established Compute Optimizers, pretty great, but let's get more into the details. Sure. What kind of recommendations does it actually give you? Okay,

Kelly 2:10
so there are three main types, instance, type recommendations, right sizing recommendations and custom recommendations. I'm

Chris 2:19
already a little lost. Yeah, it

Kelly 2:20
can be a little confusing at first. Basically, they're all trying to optimize your resources, but they just go about

Chris 2:25
it in different ways. Gotcha. So explain instance type recommendations. Okay, so it

Kelly 2:30
analyzes your application, looks at things like CPU, memory, network usage, and then it recommends which instance family and size would be the most cost effective, like maybe it'll suggest switching from a c5 to an f5 instance. You know if your app needs more memory. So it's

Chris 2:49
not just about the cheapest or smallest instance. It's about picking the one that really matches your apps Exactly. So what about right sizing recommendations?

Kelly 2:58
Those take it a step further. They look at your utilization targets. So let's say you want your instances to run at around like 70% CPU on average. Compute Optimizer will analyze everything and recommend an instance size. That'll keep you around that 70% but also keep your costs down

Chris 3:14
so you get the performance you want without paying for stuff you don't need. Exactly. It's like finding that sweet spot makes sense and then custom recommendations, those give

Kelly 3:24
you more fine grained control. Like, if you have an application that absolutely positively has to have the best performance possible, even if it costs more,

Chris 3:32
or maybe you have specific compliance requirements, right, you can define

Kelly 3:36
your own parameters and really customize the optimization. That's pretty

Chris 3:39
cool, yeah, but this all relies on data. How does Compute Optimizer actually gather all this information about my workloads? It's

Kelly 3:48
all about the metrics. It uses all sorts of data points from different AWS services for EC2. It's things like CPU utilization, memory pressure, network throughput and disk IO. And it integrates with CloudWatch too. Speaking

Chris 4:01
of CloudWatch, yeah, how does Compute Optimizer work with other AWS services? I mean, it can't just exist in a vacuum. You're

Kelly 4:08
right. It doesn't. It's all connected, like if you're using Auto Scaling groups, Compute Optimizer can recommend the best instances for that group so that you're scaling efficiently Exactly. And it works with AWS Organizations too. So you can get an overview of all your accounts.

Chris 4:23
Okay, so it's really plugged into that whole AWS ecosystem? Yes, that's super important, especially if you're studying for those AWS exams. But before we get to all that, are there any like limitations we should be aware of? Yeah,

Kelly 4:36
there are a couple. Like one big one is it relies on historical data. So if you have a brand new application or a workload that's constantly changing, Compute Optimizer might not have enough info to give you the best recommendations.

Chris 4:49
So it's not a fortune teller. It can't predict the future, right? It

Kelly 4:53
needs to see some patterns, and even then, it's important to remember that Compute Optimizer is a tool, not a replace. Meant for good

Chris 5:00
architecture. It's not going to magically fix a poorly designed application exactly.

Kelly 5:04
You still need to understand your application's needs and how much performance you need and what your budget is. So basically, use

Chris 5:10
your brain. Yes, think

Kelly 5:13
critically. Don't just blindly accept every recommendation.

Chris 5:17
Okay, so we've got a good handle on what Compute Optimizer is what it does, what its limitations are. Now, left shift gears a little bit and think about those AWS exams. What kind of questions could someone see about this on the exam? Well,

Kelly 5:31
the exams really want to make sure you understand how these services work together. They'll give you a scenario, you know, a real world problem, and ask you how to use Compute Optimizer to solve it.

Chris 5:42
So they're not just gonna ask, what is Compute Optimizer? No, no,

Kelly 5:45
it'll be more like you know, you're trying to save money on EC2. What service would you use, or what feature in Compute Optimizer would you use to right size your instances, gotcha.

Chris 5:54
Gotcha. So you gotta know how to use it, not just the name, right they wanna

Kelly 5:57
see you understand how it works and how it can save you money and how those recommendations actually work in a real situation.

Chris 6:04
Sounds tricky. You ready to dive into some example questions? Definitely. Let's do it. Okay, let's start with a common scenario. Let's say a company is freaking out because their EC2 bill is sky high. Oh, yeah, classic. What kind of exam question Could they ask about that?

