Long-term Remote Workforce Enablement and Cloud Adoption: what you need to know

Organizations are being guided into the cloud and empowered to utilize data effectively to optimize their operational performance. In deep detail, Jim Haas, VP of Data Services at Ntirety, explains how Ntirety assesses their customers using an effective maturity model to maximize their potential in the cloud.

Episode Transcript:

INTRO: [00:00] Welcome to the Tech Deep Dive podcast, where we let our inner nerd come out and have fun getting into the weeds on all things tech. At Clarksys, we believe tech should make your life better, searching Google is a waste of time, and the right vendor is often one you haven’t heard of before. 

Max: [00.18] Hi I’m Max Clark and I’m talking with Jim Haas, who’s the Vice President of Data Services with Ntirety. Jim, thank you for joining.

Jim: [00.27] Thanks for having me Max, I appreciate it.

Max: [00.28] So Jim, we were talking beforehand and you’re now the Vice President of Data Services, but before that, that was Managed Services, and before that that was Professional Services, and before that it was Databases… So, I think it’d be a good place to start, just talk about Ntirety and your role with Ntirety and how that has evolved over the past few years and how that fits into the grand scheme of things with Ntirety’s cloud practice?

Jim: [00.52] Yeah, so it’s interesting you know, over the course of time, Ntirety has morphed based on the needs of the industry. Initially it was a very heavy — actually, Ntirety itself goes back twenty years ago, and it was just a remote database administration and consulting company, which then ultimately got acquired by a much larger infrastructure and cloud operations company, it then rebranded as Ntirety. So, my role really has transformed from the database managed services to consulting services, to bringing both these two together in a synergistic way, because there are so many ways in which consulting and managed services play off each other. And I think as the conversation goes through, we’re really going to talk about how all these different pieces come together. And it’s not just about the data… So, you know, you hear — you read the articles and the articles say, “Well, information is the lifeblood of companies,” and that’s really true, but that information, that data has all these other components around it. It’s got the need for infrastructure, for cloud ops, security and compliance, all these other pieces that actually protect the data, make the data available – not just for transactional activity, but ultimately for analytics, making complex business decisions, competitive advantage… All of these things play into a cycle of data, and we’ll get into a lot of  the different details. And so my role has really transformed from strictly remote database administration company, to… we’re consulting and advising you and getting you to new places, modernizing your architecture, getting you to the cloud, which is one of the big paradigms that we’re all dealing with right now. And then of course, making sure that you’re safe, secure, monitored and managed when you’re up in those environments. So, these all play into some of the areas that I’m responsible for, and all of the areas that Ntirety as a whole is responsible for.

Max: [03.22] You talk about the merger that formed Ntirety, and part of that was – what still is a datacenter, physical equipment practice; so customers could take equipment to your facilities or you could manage equipment for your customers in your facilities, and then there’s this practice around the different public clouds, and you know, when you’re engaging with customers, are they driving that conversation of, “We still want physical hardware, we just don’t want it to be on premise,” or, “We’re switching to the cloud and we need help,” or, “We’re in the cloud and we need help.” What does that lifestyle – that lifecycle really look like for you and what you see?

Jim: [03.59] It all depends on the customer. So, one of the things that we do is – and you’ve probably heard this before – you know, like Gartner for example has a maturity model for things like business intelligence. And along that model, customers become more sophisticated, more capable, and depending on where a customer is in that model, really determines what exactly they need and how we guide them. Many times, they’ll come to us and they’ve got a set of thoughts in their mind about how they want to do things, but they have not thought all of those things through, and this sort of leads to another problem that customers deal with – or companies deal with – it’s called the half-an-SME problem. This could be a half a DBA problem, half an architect problem, where you’ve got your set of expertise and they know what they know, but you don’t have the full suite of expertise to tackle the whole entire problem, and where we come in is… We’ve done this, many, many, many times. Many customers are coming in, they’re either taking their first crack at, say for example a re-architecture of their environment up into the cloud, or hybrid… You know, a lot of times it’s an intern step where you’re doing on-prem and you’re doing cloud – possible multiple clouds: AWS, Azure, you name it, and they don’t know all the pitfalls. And this is where we sort of classify our customers into these maturity levels; we’ve got four of them. At the very beginning, you’ve really got rudimentary: you don’t have controls in place, you don’t have security hardening in place, you don’t even have standardization of builds in place. A lot of times, silo departments will build their own servers their own ways, and these lead to security vulnerability holds, inconsistency in performance and availability – that’s the sort of low level. And then you get into the next level — and most customers sit around one and a half to two, where they’re starting to get more sophisticated, they’re really starting to build templates, they’re getting smarter about security and not taking the path of least resistance on things like administrative accounts. They’re starting to get better at what they do. They don’t know everything, but they’re learning from the mistakes of the past or through their own research. Then you get beyond level three, where you’re really starting to get your stuff together and you’ve covered a lot of it. Maybe not a lot of it, because you don’t have all the expertise in-house, but you’re covering a lot of it, and then at level four you really are competitive with everybody. You’ve done this multiple times, you’ve got a really strong IT team, you’ve got a really good program in place, things for risk management, creating golden images for your servers, whether they’re app servers or database servers, or just… You know, how you set up some of your other IT equipment, and that is a very strong program that generally needs the least amount of help. So, what we’re seeing with customers is, there’s a vast array of experience somewhere along this trajectory, and in some cases we – as we get into this data, or this data and this maturity lifecycle – there are some areas where we spend a lot of time up front, in discovery, assessments, architecture, and then in others, it’s really more… Tweaking, you know? We fill in the gaps, or they might not have the gaps, and we help them implement, we help them head off the problems that we’ve seen, because we’ve done many of these. So many of these that, you know, a lot of the things we can see a mile away; we go into an environment and we know to look for it, and we can help a customer solve to that dependency or that problem before they ever even get to the point of deploying something and then finding out that it’s not going to work, or it’s vulnerable, or it’s going to break, or it’s going to perform… Not to expectations. Conversely, they’re going to over-provision and waste a lot of money. So, these are the types of things that we do: we really have a program that analyses where a customer is in this maturity journey, and we spend a lot of time understanding that with upfront discoveries and analysis of their environment, and once we know where they’re at, we can then tailor filling in those gaps and trying to make their migrations as seamless as possible.

