?Well, welcome to Cloud Talk Live. I'm your host, Jeff Diverter, now here at Cloud Talk. We strive to help decode the ever-changing world of technology to help you apply it to your business that hopefully you'll have one more tool in your arsenal to help you improve your business and those around you.

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Now, let's get on with today's show Live from the castle in San Antonio. It's the 2023 Rackspace Solve Cloud Modernization Summit. Sponsored by A W s and now here's Jeff.

Ah, so much fun. Ladies and gentlemen. Welcome to my favorite hour of the quarter. That's right, this is the Q2 Solve Modernization Summit. Uh, here by the the Solve Program folks. My name is Jeff Diverter. I'm the Chief technology evangelist here at Rackspace Technology, and delighted to be with you today.

Holy cow. Do we have a great program set up for you today? If you have been following Rackspace, you follow me. You've seen some videos that talk about what we're gonna do here today. It's all about cloud modernization. Now, each quarter here at Rackspace, we go out and we survey over 1400, 1420 to be exact different IT decision makers in 10 different countries.

Now, that is a lot of people, and in the process of this, oh good, we get to see where people are. I forgot to tell you, introduce yourselves, tell me who you are, tell you where you are, and Daniel or Megan will make sure it gets up to me. All right, so 1,420 different folks that we've interviewed all around the world, all about the single topic.

Of cloud modernization. Now we ask the question mul in a multifaceted way, you know about data, about, you know, what's happening in the compute, what are you, what security challenges do you have? And guess what we found out as in everything else, AI ran to the top of the list. And you may be saying to yourself, Jeff, how on earth, how on earth can AI show up in cloud modernization conversation?

I'll tell you how it showed up. We found out we're gonna pop up throughout the day. Some of this research, you can get all of this for free just over to rackspace.com/solve. Doesn't cost a cent. Uh uh. But we found out that over 90%, that's over 90% of those 1,420 individuals, those it decision makers that AI was absolutely falling into.

There it is right now, uh, into, uh, into this process because it was either impeding them or they realized that they had to go through this process. Before they could actually reap the rewards of the things that AI would would happen. So, so what's, what we find is more and more, there is a greater focus and attention on having successful cloud modernization.

Now, you know, we've been doing this since, you know, cloud modernization since the, of course the cloud showed up. Rackspace was in the business early on. AWS was there super early, huge thanks to AWS who helped us, uh, and sponsored that. Not only the study, but our time here this morning. So we're gonna see a little video from them.

We got some folks here from AWS that we're so grateful for. But even though we have had people who have been going through this process, in fact, we found that, what was it, 80%? Yeah, 80%, uh, of companies. Say that in, in order to, uh, to do this process, they've got legacy applications that are slowing them down.

In fact, they've got to find a way to modernize them before they can leverage the goodness of ai. In fact, even they're saying that even 50% of, uh, of their legacy hardware can't be modernized. Look at that. 50% of the legacy hardware, of those 1400 different companies, those are individual companies, folks, um, uh, they can't go through the process because of legacy hardware.

You know, one way of course to solve that is through a whole process of modernization. That's why we're here today, is to break down that process of cloud modernization for you at Rackspace over the, well, nearly 25 years. It's 24 years, but I like to round up. So quarter century of helping companies utilize technology to get the most out, uh, into their business, uh, is what we've been doing here.

So as we now have been in the business of helping companies since, uh, when was it, 20 15, 20 16, we started helping people into aws. What we found is the, the process of cloud modernization happens in four stages. It starts with advisory services. Next up is transformation. The actual transformation. Then we've gotta manage those workloads that are now in our cloud of choice.

And then lastly, optimization. Those four stages. Now I've got some great guests here today who are gonna take us through that whole process, and it all starts with the advisory services. Now as we get into advisory services, my first guest is the leader for North America for Rackspace, around our professional services offering for advisory services.

So who better to come and kick things off for us here today than Niraj Yadav. So everybody, please welcome Niraj to the stage.

Thank you so much for, uh, thank you so much for coming in and having a little chat about advisory services. Happy to be here, Jeff. Oh, so IT Advisory services, when I have conversations about this mm-hmm. I always say it starts with a conversation, right? Why does it start with a conversation? It all starts with a conversation because it's all about addressing three questions, right?

Mm-hmm. The first question is the why, and then the what, and then the how. Right? And advisory is the tip of the spear in getting those answers. Yeah. And it's important to have those answers upfront because that kind of informs your overall cloud mod modernization journey and your roadmap. Okay. So as we look at the data that, that we found, we found that, I think it's 89% of companies that we surveyed came back and said that they have been in the business of cloud modernization for as many as 10 years.

So somewhere between one and 10 years. But if we look even a little bit deeper in this shows up later in the study, is that, that not everybody's really thrilled with where they are. And you, you led with, with talking about business outcomes Yep. And not talking about a technology outcome. And I think that's really important, which gets us into, you know, your, your Ws.

So let's unpack those a little bit. The whys. Yep. Absolutely. So starting with the why, it's important to know why we are doing this, right? Um, what is, what are the business outcomes that we can generate out of this effort? Just like any other investment, it's measuring or knowing what the return on investment would be, um, before you, um, embark on that journey and.

There are ways, um, you can quantify some of those outcomes. Yeah. Uh, you can quantify them around agility, which means, uh, how quickly can you, um, go from idea to production or make more releases? Yeah. That can, um, thrill your customers with those products. Uh, you can put metrics around, um, developer productivity, like by making, by modernizing your applications on your whole stack.

How can you have, uh, developers, um, have low touch idea to production process where most of it is self-service, so that improves your productivity. And then, then you can put metrics around cost savings by moving to newer architectures and cost avoidance, um, by increasing the uptime, availability, all that cool stuff.

So it's important to know the business outcomes because it naturally drives Right. The business it alignment and, um, helps an organization rally behind such an initiative and get it done. Yeah. So, so when you go in, cuz I think you still spend a little time in front of customers, even though you, you absolutely.

You've got a super fancy title. Um, so let's, let's envision for a moment that you've walked into the mm-hmm. Into the, the conference room pretending of course, that we still go into conferences, right? Uh, and you've gotta, you've got folks who are there and they've decided we're going on this journey. So you come in to say advisory services.

This is really, this is really important stuff to do. What's the first question? First question out of out of your mouth that you asked My first question out of the mouth as I said before, is, why are we doing this? Yeah. Why are we here? Is the juice worth the squeeze? Yeah, there you go. Now I'm thirsty. And that's, it starts the discussion as to once the why is clear, what does an application modernization roadmap look like?

