3150: The Future of Cloud Technology: Lessons from Mission Cloud's Approach

[00:00:04] How can businesses navigate the ever-evolving cloud landscape to unlock innovation, scalability, efficiency, all those corporate buzzwords? How can they tick all them off the list? Well, today I'm going to be joined by the CTO of a company called Mission Cloud, which is a leading AWS-focused cloud consulting and managed service provider. And they have deep expertise in cloud transformation,

[00:00:28] AI integration, cost optimization. But today I want to find out more about how they're helping businesses not just adopt the cloud, but actually thriving it. So in today's episode, my guest Jonathan is going to be sharing his insights on the strategies for AWS migration, the power of DevOps and automation, and learn more about how Gen.ai is transforming industries, not just

[00:00:53] through content creation, but also personalized customer experiences. And we'll also tackle the growing importance of cloud security and how businesses can maintain that fine balance between cost control and high performance. So what does the future of cloud innovation look like? How can companies harness its full potential? Let's find out now. So a massive warm welcome to the show, Jonathan. Can you tell everyone listening a little

[00:01:23] about who you are and what you do? Sure. So Jonathan LaCour, I'm the chief technology officer at Mission Cloud. Mission is a 100% AWS-focused partner, and we do professional services, software, managed services, and the whole widget, right? Everything that the customer needs relating to AWS, we do. I've been at Mission since the founding, the founding CTO.

[00:01:47] And my role at Mission has changed over time. I wear whatever hat is necessary. So I've done everything from running our service delivery organization to managing our platform APIs and software. I do a lot of evangelism, and I'm an outward-facing technologist. Mission was just acquired by a Fortune 200 company, CDW, and that happened in the last couple of weeks. So I'm excited about that. And there's going to be a whole new set of opportunities for me to wear even more hats, right? Which I'm looking forward to.

[00:02:18] Oh, fantastic. And my research suggests that Mission Cloud, you focus heavily on helping businesses with cloud transformation. And I always try and leave my guests with some valuable takeaways and maybe demystify some of the technologies that they find overwhelming or daunting. So to get some insights out of you here, what would you say are some of the key AWS migration strategies and cloud architecture best practices that you'd recommend for companies navigating their

[00:02:47] cloud journey? You must see a lot of things done wrong. You must get this question asked a lot, but any advice you would offer around that? For sure. So Mission does a ton of migrations, and they really vary pretty wildly, right? And I think that's the thing where people get in trouble is they think it's a one-size-fits-all kind of approach for a migration, and that's just not true. I think getting started is just understanding what your goals are. How much evolution can you do on the workloads that you're migrating is sort of the very

[00:03:17] first question. Because obviously you can do a lift and shift, you can do light transformation, or you can do kind of a whole rework. And understanding that up front is really important. But the part that is probably shared across everything is having your AWS accounts that you're going to migrate into, configured properly having a landing zone or landing zones where those workloads will land, will be delivered as they are migrated. And that is important because it sets

[00:03:44] out all the guardrails. It sets you up for proper governance from security perspective, all of that. So to me, once you get to that, all the rest is fun, right? Unless it's lift and shift, it can be a little bit boring. But it's not complicated. It's not as complicated if you get it right up front. What are my goals? What workloads am I migrating? How much can I touch them? And sort of what's the time horizon, right? And having those questions very clear up front, it just rolls everything

[00:04:12] downhill from there and things get pretty straightforward. But having a good landing zone from a technical perspective is one of the most important things. Get that, get those guardrails in place, have everything pre-configured and ready for your workloads to land. And I don't want to be a fun sponge here, but cloud security is also a pressing concern for many organizations now, especially when we're throwing AI into the mix as well. But how do you at Mission Cloud approach things like threat detection, prevention and improving a company's overall