Max: [08.48] And the scale of cloud — this is no longer a conversation about whether cloud is or is not appropriate, right? We’re just talking about, are you in the cloud and what level are you using cloud infrastructure today? So on the scale of that, you have this very basic approach of, “Okay, we’re going to virtualize on-premise equipment, and we’re going to bring it off-prem and bring it somewhere else,” right? And this becomes like this very… Like, low-level cloud migration. On the other end of the scale, you see cloud native companies – and usually these are internet companies that started in a cloud provider environment, they’ve always been there, maybe containerization or have already gone serverless, and there’s a big chasm in between those two points, in terms of what enterprises actually could use, or need, or how they become more efficient. So, how do you help them — how do you help a customer get from – just looking at this from… We’re going to switch from a capex to an opex cycle, and from an on premise server to virtualized VM, and to actually taking advantage of things that are available to you from a cloud environment?

Jim: [09.52] Yeah, so that’s in many cases a big initiative, it coincides with a lot of different things, you know, the old paradigm in application development was monolithic applications. You build one big application, one big database, and sure – you can lift and shift that up into the cloud, you’re not taking advantage of all those cloud services, you’re not taking advantage of breaking down functional areas of the application into smaller services, which then you can also scale very easily. And so, that change requires some of – you know, a significant amount of upfront discovery and architecture. I’ll touch a little bit on it now, so you know I talked about this lifecycle, this lifecycle of infrastructure and data. The first stage is assessments and discoveries, and assessments are… They’re pre-canned, they’re targeted at things like, for example, cloud readiness assessment – that’s one of our number one assessments right now, it’s ‘are you ready to go to the cloud?’ You know, you’re talking about containers and services, but there’s also even other areas such as, ‘are you in an IaaS implementation and should you move to a PaaS implementation?’ You know in many cases, you might want to abstract out that operation system layer, and not have to worry about that; simplify your maintenance, simplify your management – but it’s not that simple. Now, it’s gotten better… You look at where it was five years ago, there were entire feature sets, and take for example SQL server, like SQL server agent jobs, and SSRS that you simply could not put in a PaaS instance, and so you had to design an IaaS instance to do all that work remotely – that’s changed. All of these things have changed over time, the feature set of platform as a service has increased dramatically over the last several years. So, these are all the types of decisions that have to be made, and when we’re doing this first stage of the life cycle, we’re doing a lot of these assessments to mine out what are your dependencies? If you’re going to go to PaaS, for example, you’re going to go into the cloud, you’re going to move to a PaaS infrastructure because you believe, “I’m not going to have to manage as much,” it’s going to be easier, but your existing application for example is targeting the OS… It could have a command batch file or a PowerShell script that wants to go in and interrogate something in the operating system — you can’t do that in PaaS. So, there’s all these dependencies; customers don’t think about this, and our cloud readiness assessment, which is part of this initial phase of the data lifecycle, is we go in and head off these dependencies, and we come back to customers and say, “Here are the things that are not going to work for PaaS, here’s your alternatives: you can either redesign this particular ETL function or this job function or this piece of code so that it’s not doing things the same way it’s doing now.” So there are shifts in the way that we have to do business, how we have to execute code and manage the interactions between applications, databases and the OS, and if we account for all of that, then we’ll have the successful migration. Another such thing that we uncover in things like… You know, cloud assessments… We had a customer that was about to do a very large lift and shift up into Azure, and an oversight on their part was that they had hard-coded into the application all of the connections, and those were all going to change. As soon as that got up there, everything was going to break. So, these are the types of things that – since we’ve been doing this for so long – it’s a part of our checklist of, you know, things that we take a look at, and let customers know that if you want to take this route, these are the things that need to be changed, or else you can go an IaaS route in the cloud, that’s obviously something that can be done if, you know, you’re not ready to take advantage of all the services, containerization… This is a process of steps. But then what happens is, you get beyond the assessment and in the next phase of the life cycle, it’s architecture, and architecture is really where you’re redesigning, refactoring your application, your database, how things interact – even your high availability and your disaster recovery, whether that’s taking advantage of new functions in the cloud, whether that’s simply utilizing functions that you weren’t utilizing before, built into a particular software engine. For example, we’ll just take databases, they’ve got high availability and disaster recovery built into them, in many cases that’s not leveraged. But you get up into the cloud and you might want to leverage that – the same thing happens even outside of the application. There are functions like availability sets, and while Microsoft will say, “You really should configure availability sets,” a lot of people don’t do that. You know, a lot of companies don’t do that. They simply put their stuff up there and then there’s a maintenance event, something goes wrong, maybe a network card goes flakey and your application is down. Well, it’s easy with something like an availability set, but not everybody has the expertise to think about that, put that into planning, and make that part of the migration plan. So, these are some of the things that we’ve learned over time because where customers have done this, maybe this is their first crack at a migration, or they’ve just done very few, or it’s been dragged out over time… We’re doing them constantly; hundreds of these migrations. When you do that, you learn these mistakes and you build them into your processes going forward. So, these are some areas where customers really can struggle up front, even if they’re sophisticated, they might not have thought of everything just because they didn’t do many of these, and since we have, we can bring a lot of value into that sort of mitigation up front, of risk. 