And what is your strategy Yeah. To do it. Right. As you said, there are organizations that have been, that have been on this journey for, um, for longer time or many, many years. It's important to know what that journey looks like for an organization, because there are workloads that came up in the survey that can't be modernized.

So what is our path forward to tackle those? Yeah. We have to answer those questions upfront. So when we embark on this journey, we have a clear plan attached to business outcomes, right. And a clear strategy to do this for an organization. Okay. So two words right there. Plan and strategy. There you go. You know, again, we are, we're not talking about what's your favorite tech.

We're talking about what is the plan and what is the strategy, because strategy's gonna tell me how we're gonna implement the plan. Absolutely. And the plan also doesn't address everything at once. You've got to choose pretty, pretty judiciously. Absolutely. About what to, what to jump into. What, what type of applications do you, so I'll tell you the second thing we do, okay.

After we answer that question is we look at what you have today. Look at it from a tech stack perspective, from a dependency perspective, and uh, looking from a complexity perspective, the integrations you have, the level of effort it'll take to modernize or get something out. Yeah. Um, and put it into the new stack, uh, and then create a plan where we start small.

Mm-hmm. Right? We start small and then we scale and we package all of these learnings in that process and make them repeatable and standardized for the other applications that will follow. This is how you generate the acceleration, right, towards modernization. And then the strategy. Your strategy, how you do modernization depends on your cloud strategy.

Yeah, right. When you're all in into one public cloud, you can leverage all of the goodness, um, go all the way serverless, use function as a service and get significant, uh, benefits out of that. So, so I want you to think for a second about some of the companies that you've talked to mm-hmm. And, and folks that we've seen go through the process.

Talk to me about a success story. Don't, don't gimme a customer name, but talk about a workload or something that somebody said, it'd be nice if we could, and you said, absolutely we could. And, and in the end, what was the business, the business outcome that they saw and maybe even didn't expect? Yep, absolutely.

So, um, I can think of many, but, uh, one of the ones that comes to mind is, is choosing the right strategy depending on the workload. Yeah. I know serverless function as a service sounds like the ultimate end goal for an organization, but a lot of people get pretty excited about that. Exactly. Uh, but then while working with a client, we determine that based on their cloud strategy, we need to keep some things agnostic.

Yeah. Because in the future they had, um, Plans to expand beyond one cloud. Yeah. So we had to go in, we had to do more cloud agnostic choices in order for that to make, to make it happen for the client because their path was not all the way to the right side of the spectrum. They had to be aligned somewhere in the middle where we can modernize most of the workloads.

The 80 20 rule, right? Yeah. That gave them the maximum benefit. Right. So that's kind of like how we tailor that journey or the modernization initiative to A, help them get from idea to production faster, increase the developer productivity. And then help them save on their monthly bill by reducing the opex and moving to a more, um, modernized, uh, way of running workloads.

Yep. Alright. So folks, I need to, I need to make sure that we're translating something that, that, that Niraj is saying, and that is, it's not gonna happen instantaneously. And even for those applications that you choose, let's, let's just grab what it's a CRM application. I'm, I'm guessing here. Uh, it's not a one and done with that a as well.

It's something that you need to create a roadmap. For how it evolves, uh, in time going forward and attach those to what are those business outcomes. Now, when we did their research and we looked at, at, um, you know, what were IT leaders expecting about their transformation to the cloud? Let's pull up the slide now that shows, you know, what they were looking for.

They're looking for improved efficiency, uh, greater cost savings. They're looking for stronger security and easier technology adoption. And I think what we're hearing from Raj is these are all extraordinarily attainable. Absolutely. But it does take a plan. It does take a plan. It does take into account your overall cloud strategy.

Yeah. And then how we can get you there. And there are ways to get there, right? Yeah. Uh, we can do it for you. There's companies that partner with, um, other organizations can, that can do it for them or do it with them. Yeah. Or organization can do it themselves. Learn and implement. So there's no one size fits all.

It's not one size fits all. There's not even a one size fits all inside of an organization. Absolutely. It really is workload by workload. It is. And it is not one and done and it takes time to get these things done, but it's worth, you know, back to your phrase, absolutely. Is the juice worth the squeeze?

Tell me about a time of juice might not be worth the squeeze. Oh, many times when, uh, we have legacy workloads that may not have an immediate path to modernization, but there are intermediate stages that we can get them through to achieve and keep the eyes on the prize and get them, uh, to where they want because there's a significant investment needed, uh, for those workloads to be, uh, fully modernized.

So it is choosing carefully and then choosing enough that we can show the art of the possible. Yeah. And then scale that momentum in an organization. Love that. Alright folks. Um, so we're gonna continue our conversation here, but. This is live. You're watching us live here on Tuesday at, uh, sometime after 10.

I don't know where, where, what, where we are in the world. Uh, but I wanna welcome everyone who's been, who's been commenting on where you're coming in from. We're so excited to have this global audience, but I wanna encourage you to ask some questions. Uh, we will take some of those as we go through with individual guests.

We also have time towards the end. We'll, we'll address it all holistically once we've, we've gotten everybody up here, so feel free to comment in there. We see folks from Germany, from from Canada, Nigeria is here. I'm so excited. Pakistan, uk, Ohio, that country, no state of Ohio. And so welcome everybody here.

And yes, doctor, there are lots of moving parts for, for this. But let's, uh, and you, you Niraj, you addressed this here when we talked about. When you talked about workloads, maybe legacy workloads, you know, they get put on hold because they're hard. But oftentimes those legacy workloads are attached to some pretty important data sets.

We think about, maybe it's an old SAP or Oracle implementation, and Oracle tends to be one of those that will take a while to move because it has so many tentacles running so many things. So let's talk about integration for a second. How do you, let's talk about strategies there. First of all, you know about, about when to do some of those, but also how to set appropriate expectations of when some of these things.

Absolutely. And before I answer that, modernization is not just application level. Hmm. Modernization is starting ground up, starting from infrastructure, elevating up to data, bringing your security up to speed in terms of modernization, and then going to the, the app layer and looking at what we can do from an application perspective.

Right. So to your point, like some of these, these legacy workloads, there's what we call sometimes call them our big rocks in your modernization journey. Yeah. Um, having a clear plan, not going after it all at once. Yeah. And trying to do it too fast. Giving yourselves time to a, analyze the workload in a better way, and then having a clear.

Short-term, midterm and long-term plan for modernization for some of these workloads is the strategy that we see working the most the best. Fantastic. And what we'll find is, is just as we found in this conversation here, is that advisory services, this part of making the plan absolutely. As it is a forever activity, doesn't really go away.

