Optimizing Operations with Predictive Data and Cloud Modernization: Jim Haas at Ntirety | Ep. 10

Max: 00:03

‍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 Clark Sys, 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. Hi. I'm Max Clark, and I'm talking with Jim Hass, who's the vice president of data services with Entirety. Jim, thank you for joining.Jim: 00:26

Thanks. Thanks for having me, Max. Appreciate it.

Max: 00:29

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 was professional services, and before that, that was databases. So I think it'd be a good place to start and just talk about entirety and and your role with entirety and how that has evolved over the past few years and how that fits into the the grand scheme of things with entirety's cloud practice.

Jim: 00:53

Yeah. So it's interesting. You know, Over the course of time, entirety has morphed based on the needs of the industry. Actually, entirety itself goes back 20 years ago and was just a remote database administration and consulting company, which then ultimately got acquired by much larger infrastructure and Cloud operations companies, and then rebranded completely as as entirety. 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.

Jim: 01:46

And and and I think as the conversation goes through, we're we're really gonna talk about how all these different pieces come together. It's not just about the data. You read the articles and the articles say, well, information is the lifeblood of companies. That's really true, but that information, that data has all these other components around it. It's got the need for infrastructure, for CloudOps, security and compliance.

Jim: 02:18

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 that we'll get into a lot of the different details of. And so my role has really transformed from strictly, okay, we're we're your, you know, remote database administration company to, you know, we're consulting and advising you and getting you to new places, modernizing your 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 the areas that entirety as a whole is responsible for.

Max: 03:21

But you talk about the merger that formed entirety. And part of that was, you know, what still is a data center physical equipment practice. So customers could take equipment to your facilities or you can manage equipment for your customers in your in their facilities. And then there's this practice around around the different public clouds. And, you know, when you're 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, you know, we wanna switch to the cloud, or we're switching the cloud, we need help, or we're in the cloud, we need help.

Max: 03:54

What does that lifestyle, you know, life cycle really look like for you and and what you see?

Jim: 03:59

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.

Jim: 04:27

Many times they'll come to us and they've got, you know, a set of thoughts in their mind about how they wanna 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 is 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.

Jim: 05:09

They're either taking their first crack at, say, for example, a rearchitecture of their environment up into the Cloud or hybrid. You know, a lot of times it's an interim step where, you're doing on prem, and you're doing cloud, possibly multiple clouds, AWS, Azure, you name it. And they don't know all the pitfalls. And this is where, you know, we we sort of classify our customers into these maturity levels. We've got 4 of them.

Jim: 05:40

And 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, siloed departments will build their own servers, their own ways.

Jim: 05:58

And these lead to security vulnerability holes, inconsistent in performance and availability. That's the sort of the low level. And then you get into the next level. And and most customers sit somewhere around 1 and a half to 2 where they're starting to get more sophisticated. They're really starting to build templates.

Jim: 06:18

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 they're learning from the mistakes of the past or through their own research. And then you get, you know, beyond, you know, level 3 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.

Jim: 06:49

And at level 4, you really are competitive with anybody. You you've done this multiple times. You got a really strong IT team. You've got a really good program in place, things for risk management, you know, creating golden images for your your servers, whether they're app servers or database servers or just, you know, how you set up, some of your other IT equipment. That is a very strong program that generally needs the least amount of help.

Jim: 07:19

What we're seeing with customers is there's a vast array of experience somewhere along this trajectory. And in some cases, as we get into this data and this maturity life cycle, there are some areas where we spend a lot of time upfront in discovery, assessments, architecture. And then in others, it's really more tweaking. You know, there we we fill in the gaps where they might not have the gaps, and then we help them implement. And we help them head off the problems that we've seen because we've done many of these.

Jim: 07:56

So many of these that, you know, a lot of the things we could see a mile away, we go into an environment 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 it's not gonna work or it's vulnerable or it's gonna break or it's gonna perform not to expectations. Or conversely, they're gonna overprovision and waste a lot of money. So these are the types of things that we do. We really have a program that analyzes 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.

Jim: 08:39

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 and the scale of Cloud, I mean, I mean, 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 what level are you using cloud infrastructure today? So on the scale of that, you have this, like, very basic approach of, okay, we're gonna virtualize on premise equipment, and we're gonna bring it off prem, and we're gonna put it somewhere else. Right?

Max: 09:08

And this becomes, like, this very, like, low level cloud migration. On the other end of the scale, you see cloud native companies. Usually, these are Internet companies that started in a cloud provider environment, always been there, are maybe, you know, containerized 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, you know, just looking at this on my a we're gonna switch from a capex to an opex cycle and from an on premise server to a virtualized VM and to actually taking advantage of things that are available to you from a cloud environment.

Jim: 09:53

Yeah. So that's, in many cases, a big initiative. It coincides with a lot of different things. For example, 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.