Max: [16.29] So, an example of the assessment of having hard-coded connection strings… That’s something that once you’ve experienced it the first time you have like, “Okay, note to self, remember to always check for this in future.” But when I think about enterprise applications, especially something that’s been running inside of an enterprise for years, you’re talking about layers of technical decisions and configurations that probably doesn’t even have a map any more. You know, if you’ve implemented something five years ago, and nobody even knows why it’s running that way, where it’s running, what’s even happening with it… How long — I mean, when you start an assessment, you’re not going to discover everything, but how long does an assessment process take, and what does that really look like with the customer, of trying to say —  okay, are you literally giving them a checklist that has five hundred questions on it, or… You know, is it more about the application and the environment and the processes and what the business is doing, or a combination of both?

Jim: [17.26] It’s a combination of both, it really is – and the assessment isn’t necessarily high-level, there are levels of that assessment. Some of it can be simply the best practices, some of it can be PaaS versus IaaS options, but other ones are a lot more detailed, and actually, we sort of use a little bit of a different term, we then move away from the assessment term and more to the discovery term, because in that particular case, we’re looking at how the application is operating, we’re looking at how it’s interfacing with the database, and then we’re looking for things that won’t work when they migrate up into the cloud. So, it’s a much deeper technical dive; I would say assessment is a very formulaic approach to things that we know fit — you know, like a checklist, but I would say a very deep checklist, and a discovery is really… Not so much following a checklist, we’re following the workflows, we’re following the interactions between – for example – an application and a database, and we’re looking at all the different pieces technically, and how they fit together, and then from that we make architecture, we’re raising awareness of things that could be blockers to moving to the cloud, or we will make actual redesign recommendations. And in some cases, that can be very hard – if it’s a vendor app, you might have very limited things that you can change, and if it’s an internally developed app, you might have quite a bit of control over what you can change.

Max: [19.07] I mean, what’s the ratio of that right now that you’re seeing? How many of these are internally developed apps and how many of these are customized, you know, ERPs or something that a company has?

Jim: [19.15] The ratio’s hard to say, you know… What’s taking over the industry right now in a lot cases, are moves to SaaS. So when you’re talking about vendor apps, and you have a cloud initiative, many of those types of applications are also moving to a SaaS format, but there are an awful lot of custom-built applications out there, still many, many custom-built applications. I don’t know what the actual distribution is, I can tell you that we do so many discoveries and assessments, and there’s still a very high percentage chance, I mean still a high percentage number of internally-built applications, or at least customizations to applications. You know, you might have an application somebody has built C# services on top of it for ETL functions, or for API poll-ins, to bring data into a data lake or some other ODS or repository. So, you’ve got the app and then you’ve got all the other stuff that’s surrounding it, and some of that might be things that are really good targets for making to, for example, breaking them up into Azure services.

Max: [20.32] If phase one is assessment and phase two is discovery, and you said this is a four phase process usually, I believe… What are three and four?