But at this point, I wanna move forward in our process of moving from, uh, through the through. Uh, this whole modernization, uh, adventure journey, if you will. It starts of course, as we just talked about with advisory services, but once we have a plan, once we have a strategy, then it's all about executing that transformation.

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All right, with that, let's get back to the program. Now I've invited, uh, a, a, a, well, really a good friend. Now here at Rackspace, we have a phrase, it's called Once a racker, always a Racker. So, uh, our next guest, while he is an amazing architect over at aws, he was once here, uh, at Rackspace. So once a racker, always a racker, currently employed by s would you please welcome to talk about all things transformation.

Adrian San Miguel.

Once a Racker, always a racker. Adrian. Yes indeed, Jeff. Thanks for having me. So glad that you're here and I've never had somebody, uh, live or or otherwise with such a cool cane. Gonna say it's barely there. Well, thank you so much for being a part of, of this process. Now, uh, you guys been following our, our, our lead up to this event.

You've seen some promo videos. You and I shot one of those as well. Mm-hmm. And in there you said something that's really been, that it's stuck in my head for the past couple of weeks, and that was that, you know, once you, once you think about doing that move and you move some stuff over, well that's just the beginning of the journey.

You've just hit base camp. The summit is still a few thousand feet above your head. What do you mean by that? I mean, exactly that is exactly as you mentioned. You have to begin unpacking everything. Once you get to base camp, you get there and you realize that. Hey, I may have left back the car, the carabiners, I may have laid, left back my canteen.

We were in such a hurry to get going on this journey. We didn't ask the right questions. We didn't answer the appropriate scope of discovery. We just thought, Hey, we have an impetus. We've got six weeks to get out of our data center. Right? We're just gonna go into a lift and shift approach. Just like your stats said, we got there and we, what we thought was going to be a multi-week journey.

We're 8, 9, 10, 12 years into it, and we've realized we never really did find that R O I or that promise of innovation or investment that we may have found on the cloud. Yeah. And so if you have packed your ruck sack really quickly and headed up the mountain and then realized you were missing some stuff, like the canteen naturally was either not there or not full of anything to drink.

Yeah. Uh, we found some companies in our research, we found that there were some common challenges that folks had in the transformation aspect of it. And if we pull that slide up now, here's what we found. We found integration challenges. We found, uh, unforeseen costs show up. Hey, you know, it costs a lot to climb this mountain.

And then lastly, legacy incompatibility. What a delight. Um, so if, if we have, if we've gone through advisory services, um, and we've done that, right? Not everybody has, and that was something Niraj we didn't really even get into as much. And that was, this isn't we, I've said the phrase, it's one and done. But most of the companies, a lot of the companies that show up.

Have tried to summit and have gone back down. They, they've left Basecamp and they've gone back down to the city. Um, so when we, we look at companies who are going through transformation, then they have issues like integration challenges, you know, how can companies deal with that and have a successful outcome?

It really all does start with the definition of the problem that you're really trying to solve. Mm-hmm. It's, we are going to get to cloud and then what are we going to obtain a higher sla? Are we going to improve on our R T O R P O? Are we looking to see multi region or geographic distribution? Are we trying to.

We shorten our development cycles. Are we trying to reach a wider audience? Yeah. It all depends on properly defining, scoping, and setting realistic expectations with customers and with stakeholders about what it will take to get there. Sure, you have a legacy mainframe or Solaris implementation that needs to get into aws.

We'll be more than happy to help you get there if you have the impetus of speed and you need to get there. Sure. Here's a legacy emulator by Strumis that will slot right in bing bang, boom. You're on your way. Yeah, but the problem is whatever existed when it was there, when you put in that emulator, still gonna be there.

Still there. It's still a problem. You've taken your messy garage and moved it to a new garage to be messy. Anybody that's a parent or has to get on a plane and get going fast, you know, you might not put everything into the luggage. And once you get there, that's when the problems really start. Right.

You're missing a toothbrush, you're missing your deodorant. You. Forgot the cane. Something. There's something that you leave behind and that's when the, that's really when the wheels begin to fall off, you start realizing, I need to go back and get something that costs time, that costs money, that costs frustrations.

Within your developer community, within business stakeholders, say, you said, if we did X, we would see Y. Yeah. Without the appropriate scoping, as Niraj stated, without asking and validating the right questions, without trying to really understand what it is that you're trying to solve for, it's no surprise that customers are running into these sorts of things.

That's exactly where AWS can help customers. Yeah. In real realizing no matter where in the spectrum you fall in, we want to be lift and shift. We want to be extremely agile and incorporate some sort of hybrid approach so that we don't have to rush the migration or. We want to go serverless by default, no matter where you are in your journey.

Yeah, we can help you. So a couple things I wanna unpack inside of there. So first of all, let's say we're gonna, we're gonna beat this analogy to death. And by the way, please. So we realize we're, we're at Basecamp, we look in our backpack, we realize that the canteen is empty. Mm-hmm. Does that mean we failed?

It doesn't mean we failed. Absolutely. It does mean we need to make a change. But it doesn't mean we've failed. It does not mean that you failed. It means that you need to rethink your assumptions. Does that mean you, you can make it with a couple bottles of water? Well, it depends on how far the climb is and how, how.

Treacherous. The terrain is how well under foot you're prepared, what physical shape you're in, whether everyone in your party can potentially spare a bottle of water or help refill something. Yeah. To help you get going. It doesn't mean that you're stuck, it just means you need to reevaluate. Reset. Right.

So, but if we draw this now back to, to AWS migration, to cloud migration, we realize you got a business partner who's now showing up going, you said I was gonna get this outcome and we're not. Now it is. We have legacy and compatibility issues. What, what a bunch of our folks said. How many people? A lot of people.

Um, and, uh, it doesn't mean that the cloud migration has failed. It doesn't mean the cloud migration has failed, by the way. Absolutely correct. Even with all the best strategy and all the best planning. Things happen. Things do happen. Uh, stakeholders can leave, plans can be abandoned. Reprioritization and customer partner company, aka somebody changed their mind.

Exactly. Something changed to either reset the priority list or just drop off priorities. This is the new important thing. Yeah. Uh, so, so uh, I think what that is driving towards is this cloud migration process really has to have a, a bit of flexibility. It needs to have a lot of flexibility built in. It absolutely does it, it's no embellishment to say it's just like a road trip.

You can start off with the best of intentions. You have your stu, your pit stuff set, where you're going to stop for fuel, where you're going to stop for coffee, food, donuts on the way. Donuts. It doesn't matter. You know, you, you need to bake in that flexibility. If you're the type of individual or the mindset is going into the project where it is static, it is finite.