Jim: 10:11

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. That change requires a significant amount of upfront discovery in architecture. I'll touch a little bit on it now. I talked about this life cycle of infrastructure and data.

Jim: 10:45

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 is, are you ready to go to the Cloud? You're talking about containers and services, but there's also even other areas such as, are you in IaaS implementation, and should you move to a PaaS implementation? In many cases, you might want to extract out that operating system layer and not have to worry about that.

Jim: 11:24

Simplify your maintenance, simplify your management, but it's not that simple. Now, it's gotten better. You look at where it was 5 years ago, there were entire feature sets. Take, for example, SQL Server, like SQL Server Agent Jobs and SSIS that you simply could not put in a PaaS instance. So you had to design yet an IaaS instance to do all that work remotely.

Jim: 11:49

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 in this first stage of the the life cycle, we're doing a lot of these assessments to to mine out what are your dependencies.

Jim: 12:11

You know, if you're gonna go to PaaS, for example, you're gonna go into the cloud. You're gonna move to a PaaS infrastructure because you believe, I'm not gonna have to manage as much. It's gonna 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.

Jim: 12:36

You can't do that in PaaS. There's all these dependencies customers don't think about this. Our Cloud readiness assessment, which is part of this initial phase of the data life cycle, 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.

Jim: 13:08

So there are shifts in the way that we have to do business or how we have to execute code and manage the interactions between applications, database, and the OS. If we account for all of that, then we'll have a 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 the connections, and those were all gonna change.

Jim: 13:47

As soon as that got up there, everything was gonna 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 wanna 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 always something that can be done if, you know, you're you're not ready to take advantage of all the services, you know, containerization. This is a this is a process of steps.

Jim: 14:19

But Then what happens is you get beyond the assessment, and in the next phase of the life cycle, it's architecture. Architecture is really where you're redesigning, refactoring your application, your database, how things interact, even your high availability in 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 the particular software engine. You know, 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.

Jim: 15:01

But you get up into the Cloud and you want to leverage that. Same thing happens even outside of the application. There are functions like availability sets. While Microsoft will say you really should configure availability sets, a lot of people don't do that. A lot of companies don't do that.

Jim: 15:20

They simply put their stuff up there, and then there's a maintenance event, something goes wrong, maybe a network card, you know, goes flaky and your application's down. Well, it's easily solved with something like an availability set, but not everybody has the expertise to think about that, put that in the planning, and make that part of the migration plan. So these are some of the things that just we've learned over time because where customers, you know, 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.

Jim: 16:04

And when you do that, you learn these mistakes, and you you build them into your processes going forward. So these are some areas where customers really can struggle upfront. Even if they're sophisticated, they might not have thought of everything just because they didn't they didn't do many of these. And since we have, we can bring a lot of value in sort of that, that mitigation upfront of risk.

Max: 16:29

I mean, so example of of the assessment of of having hard coded connection strengths. I mean, I mean, that's something that once you've experienced it the first time, you have that, like, okay, note to self, always check for this in the future. But when when I think about, you know, an enterprise application, especially something that's been running inside of an enterprise for years, you're talking about layers of technical decisions and configuration that that probably doesn't even have a map anymore. You know, people have implemented something 5 years ago, and nobody knows why it's running that way where it's running what's actually happening with it. How long I mean, when you when you start an assessment, I mean, you're not gonna discover everything.

Max: 17:05

But, I mean, how long does an assess an assessment process take? And, you know, what does that really look like with with the customer of trying to say, okay. You know, I mean, are you literally giving them a checklist that you're running through that has, like, 500 questions on it? Or, you you know, is it more about the application and the environment and the processes and what the business is doing or or a combination of

Jim: 17:25

both? It's a combination of both. It it really is. And the assessment isn't necessarily high level. There are levels of that assessment.

Jim: 17:34

Some of it can be simply the best practices. Some of it can be PAS versus IaaS options. But other ones are a lot more detailed. Actually, we use a little bit of a different term. We then move away from the assessment term and more to the discovery term.

Jim: 17:53

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.

Jim: 18:22

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. We're looking at all the different pieces technically and how they fit together. Then from that, we make architecture, we'll raise awareness of things that could be blockers to moving to the Cloud, or we will make actual redesign recommendations.

Jim: 18:54

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 may have quite a bit of control over how you change.

Max: 19:07

I mean, what's the ratio of that right now that you're saying? I mean, how much of these are internally developed apps and how much of these are customized, you know, ERPs or something that a a company has?

Jim: 19:16

The ratio is hard to say. You know, it what's taking over the industry right now, in a lot of cases, are moved to SaaS. So when you're talking about vendor apps, you know, 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.