Jim: [20.41] So it’s a five-step process – so you’ve got assessments, and you know, where there’s lots of recommendations that come out of that, then you’ve got the architecture phase where you’re actually designing the new environment, and before I move on from that, that design can also be, you know, new high availability, new disaster recovery, utilizing new features, it can be upgrades; in many cases, a lot of our customers going to the cloud are on old versions, and you go to the cloud, some of those versions, you can’t even put them up there anymore, especially those that have waited for a very long term, or those that have… Let’s say, Windows SQL 2008, Microsoft Azure’s throwing you a bone for security enhancements for a little bit longer, but that doesn’t change the fact that it’s going to go away, you have to start upgrading, and it’s been an impetus for a lot of companies to actually take that step when they’re finally doing that migration and to upgrade as well. So, that architecture phase is all about taking advantage of new features, and a lot changes from version to version, you know? You have compression, you’ve got encryption, you’ve got new HADR features, all of these new things come out as you move across different versions, and ultimately companies are making decisions to take advantage of that stuff, because they have to upgrade as part of this migration. So you’ve got this, you know, this architecture and design… Stage three is really the go do it stage, we call it implementation enablement… You did all this great analysis, and you have to go make it real. You’ve got to go ahead and take it, and deploy it. This in many cases is going to be your infrastructure, your security, whether that’s hardening, templates; everything that you need to do to get it up there, installed and protected according to best practices and the other standards that you follow, or are required to deploy for the customer. So that’s actually a pretty simple phase, I mean it does have many iterations to it, but let’s make it happen. And then second to last, you get into the managed phase. So, you’ve spent all this time designing, all this time assessing, you went and put it all out there, we don’t just let it run; at that point, you really have to monitor and manage it. The key is, all that data, all those applications, they’ve got to be available, they’ve got to be performing, you’ve got to be looking out for things like, “Am I spending too much money? Do I have performance problems or are they sized properly?” All of those things – and you try to head off a lot of this in those architecture phases – but when you get up there, you’re going to have to make adjustments. So you get up there, you put monitoring in place, you respond to alerts, you respond to potential user complaints about performance, all those things that you’ve got to do to make sure that a, it’s performing, and b, it’s available. Those two things are absolutely critical. And then beyond the managed phase, you’ve got all this data, you’re protecting it, you’re managing it, you’re doing daily care and feeding on it. Now you get to the really neat stuff, and that’s leveraging that data. You know, it’s one thing to have a bunch of transactional systems that do things like… Okay, you’ve got card readers to let people in and out of buildings, you’ve got payment processing systems, you know, those all have database backends and applications, but when you start looking at your CRM systems, and your finance systems, and in many cases even your operations systems, and all the other ones that tie into that, you’ll now want to start taking all those disparate pieces of data, you want to take it, bring it in, standardize it, do all the data engineering on it, model it for analytics, and then really get business insights out of it. Those business insights can be everything from… We’ve got manufacturing environments, where they want to predict based on a certain amount of runtime and sensor data, when is this machine going to go down? We can’t afford to have a machine go down, so they will do maintenance ahead of time. In retail, what products sell best during what times of the year? What competitive advantage can I get against, you know, other companies that I’m competing against? That leveraging of the data is where it is more than just reports, this is really where you’re taking many different data domains, bringing them all together in a way that you can put all that data together, and make really, really interesting business decisions, and get really interesting business insights out of it. So that’s really the whole lifecycle, it’s high level assessments, it’s architecting the future state, go ahead and do it and deploy it, manage it and make sure it’s always there, and that if there’s any issues, you can resolve them quickly via monitoring in a fast cloud operations escalation system, and then finally leverage that data for competitive advantage. 

Max: [26.22] What strikes me as you’re talking about this is the description is way more involved than just, you know, a company that’s going to help administer, migrate, manage, you know we hear these things a lot, “Oh, we’re going to help you manage your cloud environment,” or, “We’re going to help you do cost optimization and cost control,” and when you start getting into the nitty-gritty here, you know, helping somebody figure out what their data lakes and data warehousing and reporting processes are… I mean, that’s not admin work. This is getting to be some really interesting stuff here.

Jim: [26.53] Yeah, it is, and that’s where I think we’ve really married consulting and managed services together extremely well. There’s such great synergies between the two, and some, you know, companies will only take you so far. We take you through the whole part of all of this, and interestingly, when we look at customers and their maturity – we talked a little bit about maturity and sort of where they are, you know, along that scale – that maturity level is different for security and compliance, it’s different for cloud operations, it’s different for business intelligence and analytics, you know, it’s different for all the different things that basically make up the IT ecosystem and the service around it. And so, where I think we really shine is that we span the whole entire lifecycle. You know, we’ll get into — I can’t tell you how many times we’ve gone into a company where for example they already have data scientists, and if you’ve already got data scientists, phds, that are already doing really high level algorithm work, you know, to try to do predictive analytics on some function in their business, for an education system it might be collecting data to predict the dropout rate, what is the propensity of a student to actually complete the courses based on their grades, their attendance, their interaction with counselors – all these different types of KPIs give them, you know, insight into… Which students do we need to reach out to and talk to and try to head this off before they finally just quit school? So – and this is just one example – and this is where we’ve got the experience, we’ve been doing this for so any years that when we architect the initial solution, we’re thinking all the way through to the end, if we know the customer is going that route. Now, some customers aren’t sophisticated to be thinking about the leverage phase of the life cycle, they’re just not there yet. They might have SSRS reports, or Crystal reports, you know, Cognos, and that’s fine. But you still need a respiratory for that, and so we just… We help customers see the big picture, we – at the very early stages, we bring up the things to them that they certainly have not thought of. In many cases, they’re just thinking, “I’m going to lift and shift -” maybe just part of their environment; today, hybrid environments are still common. They’re going to lift and shift, okay, so what’s the next thing? You lift and shift, how are you going to monitor these two disparate environments, how are you going to connect these two disparate environments? You know, what’s your security and compliance and your risk program for these two different departments? And a lot of times, those answers, they just haven’t gotten that far, they’re thinking, “Well, I’ve got a VM, I’m going to move it up there, and it’s going to work.” But it’s not quite that simple all the time. There are all these other things that have to be considered, and the fact that we operate across this whole trajectory of how data is protected, implemented, and then leveraged, we’re just five steps ahead, just because we’ve done this so much, and I think this is where we really help because we uncover a lot of problems that customers just – they don’t see, they don’t see these things ahead of time. You know, I’ll focus on another type of example which is in the security space. Security is obviously an extremely hot topic right now. Yeah, it’s one of the – if not the – hot topic right now, and we deal with a lot of customers, you know banks and payment processors and other types of companies that have to conform to security hardening standards, and we’ll get in there and we’ll take a holistic approach at the whole entire environment, find out that they checked all the boxes on their list, and yet there is so much more that isn’t done. I’ll give a database example, where a customer really felt they had this server locked down, they did some of the good steps, they reduced features that weren’t in use, they changed their ports, they did a bunch of other things, and then what ends up happening is, administrators are always balancing… Should I do the ultimate right thing when it comes to security, or should I make my life a little bit easier, the convenience factor? And so, this particular company created local administrative accounts with linked servers that could reach every other database inside the environment. So you can imagine, despite all of this work they did, they did all of this really great work, and then just because they took the easy path on something real simple, all it took was any one of those to be compromised on a local account, and they had access to every single database across the footprint. So, these are the types of things that, you know, I think our experience really brings to bear, because we can help customers head off these problems before they get exploited.