The plan is a plan and there's no deviation. Yeah. You are probably going to fail and you need to be comfortable with the fact that you're going to fail because there is no flexibility built in. Well, doesn't that, doesn't that get us back to the old adage? Uh, and we hear it a lot in technology, but that's fail fast because what we're trying to do is get to the point where our plan doesn't work.

So at Rock Space, I've had the opportunity to, to be a part of some of the m and a activities that we've had. And, and uh, and one thing stuck with me, Brett Pi, if you're watching you, you taught me this and, uh, cuz he was helping with the, the, the whole process. You remember Brett? I do. Uh, and now he's run some businesses here in San Antonio.

But the, and it was, I would say, Brett, Brett, are we gonna do this thing? We're gonna buy the company. He goes, well, you got to improve. Approved to go to the next meeting. What does that mean? It means you get to have another meeting to continue to prove your case. And they may shut you down in there. You may get another meeting.

And if it just continues forward, and that really is talking about the fail fast, how can you get to a point where either no exists or success exists? And I think that that drives us towards flexibility. That's exactly right. You have to be okay with a divergence of the past. Uh, hey, the original plan is we are going to begin to containerize this workload.

Okay, well, great. We have some code and compatibilities. We have code dependencies. We have a incompatible database engine. We have some in some sort of different, um, ideation, some sort of difference in training and divergence that's going to make this not as fast or not as flexible as we thought it was.

Okay, cool. Park this. We're going to take a detour. Yeah. Being comfortable with that detour and being comfortable with failing fast and not letting a single setback derail the plan is really the secret to success. How often? This is a leading question. Let's just admit it. Thanks. How often. Is the problem, the technology, how often is the problem the people?

Almost entirely skewed to the people. Okay. Bad expectations. Um, not having the appropriate mindset and not being really willing to do the thing. Everybody really has to be bought in for that journey to the summit. If you're still in base camp, you know, going to beat the analogy to death base camp. If you are not all in on it, bad things are going to happen.

Yeah. And if you're not okay with stopping the plan, reasses reassessing, taking the detours where needed. Yeah. You're never going to get there. Okay. All right. So you've made your move. You, you, you've, you've left Basecamp now, so you've made that move into, into, uh, into your cloud. Uh, and, uh, and so grateful to have AWS with us today, uh, as a sponsor, as a, as a genius to, to help share some stuff well there.

But, uh, but what I wanna do is just pause the conversation for a moment and share a video that AWS has shared with us just to, to talk a little bit more about their capabilities and their scale. So let's go ahead and roll that clip. Running a wide range of applications efficiently and securely is a top priority for organizations looking to transform their businesses.

Millions of customers trust AWS's capabilities to run their applications. AWS is designed to be the most secure and reliable cloud by delivering innovations and performance so you can get the most value from your infrastructure. The A W S Nitro System offers built-in security at the chip level. To continuously monitor and protect hardware against potential security threats.

A w s designed silicon offers the best price performance for your applications. A w s Graviton based instances deliver up to 40% better price performance and use up to 60% less energy than comparable X 86 based instances, a w s delivers the most capabilities across infrastructure, services and tools, so it is faster and easier for you to build and run any application.

Leverage the broadest range of storage options, the fastest networking, and over 575 compute instances for different types of applications. Choose from over 200 services, including serverless and machine learning capabilities to accelerate development, modernize existing applications and simplify operations with aws.

You can use the same infrastructure services and tools to build and run your applications wherever you need them in the cloud. All right, so, uh, I gotta call this out because it's a great example of the cloud. This is a great video. It does talk about amazing things that AWS can do, but since we went to sleep, things changed in aws.

Yeah, absolutely. Um, video called Out 575 instances. As of this morning, we are at over 650, generally available instances to meet you exactly where you are. It doesn't matter where you are in the journey, what the particular workload is, how many bp, cpu, is it type of cpu, we're ready to help you in the best way possible.

That's fantastic. So folks, you know, think about that. We talked about how things can go awry. Even if you have a great plan and you have a great strategy, you may be a hundred percent lined up and all of a sudden new services exist. Like an AWS that you, uh, that, that weren't there when you created the plan and it creates a pivot.

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You gotta manage these applications inside of the environment. And, uh, and so to here to talk about the, the, uh, the, the management aspect of it. Straight from the office of the CTO here at Rackspace is my good friend, Atari. Uh, and he's gonna share all about that. So would you welcome to the stage Atari.

All right. So Tara, you've been around Rackspace for a good long while. How long has it been? Yeah. Uh, almost 17 years now. 17 years. 17. So what was your first job at Rackspace? Uh, I was a software developer. Software developer at Rackspace. Now, when we, in those 17 years ago, it was all about managed hosting.

Mm-hmm. We would take somebody's workload running in somebody else's data center and we would put it in our data center and we would operate it. Mm-hmm. And uh, and we would put a thing around those workloads, it's called a spheres of support document and what it said, think of it just like that spheres of support.

It's a big circle. Anything inside the circle we would do forever. Anything outside the circle, well, we would still do it, but there was no SLA wrapped around it. Uh, cuz Rackers would always just go the extra mile to solve a thing. So we do at Rackspace. Uh, but when we started to run things out in the cloud, we started to run and manage workloads in aws.

Mm-hmm. We still had a spheres of support document. Mm-hmm. We'll do stuff inside of that circle, but the stuff outside. A little try. Best effort. Mm-hmm. And that got really dicey. I mean, Adrian, imagine in those days when, when all of a sudden now there's more services. And our customers would ring up and they would say, what are you gonna do about these things?

What we learned, I'm gonna cut to the chase. What we learned is operating workloads in the cloud. Very different than operating workloads in a traditional VM type driven data center. Exactly that. So gimme a characteristic. Yeah. You're, you're a hundred percent correct, right? Uh, when you're operating workloads in the cloud, the first thing is you gotta be able to monitor it.

Uh, and you're monitoring different components in the cloud, right? Because back then it was just more servers. Yeah, just more their server. But in the cloud there's so many different components, right? You have, uh, serverless components, you have, uh, event-based services, you have cloud native services.

That's right. And then also you have ISAs and your application in the cloud is kind of distributed across all these components. So how do you effectively see what you're going end-to-end and be able to respond accordingly? Right. So the model is completely different, uh, because of the distributed nature of the applications, uh, in the cloud.

Um, another thing I wanna talk about monitoring too is that you, you, that you monitor for two main reasons. You know, you wanna be able to measure, uh, and you wanna be able to respond to what you're doing. Yeah. Uh, some of the reasons that you might measure, like, uh, Niraj was saying from an advisor perspective is you wanna ensure that you're meeting your business objectives.