Kelly 6:19
Well, they could ask something like, which AWS service can help identify potential cost savings for EC2 instances? Okay? Straightforward enough. Or they could get more specific, like, which Compute Optimizer feature analyzes EC2 usage and recommends right sized instances. So you gotta really know your stuff. Yeah, you got to be able to explain why you'd choose Compute Optimizer and what specific feature you'd use. So

Chris 6:45
how would you answer those questions? For the

Kelly 6:47
first one, I'd say something like Compute Optimizer analyzes how you're using your EC2 instances, and can recommend instances that are the right size. I'd also mention that it uses historical data to make sure your performance doesn't suffer.

Chris 7:01
And for the second question, the one about the specific feature, I'd highlight

Kelly 7:05
the right sizing recommendations feature and explain that it looks at how much of your resources you actually read, and then suggest instances that are just the right size, you know, so you're not wasting money. All right.

Chris 7:15
Cost optimization got it. What other kinds of questions could we see? Well, let's think

Kelly 7:19
about performance like, imagine your application's running really slow, maybe because your EC2 instances aren't powerful enough, okay, in there. How would Compute Optimizer help with that? Hmm,

Chris 7:30
well, it could analyze the app's usage and see if the instances are indeed too small, and then maybe recommend upsizing to a more powerful instance type,

Kelly 7:40
exactly. And the exam might ask something like, which Compute Optimizer recommendation type analyzes resource utilization and suggests larger instance types.

Chris 7:49
So again, it's those right sizing recommendations, yep, because

Kelly 7:52
right sizing means getting the size right, whether it's bigger or smaller.

Chris 7:56
Okay, I'm starting to see the pattern here. Let's keep going. All

Kelly 7:59
right, how about this? You're using an Auto Scaling group to manage an app that has like, variable traffic throughout the

Chris 8:05
day. Okay, so it scales up and down automatically

Kelly 8:07
right now. How would you use Compute Optimizer in this situation that's

Chris 8:12
tricky. Auto Scaling is already handling the scaling So what role does Compute Optimizer play?

Kelly 8:19
Well, you want to make sure the instances within your Auto Scaling group are optimized too Right. Compute Optimizer can analyze those instances and suggest the most cost effective and suitable instance types for your specific scaling needs. I

Chris 8:32
see. So it's like Auto Scaling handles the quantity of instances, and Compute Optimizer makes sure each instance is the right size and type exactly

Kelly 8:40
you want both working together. And the exam might ask, like, how can you use Compute Optimizer to optimize both the cost and performance of an app that's using an Auto Scaling group? Okay? So

Chris 8:51
the key is knowing that Compute Optimizer works with other services, like, it doesn't just work in isolation, right? Exactly? Wow. This is making me think about all the different ways Compute Optimizer can be used. I'm starting to feel like an expert. That's

Kelly 9:04
great, but there's always more to learn. Luckily, we have plenty more exam style questions and scenarios to cover in part two of our deep dive.

Chris 9:11
Welcome back. Ready for some more Compute Optimizer brain

Kelly 9:14
teasers always hit me with those exam style scenarios.

Chris 9:17
All right, let's jump right in. Imagine you've got an application with really unpredictable traffic, like a viral marketing campaign or a flash sale, something like that. Okay, I see where you're going with this. Would Compute Optimizer be the best choice in a situation like that?

Kelly 9:32
That's a great question, and it highlights that whole historical data thing we talked about earlier. If your workload is super unpredictable. Compute Optimizer might not have enough info to give you good recommendations.

Chris 9:45
It's like trying to predict the lottery, right? Kinda

Kelly 9:47
Yeah. Compute Optimizer is great when you have patterns, it can analyze, but when things are constantly changing, you might need a different approach, exactly like you might wanna think about using serverless, something like AWS. Lambda that can just scale up and down automatically as needed.

Chris 10:03
So choose the right tool for the job. Compute Optimizer is not a magic bullet, exactly. Okay, here's another one. What about machine learning? You know, those workloads often need specialized hardware, like GPUs. Sure can Compute Optimizer recommend the right instances for that kind of stuff. Oh,

Kelly 10:20
yeah, absolutely. Compute Optimizer knows about all the different instance types, even those specialized ones, like the P family for GPUs.