[00:04:42] cloud security posture? Again, we're at that time of year, we're looking at doing things differently and improving on things next year. Anything you can share around that? Absolutely. So it's a comprehensive approach, right? Because security obviously is probably one of the most important considerations of your environment in the cloud. I think one of the big challenges that if you look at the cloud providers, AWS included, they will offer cloud native security services. However, they are restricted heavily to the CSPs kind

[00:05:12] of platform. So they help you with the security of the platform and the workloads in that platform, but they don't reach out and extend into other areas, right? And so one of the biggest places where security is important is on employee endpoints. So their phones, their computers and so on, and making sure that they're monitored, but also monitoring, managing and prevention on the AWS environment. And so Mission, the way we approach this is, again, we start with best practices,

[00:05:39] right? And so going through an auditing the customer's environment, we have a fully automated platform called Mission Control. It's a user experience that customers log into. It's sort of our how we deliver service in collaboration with the customer. And when it comes to security, one of the things we do is we automatically scan the customer's environment using a variety of different checks to generate a score. This is your score, your mission cloud score. How good are you doing with your AWS sort of estate, all of the different accounts? And one of those kind

[00:06:08] of deep checks is security. That's based upon the well-architected framework. We do a bunch of different pillars. So very first thing is audit the environment, understand what's going on. Do you have any deviations from best practice? Low hanging fruit, right? After that, there is a lot of consultative kind of work, understanding where does all your data live, right? If we're migrating it, we'll know that right out of the gate. But if the customer's already in AWS, we need to go through

[00:06:34] and understand where's your sensitive data, right? How are you currently managing it? And then the last aspect here is response, right? You talked about sort of threat detection and response. And we have a service called Mission Cloud Secure that is sold through the AWS marketplace, and it's in partnership with CrowdStrike. So the beauty of CrowdStrike is it sort of addresses that first problem we talked about, where security spans beyond your cloud environment. It's all important. And CrowdStrike is one of the few

[00:07:04] vendors out there that really does a great job kind of across that entire spectrum from end user devices all the way through cloud architecture. And then it isn't about making sure that a breach or a problem never happens. I mean, obviously, that's what you want. But what's more important, or as important, I should say, is being able to quickly respond when something actually happens.

[00:07:30] And I say when it happens, not if it will happen, because everyone is going to have a security incident. It is, you can do everything in the world to prevent it, but you really need to tabletop it, make sure you have incident response available. And that's what we do. So we put CrowdStrike into customer environments, we light up a bunch of AWS kind of security. And then if something pops, or when something pops, we are all over it 24-7 teams. So a lot of customers have that kind of capability

[00:07:56] in-house. A lot of businesses do. But that's one of the things about being a partner is if that's something the customer doesn't have, we can absolutely provide that for them so they can focus on creating value, building out their workloads, their applications for users, whatever it happens to be. And another thing rising in importance is DevOps and automation, widely considered crucial for agility, scalability, something that every business is chasing right now. So how do you help businesses

[00:08:23] maybe automate some of their infrastructure? And what are you finding are some of the tangible benefits that this brings to their operations? I'm curious what you see here too. Great question. So yes, DevOps, obviously, and a lot of different tools that are associated with DevOps, hypercritical for getting customers for getting any business to a level where they can take full advantage of the cloud, right? If you're doing just a lift and shift migration, you get some value

[00:08:49] out of that. Like for example, if you are currently paying a lot of money, you have a huge capex for on-premises infrastructure, you gain the benefits from the billing side. But to really fully unlock all of the value and the benefit of the cloud, you really do need to have the ability to do continuous improvement, CICD pipelines, infrastructure as code, all of the DevOps principles. You want to be

[00:09:13] able to deploy at will with confidence, right? As many times as you want, multiple times per day, often dozens of times per day. And so that is something we help customers with as well. I think getting back to our earlier conversation around the migration and understanding the strategy. If one of the things that is part of the long-term or mid-term goals for that migration is to take full advantage of DevOps principles and build out a CICD pipeline or 10, that is absolutely something we do. We have