You know, how are you gonna know if you're meeting your business objectives without measuring? So that's one of the key things we're using, uh, monitoring your infrastructure components. I love that. Well, let's talk about monitoring, because that in is one of those things that sticks out in my head as one of the big differences in running a workload in public cloud than in a traditional VM type of an architecture.

And the reason for that, well, there's a lot of reasons, but one of the things that sticks in my head is you mentioned serverless before. If we're in a serverless world and I have a traditional monitoring agent, where do I put the agent? Exactly. That's a problem. Exactly. So that's why you have to rethink how you're monitoring.

Uh, there's a lot of tools that are out there too, like the AppDynamics and New Relics, and those have had to evolve over the years to keep up with all the change in technology in the public cloud. Uh, so there there's different things that you have to measure and be aware of. Yeah. Uh, so for example, things like service technology, right?

You know, how, how fast is, is, is a function. Working, you know, how, how fast to respond to it requests. I mean, there's all sorts of things that you have to consider in the new world that you, you would've considered early on, right? Mm-hmm. Now, there's a phrase that, uh, that our friends over at AppDynamics use, they sponsor the program.

We're grateful for them as, uh, is they, they use this phrase, Keith. Keith Loren uses it. He and I present a fair amount together, and that is, uh, and everybody, it's full stack observability. And they started using that around me, and I was like, What the heck is full stack observability. Yeah. Uh, and, and, and uh, and they start using this phrase, they would talk about, you know, when things go south, when something stops working the way it's supposed to, what happens?

We've all been in that seat, uh, regardless of who we are, uh, here on stage. And that is, you know, the dreaded P one shows up, the app's not responding the way it's supposed to. We've got network in there, the developers are there, the business is there, everyone's in there. And it becomes this conversation of meantime to innocence.

How do I, how long is it gonna take me to prove that it's not my problem in there? It's somebody else's problem triage there. But when you use a tool, like what we find with some of our, our partners, you mentioned New Relic, I'll, I'll uh, um, uh, Datadog is another one. Yep. I use a fair amount as well, but, uh, and AppDynamics, but they're looking at the whole stack from business transaction all the way through into it, and they're able to measure all of that stuff and then also attach it to a business metric.

You mentioned business metric, so Exactly. But the metric moves. Yeah. Apps a little off. Exactly. And and that's another thing, moving your applications to the cloud too, right? It's the focus is less on the infrastructure and more on the applications, right? Because that's what it is. Customers run applications.

The infrastructure in the past was just a means to get there. That's right. So that's why monitoring is a little bit different. Full stack monitoring, you're looking at business transactions. Yeah. You're looking at impacts from a networking perspective as well. Uh, cuz there's different layers of supporting application.

Also from a deployment perspective, you wanna be able to monitor that. There's times where you deploy an application, you wanna be able to see from the time I deploy this application, here's how it behaved. Yeah. You know, uh, the service I had deteriorated or it increased, you know, so there's all sorts of things and that's why Well, and if we're attaching it to a business outcome, then, then, you know, things start to look a little different on Monday morning and people are saying, why, uh, why is the pro, why, why are we not able to tra process as many credit card transactions on our site as we were on Friday?

Exactly. Well, you look through it. Wow. Somebody deployed some new code on Friday. Right. I wonder if that might be something to do with some of that code. Mm-hmm. Could be. So let's, let's rewind to the beginning for just a second, and that is advisory services. Tell me about the conversations you're having on the front end.

Are you talking monitoring at the very beginning of, of those, those workloads? Absolutely. Um, as I mentioned, we have to create a holistic, actionable roadmap. Yeah. And one of the components of that roadmap is once you go live with a modern workload, how are you ready for day two? Yeah. And day two is where all of the modernization conversation happens as to how we get ourselves ready to be able to operate that workload.

Keep the lights on 24 7 and also take the next step, make it self-healing. Because that you can totally do when you modernize a workload. Well, when we start talking about self-healing, now we're now we're bringing AI into, into it. Again, we're talking machine learning, we're talking about about, we're talking about non-human intelligence.

Uh, you know, I can't tell you how much inside of this last study that we did that, uh, artificial intelligence showed up. It is the, the magic word these days. If it isn't the solution, it's a part of the conversation. That is absolutely for sure. At Rackspace. We have some new service offerings around that you can learn, you know, more about how that impacts Guys, we're, we keep referencing this study.

Uh, just head over to rackspace.com/solve. You're gonna find it on the main page there. Some fancy new graphics too. We're pretty excited about those. Uh, love to hear what you think about that. Right? Yeah. You mentioned AI too. A lot of these monitoring tools and new ones actually have AI built in to help you triage.

Yeah, because sometimes these tools are just there. You can look at it and then you still have to go, well, what's going on? They might make it easier for you to figure out what's going on, but some of these tools with AI can actually tell you. This is what the problem is. Yeah. We saw there was a, a degradation in service.

We saw this is what happened. The data, the database connections are cutting off and here's what the issue is. So it helps actually speed up your, you know, meantime to resolution. Yeah. And those types of metrics that are very, very important. Yeah. And not, not to pitch a product, but at Rackspace we have an offering called Modern Operations, and it's for some of those workloads that are moving into the cloud that maybe aren't as, as cloud natively yet.

What are some of the characteristics, because I'm not trying to pitch a product here. What I'm trying to do is paint the picture of how things are a little bit different inside of the cloud. Mm-hmm. And it's best to go back and look at some of those characteristics. Uhhuh. Yeah. I mean, uh, literally you're looking at, I mean, uptime, you gotta figure out if your applications are working, uh, you know, uh, downtime.

And there's all of characteristics that you look at. One of the key things is being able to respond automatically. Right. It's the self-healing type of thing. That's right. So for example, uh, if you have a server that's not responding, you, we actually can code in Runbooks that can actually take out a server, uh, spin up the application again and bring it back into, in the server pool without anybody actually interacting with it.

So being able to define all those kind of things, um, that's very important and that's kind of what we do. Yeah. Part of our, now we've sort of gotten lost in this great conversation. You know, I just brought AI back into it, but you, we go back to that metric of 90% of those respondents, 1,420 respondents, 90% of them, I think that's more than a thousand.

I'm not great at math, but, uh, uh, that are, are going through this process so that they can start to leverage. Ai. Exactly. It is a driver. People see that as a massive, uh, opportunity inside of their businesses to utilize that stuff, but they're recognizing that that data's gotta transform, that those applications have to transform and they need to get it into an environment that has some of that native tooling, like over at aws where you guys have all that, that wickedly cool new stuff that's happening over there.