Chris 10:27
Okay, cool. So it can handle more than just general purpose computing. Definitely, it can analyze

Kelly 10:32
your workload, figure out if you need GPU power, and then recommend the best instance types. So it's pretty

Chris 10:38
versatile. This makes me realize that Compute Optimizer must know a ton about all the different AWS services, right? It's not just a simple cost cutting tool you

Kelly 10:47
got it. It's like having an AWS expert built right in. Speaking

Chris 10:52
of AWS services, how about AWS Organizations? Let's say you're managing multiple accounts for like a big company. How can Compute Optimizer help with that? Well, imagine

Kelly 11:02
having to log into each account separately run Compute Optimizer and then try to combine all the recommendations. It would be a nightmare. Sounds like a recipe for a massive headache. Thankfully, Compute Optimizer works directly with AWS Organizations. You can see all the recommendations and insights for your entire organization all from one place, so you can get a bird's eye view of everything, exactly, much easier to manage. And this is something they might ask about on those higher level exams where you're dealing with multiple accounts.

Chris 11:30
Okay, that makes sense. I'm feeling pretty good about this Compute Optimizer stuff now, but I bet you've got more challenges up your sleeve, of course.

Kelly 11:37
How about this? You've already implemented Compute Optimizer, you're saving money. Everything's going great, but how do you keep it that way?

Chris 11:44
So like, how do you make sure you're always getting the best results from Compute Optimizer?

Kelly 11:49
Exactly? It's not a set it and forget it thing. You got to stay on top of it. Compute Optimizer is always analyzing your usage, so you need to keep reviewing those recommendations and make adjustments if things change. So

Chris 12:02
it's like an ongoing process, not a one time fix, right?

Kelly 12:04
Think of it as a continuous feedback loop. You adjust Compute Optimizer analyzes it recommends you adjust again.

Chris 12:12
Makes sense. Any other tips for making the most of Compute Optimizer?

Kelly 12:15
One thing I always recommend is integrating Compute Optimizer with your existing workflows, like if you're using infrastructure as code, tools like cloud formation or TerraForm, you can bake those Compute Optimizer recommendations right into your code

Chris 12:30
so it's all automated. You don't have to manually do error exactly, and it helps prevent configuration drift, right? Because things are always changing in the cloud. And don't

Kelly 12:39
forget about custom metrics. We talked about those earlier. Yeah, yeah. Those let you really fine tune things. If you have an application with unique performance needs, use custom metrics. Give Compute Optimizer even more information to work with.

Chris 12:51
That's a great tip. All right? Anything else?

Kelly 12:54
One last thing, don't be afraid to experiment. Try different recommendations, different utilization targets, see what works best for your situation. So don't be scared to play around a bit Exactly. Compute Optimizer is flexible. You can tweak it to your liking. Okay,

Chris 13:10
I'm starting to realize that Compute Optimizer isn't just about technology. It's also about a way of thinking, you know, constantly optimizing and improving.

Kelly 13:18
I like that. It's a mindset shift. Now,

Chris 13:21
let's say you're working with a team of developers who are, like, skeptical about letting an AI tool optimize their applications. Ah, yeah, I've met a few of those. How do you convince them to give Compute Optimizer a chance? It's

Kelly 13:35
all about showing them the benefits, proving that it actually works, and being transparent, explaining that it's not some magical black box. It's just using data and analysis to help make better decisions.

Chris 13:47
So like, show them the metrics, the data behind the recommendations, right?

Kelly 13:52
Show them that it's not replacing their expertise. It's just giving them more information to work with,

Chris 13:56
and maybe even let them try it out themselves, right? Yeah,

Kelly 13:59
absolutely. Hands on experience is always the best way to learn. Okay,

Chris 14:03
let's shift gears again and talk about limitations. Remember how we talked about Compute Optimizer needing historical data. What if you're working with a serverless app that uses Lambda and you're seeing some performance issues, would Compute Optimizer be helpful in that scenario?