Max: [32.51] I want to go back to your earlier example, because I think it’s a very interesting point to talk about. So, in education – in a school – primary school, secondary school, college, whatever it is, right? YOu look at the transformation, and what you’re really talking about is transformation from looking at tech from, “Okay, we need to have this because you have to have a computer,” to, “We need tech in order to actually function,” to, “Now we’re actually functioning the business through tech,” to, “Now, how do we actually excel as a business through transition from being a tech-enabled business or a tech-focused business, into a data-focused business.” You know, from a competitive advantage, I don’t care if you’re a for profit or a not for profit organization, saying, “This is our graduation rate,” that’s a massive statistic to know and track. And you know, that transition, that shift to say, “Okay, we’re now looking at, well, our students have laptops, and so they can work on a laptop and we’re going to digital classrooms,” to actually saying, “Okay, now we have all this predictive data that we’re doing something with,” to saying, “This is how we’re actually affecting an outcome for the business that is positioning this business in a better way. We’re going to get ahead of the market, we’re going to get ahead of competition, we’re going to brand differently,” and this is a school… Like, who thinks of a school as a data company, right? Like, the school’s not a data business, but here’s an example of when a school is a data business. And if you take that out and you walk this into other industry verticals, I mean I have to imagine the examples of this become massive. You said something about predicting when a machine goes down. Well if you’re a manufacturing plant and you’re running CNCs and you’re running them on shifts and you’re milling titanium, you’re going through the energy of testing… How fast and hard do we run the machine, you know? Is it worth it to run it faster and burn out more bits, or do we run it slower and preserve the bits, or where’s that balance? You know, taking and actually putting that data into play and saying, you know, this is when this machine needs to have maintenance otherwise it’s going to be a big problem… That’s a huge, massive financial advantage… Forget like, in the efficiency of the machine, but also what you can deliver to your customers and your product. It’s a very interesting thought process when you look at it in these ways.