Little bit. Just a little bit, yeah. Part of what drove those numbers and services. Mm-hmm. So, Atari, the last thing I wanna talk about with you here real quick is what's different about team structure and in, and those, those traditional support IT teams and how they have to integrate more with the business on a moment by moment basis in some cases in this new cloudy world.

Yeah, I think the obvious thing is the whole, in the cloud, the cloud kind of favors a, a DevOps model, uh, because in the past, uh, you had very laid out roles. You had people that were managing the infrastructure. You had a separate security team, then you had your developers, I remember in the core days right, where we were developing, and then we would toss it over to, and try and run a release with so many code changes at the same time.

And, you know, it was, it was very interesting, right? Yeah. But in the cloud model, because you can spin up infrastructure and tear it down very easily, like, uh, and there's, there's, it's easy to spin up infrastructure for the actual application development teams. Uh, you know, the DevOps model. Kind of is a little bit different.

So you have positive teams with cross-cutting concerns. You've got the application developer on owners, you've got the QA folks, you've got security folks. Yeah. And then you have like SREs or dev engineers that can automate infrastructure. So essentially, again, like I said early on, it's more about the.

Application less about the infrastructure. And that's why these teams are focused on building apps. Yeah. And there's no concept of, oh, I did my part or my code worked on my box, and that type of stuff. Right. So it's all team. And you know, one of those groups that have been brought into the team is, is, I already, I said it was the last question, but I have one more.

Um, classic Jeff, by the way. Is, uh, is security. How is cloud, how is security approached maybe differently? Uh, yeah, in this cloud-based world, it's cool cause the cloud-based world brings a lot of programmatic models for a lot of things. Infrastructure, security. Yeah. There's so many things there. Right. Uh, and that's why it's a good thing for the Dell model.

Uh, in the, in the old days, the old way of doing things security more was an afterthought. Right. It was the gate, you know, make sure we're secure. Yeah. They were the no team that sat over in that office. Exactly. But right now with DevOps, you volunteer DevOps, DevSecOps. Yeah. Security is able to code things ahead of time.

Right. So you're banking in security as part of your application development process, the cloud modernization process. Yeah. So it's a lot more efficient. You don't have that bottleneck and things are kind of going. That's excellent. All right. So, so we've made that move. We're out in, in the cloud now. Uh, by the way, Deon, great thoughts.

I love it, doctor. Uh, great, great stuff. You're, you're sharing there with us as well, folks, continue to comment. I love them. Seeing them come across. Uh, I'm not checking email, I'm reading your comments down here. Uh, also, uh, get your questions ready cuz we do have a q and a session coming up here in just a minute.

So we will address as many of those as we can in our hour that we have. Okay? So we've got the move out into the cloud. But it doesn't stop there. When you make that move out into the cloud, you are now an environment that is transforming under your feet. Your business is evolving over time. And that takes us to the fourth stage of, of what we think of as cloud transformation starts with advisory, moves to the transformation, then we're operating, then we're optimizing.

And here to talk about all things. Cloud optimization is, is one of our senior leaders in and managers in managing these teams who do this work. Uh, straight from California live here in San Antonio is Mr. Jr. Price. Hi,

Jr. Hello. What are you looking forward to doing in Texas now that you're here? Uh, gotta get some barbecue. That is a great first thing to want to think about doing. All right, so I'm not gonna ask you how to, um, uh, the parallels between, uh, barbecue and elastic engineering or cloud optimization as we can refer to it.

But, uh, but let's talk about that. So Rackspace does have this offering, it's called Elastic Engineering. You're one of the leaders of a pod of a team. Uh, and again, folks not pitching a product. But what we're doing here is decomposing an offering so that you can better understand why it's important. So at Elastic Engineering, this is not one of your traditional call centers.

This is not a couple of thousand smart people, uh, you know, and you're getting round robin to, to helping somebody optimize their application. But if we go back really quick before we get into, into that, we're gonna go back to what are companies expecting about how to ma uh, in their move out into the cloud?

It might be. You know, improved efficiency, it would be greater cost savings, stronger security, or easier technology adoption. Now you may get that as part of your initial move in, but if you temper your expectations just a little cuz it is a trans a, a bit of change, uh, we get into, and once you've made the move, Well, now it's time to optimize.

Let's unpack a few of the things that a company is wanting to do, or their outcomes that they would expect in the optimization phase. One of those that comes to mind is financial optimization. We do the best we can. Everyone does the best they can, starting in advisory to help set the right financial expectations.

But if we think about financial, uh, optimization, we're trying to make sure every dollar we're spending in the cloud drives business value. How does, how do we, how, how can we help with that in, in an optimization phase? Yeah, absolutely. So obviously the first thing you have to do is identify your applications and workloads properly tag them so that you can allocate them to cost centers.

Yeah. So that you can know exactly what applications or what business units are costing the most. I gotta push pause real quick because it's a really important point that you just made. You want to identify all of the costs. And allocate them to cost centers to business units inside of, of an organization.

It can't be this amorphous, hey, it's up to it to pay the data center bill. That changes here. You gotta get financial accountability back to the people who are ultimately spending, uh, driving that, that meter. Absolutely. Yeah. All right, so we've identified that. Now let's continue down the process of financial optimization.

Yeah. So once you've identified your, your workloads and you attribute them to the cost centers, um, you need to set some measurements and metrics around, you know, what these resources should be costing. Yeah. Um, once you've set that, you can identify, um, resource waste, um, lots of over-provisioned resources as well.

Um, so not only does it allow you to optimize your costs, but it allows you to start optimizing your resources and your efficiency as well. Yeah. Some of your sustainability is in there as well. Yeah. So that becomes the financial, uh, accountability. Uh, um, an optimization becomes a good way to go through.

And one, just a, just a, a bird's eye view down, here's everything that we're, we're consuming, and the way I like to refer to it, and I said it earlier, is not how do I lower my bill? Everybody would like a lower bill, but we're trying to drive a business outcome. But how do I ensure that every dollar spent in the cloud drives business value?

Yeah, absolutely. Um, at the end of the day, um, each dollar in the cloud, um, uh, you know, is, is being spent for you to, uh, deliver some value from your business to your customers. Yeah. Whether that's, you know, you're selling tacos, you're serving webpages, whatever it is. Um, so at the end of the day, you really wanna make sure that you're focusing and putting those dollars towards those, uh, applications that are bringing in money for your business as well.

Yeah. So, but it's not just all about dollars because we're trying to get additional capabilities as well, because that may be part of Raj's plan from the beginning. That strategy from the beginning is maybe we are gonna do a lift and shift. And that's okay to do a lift and shift as long as it doesn't stop at lift and shift, because that optimization phase now may be to take and, and go through some sub levels.