[00:09:43] effectively a managed DevOps service called Cloud Elevate. And we have a team, a fractional team of super smart AWS folks across a bunch of different disciplines and skills, and we can flex in and out of different things at the right time. And it really is all focused on that continuous improvement, that DevOps kind of approach. Advantages are many and alluding to my reference around multiple

[00:10:07] deployments per day. It's agility, it's velocity, it's the ability to continuously improve and to be able to have the advantage of things like spinning up an entire staging environment and then destroying it, right? And seeing, being able to kind of poke in product to understand what it looks like. And I think there's tons of benefits here. I think velocity, agility, and then the ability to use that infrastructure's code to help you down the journey of spinning up environments, doing tests and

[00:10:36] development, destroying it all, and have it be a replica of your production environment, right? And one of our customers we have done this for is the Boston Celtics. The Boston Celtics are a wonderful organization, but they are, and they're large, right? They would definitely be considered a enterprise, right, in the categorization for a customer. However, their technical team is very small, and they do a lot of amazing work around basketball analytics, sort of like money ball for basketball.

[00:11:06] And they were started off in on-prem infrastructure that was in the CTO's office, big iron, just kind of keeping him nice and warm in the Boston weather. And eventually we migrated that all and we did a lift and shift with light modernization. And now they're all the way down the path of on-demand push button multiple time deployments, spinning up test environments, iterating. And so it's been fun. That's a good example for me of a customer that went down that entire journey and is now reaping all of the benefit.

[00:11:35] Apart from the guy that sat there now feeling a little bit cold, right? Yeah, Jay, the CTO over there, and he's going to have to put on a jacket now, but yeah. Love it. And another thing that's increasingly popular is building cloud-native applications. So any advice you'd give to any businesses maybe looking to optimize serverless and containerized applications and how you support these efforts too? I think this is one of my favorite topics because I'm a nerd and I'm a programmer, right? I've been

[00:12:04] writing code for many years and I get very excited by AWS kind of platform services, right? Things like serverless Lambda and all of these APIs that you can build out containerization, all that goodness. And the way that I explain this to folks is that in the back in the day, we used to have SDKs, right? We would have a library that we could use to assemble an application. We would take

[00:12:30] capabilities that are in the libraries and the SDKs and do things, right? And that was part of the architecture of your application. The cloud represents an SDK as well. So AWS has this massive number of services with APIs. Everything is API consumable. And now instead of just looking at your SDKs that you depend on, you can say, hey, what are all the capabilities I have in the cloud? Now my software

[00:12:54] architecture can lean on and leverage things like AWS Lambda, right? And I can say, hey, I'm going to put all of this code in Lambda. And now your architecture and your infrastructure are aligned very tightly. And you've got a lot of different benefit. Like for example, one of the benefits of Lambda is this sort of automated scaling up and down. And yes, there's things that you can do on an automation basis to kind of help AWS do it better and eliminate things like cold starts. But one of

[00:13:22] the best things about Lambda function is you have what I call granularity of cost, right? You, if you have a workload that is a massive monolith that's sitting in AWS and you want to identify why your costs are too high and you've got like everything chucked on EC2 instances, and it, there's nothing that is using the native capabilities of AWS, you're losing a lot of, of that insight. Your developers and engineers are not going to be able to come to you and say, if we optimize this part of the code, this is

[00:13:50] what you will get out of the other side from a performance and a cost perspective. When you're using something like AWS Lambda, every function, every little component of your workload gets very granular. And you can say programmers love to refactor things and we're often not allowed because of what's the ROI. Well, now if you have your code in Lambda, if you have some code in there where you are hitting it on a regular basis, you can see precisely how much money you are spending on a monthly basis,

[00:14:18] on an hourly basis, on that chunk of the code of a much smaller chunk of the code. And then you can go to your teams and say, hey, we're currently spending $25,000 a month in these six Lambda functions. If we go and we optimize them, we can reduce that cost to $1,000 a month, right? And it is the best ammo for technical teams to go and say, hey, we should refactor. And yes, there is ROI. So it goes