Jim: [35.10] It is, and let’s go back to the manufacturing example; we all know that so much of manufacturing now is just in time, right? So nobody is — in many cases manufacturing is not building up massive, massive supplies waiting for it to sell, so if you can determine that a particular machine and it’s particular part has been used so many cycles, it’s sensors are saying, “We’re about to have a problem,” sort of like the smart data on a harddrive, then you can order that replacement part and fix it in a short scheduled maintenance, before it surprises you and goes down, and you’ve got to go and get that particular part, you’ve minimized your revenue loss. You know, you’re meeting your just-in-time schedules, you know, you’re not down for say, three, four, five or longer depending at where you’ve got to get the parts from, and you’ve actually kept your business running largely on schedule, and those things all have revenue impacts, all of them. So, that’s an example that we talked about there, in the manufacturing world, and it plays out across pretty much every single industry. I mean, you look at retail, retail the classic example is what sells best in what type of season? Well, even beyond that, you’ve got campaigns. You can measure campaigns, you can measure responses of campaigns, and then there’s all these other variables that go into it, where you can figure out competitive advantages against the companies that you’re working against. So, this data, this final stage of leveraging the data really is the most powerful stage. You’ve got to keep the lights on, you’ve got to keep the transactional systems going, you’ve got to take payment processes, you’ve got to sell orders, you know, you’ve got process online or some other type of class for a university, but ultimately when you figure out where you’re going to move the business to become better than everybody else, that’s that final stage of leverage, and in the cloud, there are an awful lot of really neat services to help. You look at Azure for example, Azure has AI processing services. You’ve got to set all of this up, but they’ve got the right storage, they’ve got the right services to process. You’ve got Kubernetes and containers and notebooks, and all these different pieces fit together in a pipeline to process data, and ultimately get you to those answers. So, it really is exciting and there are some companies that we know that are actually going into microservices and building it in house; we’ve seen them do that largely because of security concerns, there are still security concerns with the cloud, but I think that is all going to dissipate. I look at some of the really big paradigm shifts that I’ve seen in the last ten years… The first one I saw was virtualization. You know, you go back about ten years ago, and you know, in 2011-ish timeframe, everybody was virtualizing their file servers, they were virtualizing DR, devtests, but your mission critical database, or applications… They weren’t being virtualized, they were still on bare metal. And then we reached a certain version of virtual software, where that interim layer became — that penalty layer became so small, and the performance increased so massively that it became a sea change. In a very short period of time, we had customers asking for guidance on how to go from physical to virtual, and even with their mission critical applications. Not all of them, but a lot of them. And then, we started to see this move to the cloud, and cloud really was a buzzword for a long time, and then it finally got to a point where people started to get comfortable with security. They realized Azure, AWS, they’re better at security than the internal teams – the internal IT teams are! It’s their whole business, it’s their lifeblood, and as soon as companies started to realize, “You know what, these cloud providers are doing security better than we ever could,” you started to see this big migration. Again, that was another big paradigm shift. And now the third one that we might be seeing is obviously the events of the world are really getting a lot of companies focused on long-term remote workforce enablement. And so, I think that is going to escalate, or it’s going to accelerate the rate of cloud adoption. It just feels that way; you know, we’re dealing with a lot of customers that say — you know what, here’s an example: we had a customer that had to go real quick, obviously shut down their doors, get everybody working remote, they had O365 AD, they had on-prem AD, and it was only synchronizing one way, okay? So, every time somebody had a password reset problem, they had to hit their service desk. Their service desk was getting hit with tons and tons of requests. Well, you go in, you re-architect the bi-directional solution, and now you’ve got self-service password resets; people would go up into the Office365 side, reset the password, and it would replicate back down. So, these are the types of accelerated problems that IT organizations are dealing with, as a result of moving to the cloud – in some cases begrudgingly – although I think they’re going to like it when they get there, and in some cases they already had those plans and they’re just accelerating them because the need is there. But these are the types of challenges that customers are working with, and since we’ve been doing a lot of these setups – especially hybrid – hybrid cloud setups — I mean, we’ve got customers that are in AWS, Azure and in multiple on-site colocations, all around the world. And so, we know how to tie in those VPN, those security functions, access, get them all looking together, bring in a monitoring solution that’s one pane of glass that can monitor AWS, can monitor Azure, can monitor your on-prem, bring it all together so that you don’t have ten different tools. You’ve got one tool where you can see what’s going on with your environment. These are the things that I think have really benefited us, because over the years, we’ve learned from these – you know the early growing pains, there. We’re now at the point where we’ve really got the process refined.

MID-ROLL: [42.36] Hi I’m Max Clark and you’re listening to the Tech Deep Dive podcast. At Clarksys we believe tech should make your life better, searching Google is a waste of time, and the right vendor is often one you haven’t heard of before. With thousands of negotiated contracts, Clarksys has helped hundreds of businesses source and implement the right tech at the right price. If you’re looking for a new vendor and want to have peace of mind knowing you’ve made the right decision, visit us at Clarksys.com to schedule an intro call.

Max: [43.00] I’m laughing at something you said, but you know, begrudgingly going to the cloud and being happy when they get there. It’s like virtualization, you said it – maybe you put off virtualization for a long time and then you do it and it’s like, “Oh, this is amazing, why didn’t I do this beforehand?” And then go the cloud and you’re like, “Oh wow, this is amazing, why didn’t I do it beforehand?” But then, it solves and makes some things easier and it makes other things harder; the complexity you can find in cloud environments is incredible, remote access, connectivity, security, all these other layers… You know, are things that — an IT person’s not going to migrate to the cloud and be less busy; I’ve never seen that, ever. In many cases it’s quite the opposite, where the business realizes it can accelerate and they can do more and they want to do more, and then it’s, “Okay, now we have more to do, we’re just not managing physical boxes spewed around any more.” I’m also very curious what’s coming down the road as it relates to remote or distributed work, and I’m not feeling like an absolute, like it’s absolutely going to be remote or it’s absolutely not, I think it’s going to be some variation of it, but the demands of flexibility, of being able to support your internal and external — your internal employees and customers and your external customers, from anywhere at any time. I think that has shifted, and companies are going to be looking at that and thinking about that going forward in a much different way. 

Jim: [44.27] Yeah, I think you’re right, and we’ve actually had a couple different customers that are very sophisticated, some of those are the types of customers that we talked about that collect that — that leverage that data and collect that advanced analytics information, and they’re measuring their employees and they’re finding out that many of them are far more efficient working from home, you know? You don’t know – you go into the office, people walk by your office or your cubicle and you get caught up in conversations and you go to lunch, or you go to the cooler, and it’s another five or ten minute conversation, and the next thing you know, you’ve lost a third of the day. And literally some customers are measuring marked improvement in efficiency. And so you’re right, I don’t think it’s going to be all or nothing, but what we could see is a very hybrid approach going forward where more and more people are spending part of the week in the office and part of the week remote, something along those lines, and the ones that maybe are very, very efficient and productive working remote may have an option to just come into the office periodically, you know, every other week – I don’t know. We’ll see how it all pans out, but you can obviously save on lease, utilities, all the other office type expenses, and if your employees can do the same job, and those employees can be even more efficient at doing their job, there’s an ROI to that. And so, we’ll have to see what companies really embrace this going forward, and which ones embrace it in a hybrid fashion, and which ones maybe just go back to their old culture… I don’t know, we’ll have to see.