I like to think of 'em as micro transformations. How do we on a, on a, every couple of week a sprint basis, look at these workloads? So we assemble teams, small teams, uh, about nine, nine people. Um, tell me the makeup of these teams. Yeah, so our, our teams are made up of, uh, uh, a few cloud engineers, a few senior engineers, and a few cloud architects.

Yeah. As well as a pod lead. Um, and, uh, with that team, um, also comes an engagement manager that is gonna help align the customer's business needs towards our technology solutions. Now we're talking about a long-term engagement here, or are we talking about short-term engagements? Um, it, it both are, both are available, so whatever.

A lot of customer demands. Correct. A lot of customers come to us for a specific business outcome that they want. However, just like the analogy with the base camp, once they're at camp, they start unpacking, they realize they're missing some firewood. You need an axe, you need something else to go and produce more firewood.

Um, so that's where Elastic Engineering is able to understand their business needs and where they're trying to go and make sure we're aligning solutions to, to help them, uh, continue to modernize. Right. So they've gotten into the cloud. Um, but then the next step is, uh, to start set setting some metrics and measurements around how cloud native are you, are you taking advantage of all these services?

Mm. Um, you know, businesses don't need to pay DBAs to manage their databases anymore unless they're businesses around the lowest transaction time. That's right. That's a really good point. So, uh, so also around that, you know, we, we we're gonna keep going back to Adrian's example of, Hey, the video was right last night, but now it's not right anymore.

Uh, because the cloud transforms under our feet. And this is one of the things that I think companies can't pay more attention to. By the way. It's one of the hardest things for them to pay attention to, and that is, you know, they may have architected with our help or someone else's, the best solution for what was available on day one.

But now we're, you know, a few days into the cloud, And what we built as a solution, there's an as a service. So tell me about the dynamic of working with a, a team like this that we find with elastic engineering, or maybe they've got some other folks who do that and uh, and prioritizing how they continue to optimize their infrastructure to be maybe the latest and greatest so that they might get the business outcomes they're looking for.

Yeah, absolutely. So after our team has delivered on the initial, um, uh, outcomes that the customers come to us for, um, we have a framework that we've developed called the Cloud Maturity Model. Yeah. That helps evaluate businesses across eight different dimensions, security monitoring, app performance, et cetera.

Um, and each of those eight dimensions has six phases that kind of measure their maturity in adopting more cloud native services. Yeah. So after we've delivered the. Uh, initial outcomes, whatever the, uh, uh, uh, projects that, that brought them to us were, um, after that we start, uh, evaluating them and measuring them against our framework.

And, um, month after month, week after week, we suggest new opportunities where they could take advantage of either the new as a service offerings Yeah. Or modernize their existing workloads. Okay, so folks, what I hope you're realizing here, and I'm driving a, hopefully a narrative through all of this, is the change in moving to running your applications, your workloads, your business in the cloud.

It requires a different approach, whether it's on the advisory side, whether it's at the transformation level, whether it's how you're operating it or how you're incrementally making it better on a day by day basis. This is not a set and forget environment. Can you set and forget, I guess you could. Uh, why would you want to, why would you want to go buy a car that can self-heal and make itself better on a day-to-day basis?

Makes me think of a Tesla. You know, you go buy yourself a Tesla, you wake up in the morning, you've got auto driver capabilities, autopilot, I guess they call it. I don't have one. I have a truck. I guess they make those trucks that do that, but I don't have one. I have to do it myself. But, but if it's gonna improve itself overnight, why wouldn't you take advantage of that?

Why wouldn't you look for ways to either drive better financial outcomes, better business outcomes, better technology, more efficient technology outcomes? Like, could we use AI and ml, uh, in a way that that is, that is compelling and makes a difference for the business? Do you guys in, in elastic engineering dig into, uh, helping with the data transformations or finding opportunities where AI and ML can be a, a, a business driver?

Not so much in elastic engineering. There are some places like around monitoring where only leveraging AI and ml. Uh, increase our signal or sorry, reduce our signal to noise ratio. Um, and so, uh, there, there are some places. That's right. Alright, so there is a, uh, a question, uh, in here I wanna address and I'm gonna give everybody a quick chance to answer this one cuz everybody's here and you guys look like you need to talk.

Um, but there's a question about managing security in the cloud. And so we're gonna go in reverse order. We'll start, we'll we'll stay here cuz I, I'm interested as we think about this optimization phase, how we're optimizing for security, but get your, your like 30 to 62nd answers together, rest of the crew here.

So how in, in optimization are we optimizing for security? Yeah, so with, uh, in, in the optimization phase, we're making sure that, uh, we're. We're leveraging, you know, infrastructure as, uh, uh, infrastructure as a service. Yeah. And all of those things are being built out with consistent best practices measured, uh, against, um, not just open source standards, but with tools to validate our compliance as code.

Yeah. Um, so those are, uh, the primary ways that we're, uh, increasing our security. Okay. So when we think about, uh, operating, how does security fit into the day-to-day in operations? Yeah. It, it's all about getting all the in information from all the different endpoints, collating it into a central place.

Mm-hmm. Uh, and being able to do some analysis on that automatically. And that's where AI comes into place, right? You can actually look at trends. You know, you can see, okay, uh, there's, there's an intrusion happening. This pattern seems rear rare, and then it alerts someone, right? So there's, the cloud allows for that, uh, in a very seamless, uh, manner.

Absolutely. So let's think about transformation stage and thinking about security and that transformation layer. Absolutely. What it does is it forces a reckoning. At the business level to state that, hey, by default, we have to be designing in a secure manner. Yeah. You have services within AWS by way of CloudWatch, anomaly detection, aws, guard duty, aws, waf that do this by default for you.

They build a baseline of what normal looks like for you. Yeah, and raise that alarm using AI and predictive analytics to say, Hey, that's different. That's a problem. Here's the thing that you need to go and reckon with and go deal with because X, Y, Z, these are the CVEs that are relevant. Or, Hey, this is just something so anomalous.

This is an immediate P one. You need to go do something about this. Excellent. All right. So how do you, so Niraj actually, uh, a two part question. Okay. Uh, the, the first one we're gonna wanna address as well, but the second is nij. Here's something I've, I recognized. I started at Rackspace, uh, in this market in 2008.

Mm-hmm. And from 2008 until 20, I would call it 2017, I'm just gonna grab that as a date. Security was a reason not to go to the cloud. Yep. It was a dry, it was, in fact it was the first conversation. And then also even going into, um, into a managed hosting environment. It started with this, here's why we can do security, blah, blah, blah.