Kelly 14:18
So you're thinking Lambdas, serverless Compute Optimizers all about EC2 and stuff like that? What's the connection? Exactly? Well, remember how AWS is always changing, always evolving? Oh yeah, for sure, Compute Optimizer has actually expanded its reach to include Lambda functions. Now, really,

Chris 14:35
I didn't know that. So even though it's called Compute Optimizer, it's not just limited to traditional compute resources like EC2,

Kelly 14:43
nope, it can now analyze your Lambda usage and suggest the best memory settings to improve performance. Wow,

Chris 14:49
that's really cool. So even if your app is serverless, you can still benefit from Compute Optimizer. Absolutely it's keeping up with the times. That's a good reminder to always stay up to date with the latest. AWS developments, those exams love to throw in questions about new features.

Kelly 15:04
They definitely do. Ready for another question?

Chris 15:06
Bring it on. My brain is in Compute Optimizer mode now. All right,

Kelly 15:09
let's talk about legacy applications, those apps that have been running on the same old EC2 instances forever, probably costing a fortune to run. Yeah, those can be tricky. How would you approach optimizing a legacy app with Compute Optimizer? Well, compute

Chris 15:26
optimizer could analyze the usage history and see if the instance is way too big for what it's actually doing, and maybe suggest downsizing to a smaller, cheaper instance

Kelly 15:36
exactly give that old app a new lease on life in the cloud. But

Chris 15:39
it's not just about downsizing blindly. It has to make sure the new instance can handle the workload Right, right.

Kelly 15:44
It's all about finding that balance between saving money and maintaining performance. Okay, that makes

Chris 15:50
sense. Now, what about a modern app, something built with microservices? You know you've got EC, two instances, Lambda functions, containers, all working together, sounds complicated. Can Compute Optimizer handle that level of complexity. Absolutely. Compute

Kelly 16:04
optimizer can handle those complex modern applications. It can look at your whole microservices setup, analyze each part and give you recommendations for everything, like right size, your EC2 instances, optimize your Lambda functions, even suggest adjustments for your container.

Chris 16:19
So it's like a one stop shop for microservices optimization. You got it.

Kelly 16:23
It's always evolving to keep up with how applications are being built these days.

Chris 16:27
This is making me realize that Compute Optimizer is more versatile than I initially thought.

Kelly 16:32
Yeah, it's a powerful tool, and that's why it's so important for cloud engineers, and especially for those taking those AWS exams. Speaking

Chris 16:39
of exams, I'm feeling much more prepared for those Compute Optimizer questions now, but I'm sure you have at least one more tricky scenario for us. Of

Kelly 16:47
course, let's wrap up part two with something that's really important in certain industries like healthcare or finance, security and compliance. Okay, yeah, those are big deals. Imagine you're working in a super regulated industry where data security is paramount. You want to use Compute Optimizer, but you're worried about the security implications. How do you approach that? That's

Chris 17:09
a good question. How do you reassure someone that Compute Optimizer is safe to use? You

Kelly 17:14
have to explain that Compute Optimizer doesn't actually access your application data. It's just looking at metadata and usage patterns. So

Chris 17:21
is that snooping around in your sensitive data? Nope, it's all

Kelly 17:24
about those patterns and metrics, and all the data it uses is already within that secure AWS environment.

Chris 17:30
Okay, that makes sense, and you can control who has access to Compute Optimizer

Kelly 17:34
Absolutely. You can use IAM policies to make sure only the right people can see the recommendations and make changes.

Chris 17:40
So it's secure, even in highly regulated environments.

Kelly 17:43
Exactly. You just got to make sure you're following best practices and using those security features. Okay,

Chris 17:48
those were some seriously challenging scenarios. My brain is officially full of Compute Optimizer knowledge now, but before we move on, anything else about Compute Optimizer that we haven't talked about yet that might be on the exam. Hmm,

Kelly 18:00
good question. Let me think, oh, custom metrics. Those again, yeah, remember how we talked about how Compute Optimizer uses built in AWS metrics? Well, you can actually give it custom metrics too, metrics that are specific to your applications. So if

Chris 18:16
you have an app that's doing something unique, you're not stuck with just the standard AWS metrics Exactly.

Kelly 18:22
Let's say your app has this special performance metric that AWS doesn't track. You can create that metric in CloudWatch and tell Compute Optimizer to use it. Ah, that's

Chris 18:34
pretty cool. You can really tailor Compute Optimizer to your specific needs.