[00:14:46] beyond just the benefits of deployment and operations. Those things are absolutely there as well to reduce the need to manually deal with the servers and the management and the scaling. Just make it all automatic for me, please, with Kubernetes, Lambda, whatever it happens to be. And of course, if you scroll down your newsfeed at the moment, you're going to see so many different stories of how data analytics combined with AI and ML are transforming industries. But I think there's so

[00:15:14] much hype around it that it can be very difficult to understand what kind of difference it could make. And there's an increasing focus on ROI of every tech project now. So what would you say are some practical use cases of AI and ML integration that you've seen and seen some of those tangible, measurable differences that it's made too? Yeah. So Mission does quite a lot of AI, machine learning, data, and generative AI right now is quite obviously the hot topic. And our practice around that has

[00:15:44] is led by a guy called Dr. Ryan Reese. Dr. Reese has been in this space since before it was cool and knows everything inside and out in terms of how to drive value because you're not just doing it for fun. You're doing things to achieve a goal. And like you said, there are lots of different use cases. We have done, I believe, more Gen AI POCs and production delivery than most any other partner in the

[00:16:09] ecosystem. And as a result, we've worked on many different use cases that are exciting. There are the classic use cases that people understand like a chat bot, right? But there are a lot of others as well. So one of our examples is a customer called Magellan TV. Magellan is a documentary company, right? They produce hundreds of hours, thousands of hours of documentary footage on a variety of different

[00:16:34] topics, very good content. It's amazing. And it's all in English. They wanted to go global. And in order to get subtitles produced in different languages, you would have to go to a service. And those service would use people and they would listen and write and translate. And you'd have to do that on every single language that you want to translate for. And so it was, there was a huge obstacle to them.

[00:16:59] It would be a massive amount of cost to achieve going global. And so we actually use generative AI and AWS native services to help this be a completely automated process. And so we are now able to take the voice, transcribe it to English, then translate it to another language, and then use generative AI to achieve things like summarization. Because if you're doing captions and you want to align those

[00:17:24] captions to the words that are being spoken, different languages have our different verbosity, right? That's what I would say. So for example, if you are translating an English topic into Mandarin or German, you may have a more wordy kind of output. And so being able to go in and say, hey, generative AI, large language model, here is a German phrase. It is too long. Please provide me, say this more succinctly. And it will do that, right? And summarize it. And then we know

[00:17:54] that we can fit that line of text as a caption in a natural way within the content. And so I think people like generative AI isn't just, I'm going to go do a gen AI project. Generative AI is, I have workloads that need to achieve a goal, right? And I'm not just using gen AI in that example. I'm using transcription services within AWS. I'm using text-to-speech and the other direction.

[00:18:19] And so it's a part of any project. It unlocks new capabilities and opportunities. So I've got dozens of other ones of those that are really equally cool, but I am personally very bullish on the future there. I think once we get past the mode of your board coming to you and saying, you need to do something with gen AI and get to the point of what problems are we trying to solve? Now I have this amazing, powerful technology as a tool in my tool belt that I can integrate into

[00:18:49] my workloads. I think that's when you really start seeing a massive advantage, right? Versus a lot of proof of concepts, which are also good, but you know. Yeah. And I think those use cases like the one you just mentioned are so valuable, especially to people listening. So of course you did say you've got a few others. Any other examples of how you're leveraging AWS to support gen AI models and any innovative use cases you're

[00:19:14] seeing, whether they are in automation, content creation, or customer experience, anything else you could share there? So another use case that we deal a lot with is around personalization of content. So for example, a real estate business who manages the MLS listings and wants to send their customers a custom, hey, you may be interested in these properties, but doing it in a way that is

[00:19:40] very personalized to them. And that is a content consumption and generation activity, right? And so understanding from a metadata perspective, what does this customer express that they're interested in? This location, this number of bedrooms, these specific features, doing some backend prediction on what, which properties the customer is likely to be interested in, and then generating a custom