Max: [46.19] You give an example of a customer who has hybrid environments, Azure environments, AWS environments, I don’t know if you said it but probably Google mixed in there as well. How do you — when you’re going through an assessment and discovery for a migration project, or maybe it’s an assessment and discovery and you know, for a re-architecture project, how is the cloud decision and which cloud… I mean, how does that work out? When you look at it from a customer standpoint and you’re making that recommendation and guidance for them, what are the big knobs that you’re looking at, or decision levers, to influence that decision? 

Jim: [46.59] Yeah, that all depends on what we find and what we’re also looking forward to in the later stages of that lifecycle, like ultimately what we think they might be doing with their data. But up front, what we’re looking at is — so right out of the gate when we’re doing an assessment for a migration to the cloud, we’re doing a right-sizing exercise. This is one of the number one things that we find customers run into problems with, is they take a look at their current resource setup, they put it up there and their bill goes through the roof. They put it up there, and they’re only using a fraction, and so they’re paying more than what they need to. For very transient environments that have a lot of like, short projects, or dev tests that spin up and down all the time, a lot of wasted resources that sit out there that are no longer being used, and they’re paying for them. So, their spend is a big part of the upfront analysis; we do a very, very detailed performance analysis of the service and we make recommendations on the sizes, there may be recommendations around reservations… Depending on the cloud — if you’re for example an education customer, you’re probably going Azure, because there are a lot of incentives for, you know, an education system on Azure. And then ultimately, what types of tools are you using, what are you ultimately going to do with your data? All these things matter in whether one is better over the other. What we’re finding more and more is the two are starting to come closer together, you know? I’ll take a look at – for example the database world – AWS, right — I don’t want to disparage them, they’ve got RDS for Oracle, MySQL, SQL server, a bunch of other things, and it’s very good, but for the longest time, you could not put your jobs – for example, SQL Server agent jobs could not run on those RDS instances, where they could in Azure. So, those are the types of — what are you using? What are you doing? What do you need to modify to make it work in the cloud? All of these things matter, especially when you’re talking about PaaS – potentially going to PaaS versus IaaS. So those are the types of decisions, but these gaps are closing – it’s like literally every single month, it seems like more and more features are being added to what you can do in the cloud. You know, part of this also is what’s your internal team expertise? You know, some companies work heavily off the Microsoft stack, they’re very comfortable just building C# services and working out of the Azure service suite, and that can make a decision. So, it comes down to, you do the pricing analysis, or the sizing analysis, the right-sizing analysis, you look at the pricing across each, you look at how you’re going to use that data going forward, and then in some cases it’s a tie, it’s a toss-up; in some cases there’s some x-factor that puts it over the top, like you’re in education, you’re a university, and you’re going to get a bunch of Azure credits if you go there. 

Max: [50.36] We used to call those layer eight issues, right? You know, the people overlaying everything else that are influencing some other decision.

Jim: [50.45] Yes, yes. 

Max: [50.45] And of course, Microsoft, if you’re an existing EA customer, there is a big push for you to convert into CSP and what is your Azure credits look like on top of that, and you know – the decision whether or not the company is on Office 365 or G-suite factors in, and are you already on Amazon or not… But you know, up to a certain point there is a reasonable amount of portability between the clouds. You could switch between one or the other if it made more sense for you down the road. So, this isn’t necessarily a permanent decision, it’s just a… This is right with the information that we have and if that information drastically changes in a year or two, maybe we look at this differently.

Jim: [51.21] Yeah, exactly. You know, again – how are you going to use your systems? You know, you look at for example some of the really neat technology coming through on the database side, which we started this conversation out, it’s about information, it’s about data, everything else is sort of around that to make it work. You’re looking at – in the Azure world – CosmosDB, and you look at AuroraDB on the opposite side, and you’re looking at all these new features, you start to hear about, “Well, we’re building database systems that can be both transactional and they can also be – they can support your analytics and your data warehousing.” It’s like, how do you do both in one? But that’s what’s coming out!

Max: [52.07] You’ve invested billions of dollars to make that happen is the answer to that question, right? 

Jim: [52.11] Well, yeah, and you know it’s a good point, because you can make a mistake too in actually implementing that. Again, just another reason why it helps to get that upfront analysis – we had a customer that went with Synapse and Synapse is, you know, very powerful, but it consumes a lot up in Azure, and ultimately they really could have gotten the same thing from a managed instance for what they were using it for, for their level, and save vast, vast amounts of money. So, there are a lot of choices in these clouds and – like you say – at one point, one of these choices might look great, and then the way, let’s just say for example in AWS, and then Azure continues to beef up their capabilities and one of their offerings, and then that becomes not only a cost effective — a more cost effective solution, but one that solves their problems better. And then if the ROI on the migration is good, then there you go. So, you could very well see migrations back and forth between the clouds as well.