Kelly 18:38
Yep. You can even get recommendations based on those custom metrics. Okay, that's

Chris 18:42
a great takeaway. So we've covered a lot of ground here. Talked about all sorts of scenarios, and I feel like I have a much better understanding of Compute Optimizer now we too, but I'm also eager to hear more about how to actually use this in the real world. You know, not just

Kelly 18:55
for exams. Well, you're in luck. In part three, we'll dive into some real world use cases and best practices for implementing Compute Optimizer. So stay tuned. Welcome

Chris 19:05
back to the deep dive. We've spent the last two parts really getting into the nitty gritty of AWS Compute Optimizer, all those AI recommendations, integrations with other services, the whole shebang. But you know what they say, the real test is putting all this knowledge to work. Couldn't agree

Kelly 19:21
more. Let's talk about actually using Compute Optimizer, you know, getting those cost savings, seeing those performance improvements, making it real.

Chris 19:29
Exactly so. Are listeners ready to jump in? Start optimizing? Where do they begin? Is there like a Compute Optimizer for Dummies out there?

Kelly 19:38
Maybe not a Ford dummies guide, but AWS has great documentation and tutorials and beyond that. It's all about knowing what you want to achieve. What's your goal? Are you all about cutting costs, boosting performance? Maybe a bit of both,

Chris 19:55
right? You got to have a target in mind. Once you know what you're aiming for, you can start looking at. All the different features and recommendations Compute Optimizer offers exactly and don't

Kelly 20:04
be afraid to experiment, try different things, see what works best for your apps. Compute Optimizer has got

Chris 20:10
a lot of options, so it's not a one size fits all kind of thing. Nope.

Kelly 20:13
It's more like a toolbox. You pick the right tool for the job. I like

Chris 20:17
that analogy. So as you use it more and more, you start to develop your own best practices. Yeah, you know what works, what doesn't.

Kelly 20:23
Definitely you start to get a feel for how to really optimize things. Okay, speaking

Chris 20:27
of best practices, any tips for our listeners who are just getting started with Compute Optimizer? One

Kelly 20:33
of the biggest ones is to check those recommendations regularly. Don't just set it up and forget about it. Compute Optimizer is constantly analyzing and updating its suggestions, so you gotta stay on top of it.

Chris 20:44
So it's like a dynamic thing, not a static thing, right? Things

Kelly 20:48
change. Your usage changes, so

Chris 20:50
you gotta adapt. Makes sense. What else?

Kelly 20:53
Another important tip is to integrate Compute Optimizer with your existing workflows. If you're using infrastructure as code, tools like cloud formation or TerraForm, incorporate those recommendations right into your code. Ah, so

Chris 21:05
your infrastructure is always optimized, even when you're making changes exactly.

Kelly 21:08
It's like built in optimization prevents things from getting out of whack over time. Smart, Okay, anything else, don't forget about those custom metrics. We talked about how you can feed Compute Optimizer extra information to work with. Yeah,

Chris 21:20
yeah. It's like giving it a secret weapon, right? Yeah. Exactly. If

Kelly 21:24
you have an application that's doing something unusual, something with unique performance requirements, use custom metrics. Give compute

Chris 21:30
optimizer as much info as possible.

Kelly 21:32
Exactly, the more it knows, the better it can help you. And one final tip, don't be scared to experiment. Try different recommendation types, tweak those utilization targets, see what happens. So

Chris 21:45
it's a learning process, really, definitely,

Kelly 21:47
it's all about finding what works best for you. There's no one right answer.

Chris 21:52
Okay, that's great advice. This has been a really eye opening, Deep Dive. I feel like I've learned so much about Compute Optimizer, what it can do, what it can't do me too. It's been fun, but most importantly, I feel like I can actually use it now, put it into practice and optimize my cloud environment, maybe even save some money, exactly. That's the best part. Well, folks, that brings us to the end of our deep dive into AWS Compute Optimizer. We hope you've enjoyed this journey into the world of cloud optimization. Remember, Compute Optimizer is a powerful tool, but it's just one tool. It's up to you to use it wisely. Use your cloud expertise and keep learning, keep improving. The cloud's always changing, always evolving. So stay curious, stay adaptable and happy. Optimizing.