[00:20:05] newsletter for them via email that says, you are searching for a wonderful house with a view and a pool. You need at least four bedrooms and this property in particular matches up really nicely. And here's some great things about it and generating content in order to make that a more effective, targeted email to the customer. It feels very bespoke. It feels very much like you have a person

[00:20:31] on the other end who cares about you and your goals. So personalization is definitely a big one. And then a lot of ability to unlock insights out of massive pools of data is another one. So we've worked with a bunch of private equity firms that track hundreds of thousands of businesses globally, and they're gathering data from so many sources. And in the past, they would have to have some of their employees go and do a lot of manual work to say, which of these businesses that we want to

[00:20:59] potentially target is a good fit for us from an investment perspective. And now we are taking that data, we're able to run it through generative AI through models to actually process and summarize the information and to surface data much more quickly, right? And much more accurately. So now that you can keep tabs on hundreds of thousands of businesses, they can interrogate their data set using chat, they can set up rules around things that they're interested in finding and produce reports that are,

[00:21:30] again, they look bespoke. It looks like your interns are doing a fantastic job, right? And they are, but they have the tools now in order to achieve those goals. So I think it runs the whole gamut, a whole spectrum of opportunities. AI and ML now are at a point where you can do some pretty magical things. And personalization, summarization are two of the big ones. Yeah, they really are. And one other big one before I let you go, of course, is cost optimization

[00:21:57] remains a key challenge for so many cloud users out there. So any strategies that you'd recommend to better control those rising AWS costs while also maintaining high performance and scalability? I appreciate that's probably an entire episode on its own, but anything you could leave people listening with that? Sure. So look, cost optimization, I think one of the biggest challenges that companies face is they treat it like a activity that happens every once in a while, right? And so I'll look at my costs,

[00:22:27] I see that they're going bigger than I want, I'll go buy a bunch of reserved instances, and then check, I've done that for the year for the quarter, whatever. And that's just not the approach, right? You need that to be a continuous activity. It's part of what you do. The benefit of the cloud really is this automated infrastructure at your fingertips using APIs on demand, right? The challenge with that is you can get yourself into deep trouble pretty quick,

[00:22:52] right? And so governance is really important. And also contextual recommendations, I think, is really important, one of the ways that we help our customers. It's important to be targeted. So for example, if a customer is using a tool that may spit out, hey, here are 100 EC2 instances that are on legacy flavors, we need to move those to new instance types to save you money, or you have these EBS volumes that you that aren't performing right, or over provisioned, whatever it happens to be,

[00:23:21] you're going to get a list that's larger than you are able to handle, right? At least in an immediate fashion. And so prioritization is really important. And one of the things we pride ourselves on is adding business context to those technical recommendations, there are no shortage of platforms out there that will tell you, I think this is right for optimization. But it doesn't know, for example, that workload is one that you are sunsetting in three months. And so you only want to do low

[00:23:47] hanging fruit there, you don't want to invest a bunch of engineering time into doing cost optimization activities, you want to take those limited resources you have and toss them at the right work. So to me, it is treat it as a process is a continuous journey, and always have some governance in place to ensure that your costs remain in control. And then apply business context to the output you're getting from tools to optimize and prioritize those activities.

[00:24:14] I love that. You've shared so many insights today that will be useful when I think so many people listening are struggling with that real pressure on us all to be in a state of continuous learning. Now, as someone leading the way, though, a question I've got to ask is, where or how do you self-educate? How do you keep up to speed with all this stuff? Any tips there? Yeah, absolutely. So look, I have an admission to make, which is that I still write more code than I

[00:24:38] probably should. That is how I have always learned is by building by doing. And it's really critical for me to find time to do that. And so I've been writing Python for, gosh, decades now. I started when it was in version 1.4, and I was like 15 years old, and started doing it professionally back then. And I'm still using it today. And I do a lot with AWS. I recently did a fun project where I created a