Max: [53.20] And a lot of these stats are very surprising. I mean you know, Azure announced recently that more than fifty percent of their compute was running Linux and not Windows, and that’s… I mean, that’s a pretty shocking statistic when you think about Microsoft and Azure and the majority of their compute is not running Windows for compute… I mean, that says a lot about what’s happening in these cloud platforms and where these platforms are going.

Jim: [53.44] Yeah, no – I agree a hundred percent. I mean, it’s — we were surprised when certain database engines got released, SQL server engines, to run on Linux. We figured, “This isn’t going to go anywhere, who’s really going to use this?” Linux is stable, we get all stuff but you’re right, you know, when you look at companies that are truly analysing their stacks, Linux, it powers many of the systems out there across the world, and now we’re seeing it combine on a platform like Azure that you would not normally thing – you would think that would be a small percentage. And I’m fairly certain in the SQL server world, SQL server on Linux is still a very small percentage, but companies are looking at their stacks, or looking at stability, they’re looking at their internal capabilities and you’re right, we’re seeing these mixes and matches and combinations of technology that ten years ago we probably didn’t see clearly, nearly as much. You saw Oracle, UNIX, Linux, you saw MySQL Linux, you saw SQL Server Windows, and these walls are starting to break down and these technologies are starting to mix. 

Max: [55.07] And this goes back to something that you said earlier, which is IaaS, infrastructure as a service, or PaaS, so it’s… You know at some point do you care what the application is running on, or do you just care if the application is running, and then you go to the next level of that: do you even care about the application or do you just care about putting data into it and retrieving data out of it, and moving down that path becomes very interesting as you talk about modernization and transformation. 

Jim: [55.34] It does, but there is still the one caveat – and you alluded to it earlier Max – you said a lot of companies just move up into the cloud and they think, “My management problems are over,” you know, you even take a PaaS solution, you still can have lock and blocking, you still can have performance problems, there’s a lot of things that don’t necessarily solve themselves, so while you do abstract out some of that management and make your life easier, not having to deal with the file system, not having to deal with the operating system, in many cases. It doesn’t mean it’s hands-off, it doesn’t mean it’s fire and forget, you set it up and it’s just going to run forever without problems. So there is a managed services component here, even if that managed service is tailored a little bit differently to a PaaS instance versus an IaaS instance, you have to keep an eye on the store. Because if you don’t, then eventually your workloads are going to increase, your system won’t keep up, you’re going to have performance problems; or along the way you could still have corruption, you have to look for things like corruption, because if you don’t then eventually it’s going to get to a point where it brings your system down. So, there’s still a need for managed services in all of this.

Max: [56.54] Of course, of course, and it also talks about velocity and capability, right? You know, do you bring in a managed services provider that has expertise and is efficient at tracking these activities and looking for these things and keeping up to date on these things or do you want to develop that internally and staff it and support it and train, or do you want to focus on your applications and your business, right? And like, finding that line – it’s a very specific question and it’s very personal to each company, right? Each entity has to figure out where those lines are for themselves.

Jim: [57.30] Yeah, and we talked a little bit earlier about the half an SME problem, when you talk about, do you want to do it internally? Do we want to do it ourselves? Well, in many cases, you can but you have to hire an FTE for that particular function, and you might not need an FTE, you might need twenty five percent of an FTE for an architect, you might need twenty-five percent of an FTE to handle your Azure security setup, creating your availability sets, you know, a variety of other functions, you might need half of an SME to do database administration for you. Do you really want to go out and buy or hire three, four, five SMEs that are not going to be fully utilized? And again, that’s where I think we can come in and augment existing staff, and help that staff just fill in the gaps, because you want to reduce waste, you want to be efficient, and going the route of hiring a bunch of FTEs that you don’t need FTEs for is counter productive to that. And then, secondarily, you touched on the other part is, many businesses are now taking a look at this and saying, “My core business is tax software,” or, “My core business is some manufacturing function. Do I really want to spend a lot in IT to manage all of this stuff when I can literally get out of the datacenter business, I can simplify my IT team to certain critical functions, and focus my business on what it’s good at, what it makes money at, and not so much all the foundation work that is required to keep all these systems going.” And that’s not a new concept, there’s a lot of — that’s been discussed for years and years and years, but in the current environment, I think the whole remote workforce enablement, the change, the accelerated — potential accelerated change to the cloud has companies re-thinking, “Should we outsource part of our IT function, save some money in the process, and not burn out our internal IT staff that we want to keep, keep them focused on the high value activities that move the business forward, and focus on what we do best, what our business is all about.” So all of these things are coming together and we’ll have to see how it all plays out, but I think we’re in probably the third – potentially the third big change that has happened in the last ten years. 

Max: [60.19] I mean that’s crazy to say, right? In just ten years.

Jim: [60.22] Yeah, IT moves fast!

Max: [60.26] It does! Jim, thank you very much for your time, this was fantastic, I appreciate it – it has been a pleasure.

Jim: [60.32] Yeah, thanks a lot Max, I really appreciate you having me on and it was great talking with you as well.

OUTRO: [60:40] Thanks for joining the Tech Deep Dive podcast. At Clarksys we believe tech should make your life better, searching Google is a waste of time, and the right vendor is often one you haven’t heard of before. We can help you buy the right tech for your business, visit us at Clarksys.com to schedule an intro call.