And then all of a sudden it became null for about a year and a half. It, it just wasn't brought up a whole lot. Now people are going to the cloud because of security. So how do you integrate security into, uh, expectations and, and understanding those business drivers? That's a great, great question. Um, and I would go back to.

AWS is answer to that, right? There is security in cloud Yeah. That customers manage. And then making the cloud secure itself is what AWS has invested heavily in. Okay. So by combining those two models, we have this very robust offering here where customers can build their own security solutions in cloud, be rest assured that everything that's they're running on is a in, is, is secured by aws.

Right. And then to your first part of the question, um, treating security in the advice phase for a modernization, we see every application go from idea to production. Right. And security traditionally was the last step before deploying anything into production. It was an afterthought. Yeah, it was. So by modernizing the applications, what we're trying to do is we shift security left.

We leverage all the products and services that Adrian mentioned early on in the cycle, in our development cycle so that we don't have to wait a fortnight before. A launch. We, we make secure solutions every day in every sprint. So that's a strategy we need up front to make it happen and deploy secure solutions to cloud.

Security. Security, security. We talk about the cloud changing a lot, but the nefarious actors. Aren't sleeping either, uh, just like the cloud isn't sleeping. So it's important to really focus on that. So, um, so I love the focus on that incremental change over time, running things in a couple of week sprints like we do with our teams here.

Um, uh, but, uh, those, those nimble teams can be flexible as well. When we think about, you know, dedicating a group of people. But what if somebody needs some deeper help in and around security? Are there, what are your paths to find, uh, subject matter experts that maybe go beyond what you guys have on the teams?

Yeah, absolutely. So, um, as you had mentioned before, with the, the spheres of management, um, uh, or spheres of support. Yeah. Um, we have a lot of passionate Rackers that just are curious already. So, so they're gonna be peeling back the layers of security on their own. Um, but we also have, and not to pitch a product, but we do have a security team, Atlassian engineering for security.

That can be that extension for you. Yeah. Um, so the same, uh, scalable, uh, team, uh, that can, uh, handle your security services for you. Yeah. So, but that becomes important and I was really kind of baiting, baiting the team here because what really, what we're looking. What I'm trying to call out is the fact that it's important to be able to get to subject matter experts in these different areas.

The cloud is constantly evolving and from a security point of view, the threat is always evolving. Um, but I would say from a business point of view, the business opportunities are always evolving. And really there is, especially with a partner like AWS folks, you aren't gonna play stump the chump with AWS and come out a winner.

There is a solution, a technical solution inside of, of that, that book of business, uh, and ca and technical capabilities to really do infinitely anything you wanna do, you can't outthink them. We tried, you can't outthink them. Um, but what I really wanna address now is to think about going back to, um, here, there's a question.

Mitchell has a great question. He says, what are some of the factors to consider when implementing a cloud storage modernization strategy? And how, uh, how can businesses effectively evaluate, choose, uh, the right cloud storage solution for their specific needs? So, uh, I'm gonna give each of you sort of a chance to answer that from your different purviews.

We're gonna start on advisory and work our way back down this time. So when, when a company comes to us with a, with a business challenge in and around their, their, uh, uh, opportunities for storage, how are we helping guiding them down that path? For storage? Yeah. For storage. Okay. Yeah. That's a great question.

I mean, uh, storage is ideally a part of the framework that we use to design that holistic roadmap. Yeah. Um, so your storage kind of like falls under your have, what is the data strategy you have when you do modernization? Yeah. And as a part of that, it's data classification. There's data storage, uh, data encryption, all those factors are handled.

Yeah. As a part of thinking that solution upfront in our advice phase before we touch the keyboard. Yeah. So let's think about it on the AWS side. Storage. What it put me on the spot, Jeff. I actually sit on, uh, to your point, not the jump. I actually sit on our technical feedback community for storage, migration, uh, as well as hybrid.

So this is kind of right at my wheelhouse. So today in AWS we have over 143 security designations ranging from NIST to high trust, pci, hipaa. Um, and the great thing to the question from Mitchell is, All 122 storage services that are capable of storing customer data can be encrypted, many of which by default use infrastructure as code.

That's a simple c l I argument, and it's off to the races. This is one less thing you ever have to worry about. And the beauty of this is no one at AWS not support, not engineering, not professional services, not the service team has any access to this data whatsoever. Yeah. All right. Well folks, you know, I was gonna give everybody a chance to answer, but we're sort of running out of time.

So I'm gonna sum this piece of it up and just really say that I want you to, I'm gonna challenge you to think beyond storage because when we think just storage, what we're thinking about is, uh, how fast do I just need to be? How much storage do I need? Because what we're storing. Is your data. And your data is your most precious asset.

Your data is what's driving all of your ai, uh, goals and, and, and adventures. So think of storage beyond just storage. Think about that data and how it might be utilized and how you might get it to somebody even better, faster, cheaper. Um, uh, dossier asked a question that there's not a lot of modern clouds running in Africa.

How do we solve for that? Well, the way a lot of folks are solving for it is getting points of presence into some of those locations. But at any rate, I wanna personally thank each of you for taking the time to be here today. This has been a, an incredible conversation. I appreciate for those of you who've had to travel in to do this, thank you so much for it.

And, uh, and of course thank you to AWS for your sponsorship of, of not only this, the, uh, this event, but also the, uh, the survey that we went out and did all that research. And folks, I wanna encourage you to head over to Rackspace. Dot com slash solve. That's where you're going to find the, uh, your access to all of that data that we've been sharing.

It doesn't cost you anything other than a little mouse click, uh, but head over to there. You're gonna be able to get all of the data that we've talked about here today, and thank you so much for being a part of this program. I've had so much fun being, being here and sharing it with you, and I hope you have a great rest of your day, folks.

I think I'm taking a week off next week. In fact, tomorrow is when PT O starts. I don't think we're back next week. Watch for a best of episode at some point, or, you know, they're all available in online. Just go watch something if you miss me. You probably won't, but I'll see you the following week. All right, everybody, have a great rest of your day.

Thank you for being a part of this program, and thank you all again for being here today. Thank you so much for listening to this episode of Cloud Talk Live now here at Cloud Talk. We strive to help decode the ever-changing world of technology to help you apply it to your business so that hopefully you'll have one more tool in your arsenal to help improve your business and those around you.

Now, this was a live event, which happens almost every Tuesday and Thursday at 8:30 AM Central Time on the Rackspace, LinkedIn, YouTube, and Twitter accounts. Be sure to watch us there, join the conversation. Live with us. Now if you haven't already subscribed, I'd encourage you to do so and maybe even give us one of those five star reviews.

These episodes can be found anywhere podcasts are found. Until next time, I'm Jeff Diverter for Cloud Talk and Cloud Talk live.