[00:25:06] AI-powered movie poster in my home. And it's effectively a big television rotated on its side. And then I can have it listen to me. I can say, what should I watch today? And it can go and pull from the information that I have and show a poster for that and then tell me why. I can say, what do people think of this? It will go and fetch reviews from public sites. And then it will summarize all

[00:25:33] of those reviews to tell me what people generally think about it. And it's a lot of fun, right? And so I do a lot of projects like that, because it keeps me excited and motivated. And technology is fascinating and wonderful. And yes, it's good for business transformation and all of that goodness. But at the end of the day, I still have that spark of delight when I solve a problem, even if it's just a fun problem, using code. And so that's how I stay fresh. I stay motivated,

[00:26:00] always trying to build new things and explore. Oh, man. Is that a video for this anywhere online? There is. There's a video available on YouTube that I can send you that. There's also an article I wrote. I have a newsletter that I periodically post on LinkedIn when I have one of these projects. I've done lots of fun ones. I did an AI powered music box for my daughter. I do location tracking

[00:26:25] 24 hours a day from my phone about where I am, what my battery is at, if I'm connected to Wi-Fi, am I moving? How fast am I moving? What's the elevation? And I am doing all sorts of summarization against that. Yeah, I've got a lot of fun examples. But the YouTube video is great. That's a good place to start a quick overview of what some of the capabilities are. Well, separately, if you can send me a link to that YouTube video and your blog, I'll make sure all that is on the blog post associated with our conversation. I'd love for

[00:26:54] people to check that out. I'm going to be checking it out. And regarding Mission Cloud, though, anyone wanted to find out more information about that and the things we talked about today? Anywhere in particular you'd like to point everyone for that? Yeah. So Mission is available at missioncloud.com. You can definitely find us there and reach out. You can see sort of all the different things that we do to help our customers be successful in AWS. And we definitely have lots of opportunities for you to kind of connect with us on newsletters. So we

[00:27:20] have a fantastic regular newsletter from Dr. Ryan Reese, who, as I mentioned, is the head of our practice around data analytics, machine learning and AI. And that's a wonderful way to sort of learn at no cost, right? Just sign up for that, get some information, and then learn about what the potential is for transformation of your business. So that's how I would suggest to reach out, hit that website, sign up for newsletters, look at what we do. And we're always happy to have a conversation with anyone about how we can help them out.

[00:27:50] Awesome. Well, I'll add links to absolutely everything there. I've just loved hearing more about how you're helping businesses optimize and innovate using AWS. We could have so much from data analytics, AI, ML, leveraging AWS for generative AI models, but also bringing it to live with some of those use cases in content creation, customer experience, and also tackling the problem with cost optimization. And you've even left me with a teaser. I need to be watching this video at the end of our conversation. But more than anything, just thank you for sitting down with me

[00:28:20] today. Yeah, it's been an absolute pleasure, Neil. I love technology. It's such a wonderful thing for me and so much excitement. And finding ways to help people with it and solve problems and talking about all of that is so much fun, right? So thanks for having me on. Really appreciate it. As my guest highlighted today, the cloud isn't just a tool. It's a catalyst for transformative change across every industry. From leveraging AWS for generative AI and data analytics to

[00:28:46] optimizing cloud costs and security. The possibilities are vast and dynamic. Yet navigating this complex environment requires good old-fashioned belts and braces approach to IT, clear goals, tailored strategies, and the right expertise. So thank you to my guest Jonathan today for sharing his insights. But how do you see technology shaping your organization or your industry? As always,

[00:29:15] let's keep the conversation going. Lovely to hear your thoughts. Tech blog writer at outlook.com, LinkedIn at Neil C. Hughes. Let me know. But that's it for today. So time for me to get out of here. I'll be back bright and early tomorrow with another episode. But thank you for listening as always. Speak with you all tomorrow. Bye-bye.