Jim: 19:48

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 still high percentage number of internally built applications or at least customizations to applications. You know, you might have an application and somebody's built c sharp services on top of it for ETL functions or for API pull ins, to bring data into a data lake or some other ODS or or repository. So you've got the app and then you've got all the stuff that's surrounding it, and some of that might be things that are really good targets for moving to, for example, breaking them up into Azure services.

Max: 20:33

If phase 1 is assessment and phase 2 is discovery, you said this is a 4 step 4 phase process usually, I believe. What are 3 and 4?

Jim: 20:41

So it's a 5 step process. So you've got assessments, you know, where there's lots of recommendations that come out of that. Then you've got the architecture phase. We already talked about that where you're actually designing the new environment. Before I move on from that, that design can also be new high availability, new disaster recovery, utilizing new features.

Jim: 21:05

It can be upgrades. In many cases, a lot of our customers going to the cloud are on old versions. And when you go to the cloud, you some of those versions, you can't even put them up there anymore, especially those that have waited for a very long time or at least the ones that are, let's just say, Windows SQL 2008. Microsoft's throw you know, Azure's throwing you a bone for security enhancements for a little bit longer, but that doesn't change the fact that it's gonna go away. You have to start upgrading.

Jim: 21:39

And it's been an impetus for a lot of companies to actually take that step when they're finally doing that migration and and to upgrade as well. So that architecture phase is all about taking advantage of new features. And, you know, a lot changes from version to version. You know, the you have compression. You've got encryption.

Jim: 22:02

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. You've got this architecture and design. Stage 3 is really the go do it stage.

Jim: 22:23

We call it implementation enablement. You did all this great analysis, and you have to go make it real. You've gotta go ahead and take it and deploy it. This in many cases is gonna be your infrastructure, your security, whether that's hardening, templates, everything that you need to do to get it up there, installed, and protect it according to best practices and the other standards that you follow or are required to deploy for the customer. That's actually pretty simple phase.

Jim: 22:59

It does have many iterations to it, but it's make it happen. Then finally, or 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, but you 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 gotta be available, they gotta be performing.

Jim: 23:29

You gotta be looking out for things like, am I spending too much money? Do I have performance problems or were 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 gonna have to make adjustments. So you get up there.

Jim: 23:48

You you put monitoring in place. You respond to alerts. You you deal with potentially user complaints about performance. All those things that you've gotta do to make sure that, a, it's performed performing, and, b, it's available. It's those two things are absolutely critical.

Jim: 24:07

And then beyond the manage 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.

Jim: 24:22

You know, it's one thing to have a bunch of transactional systems that do things like, okay, you got card readers, let people out in and out of buildings. You've got payment processing systems. You know, those all have database back ends and applications, but when you start looking at your CRM systems and your finance systems, and in many cases, even your operation systems, and all the other ones that tie into that, you now want to start taking all those disparate pieces of data. You wanna 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. And those business insights can be everything from we've got manufacturing environments where they wanna predict based on certain amount of run time and sensor data.

Jim: 25:16

When is this machine gonna go down? We can't afford to have a machine go down, so they will do maintenance ahead of time. In the retail, you know, 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.

Jim: 25:39

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 life cycle. It's high level assessments. It's architecting the future state. Go ahead and do it and deploy it.

Jim: 26:05

Manage it and make sure it's always there, and that if there's any issues, you can resolve them quickly via monitoring and a fast you know, 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 is way more involved than just, you know, a a company that's gonna help administer, migrate, manage. You know, we hear these things a lot about, like, oh, we're gonna help you manage your cloud environment or we're gonna help you, you know, do cost optimization and cost control. When you start getting into the 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 that's not admin work. I mean, this is this this is getting to be some really interesting stuff here.

Jim: 26:54

Yeah. It is. And that's where I think we've really married consulting and managed services together extremely well. There's there's such there's such great synergies between the 2. And some, you know, companies will only take you so far.

Jim: 27:13

We take you through the whole the whole part of all of this. And interestingly, when

Max: 27:21

we

Jim: 27:21

look at customers and their maturity, we talked a little bit about maturity and sort of where they are, 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. It's different for all the different things that basically make up the IT ecosystem and the services around it.

Jim: 27:48

Where I think we really shine is that we span that whole entire life cycle. You know, we'll get into I I can't tell you how many times we've gone into a company where, for example, they already have data scientists. And and if you've already got data scientists, PhDs that are essentially 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?

Jim: 28:39

All these different types of KPIs give them 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 many 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.

Jim: 29:16

They're just not there yet. They might have SSRS reports or Crystal Reports or Cognos, some type of reporting and that's fine. But you still need a repository for that. 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.

Jim: 29:42

In many cases, they're just thinking, I'm gonna lift and shift, maybe only part of their environment. Still today, hybrid environments are very, very common. They're gonna lift and shift. Okay. So what's the next thing?

Jim: 29:55

You lift and shift. How are you gonna monitor these 2 disparate environments? How are you gonna connect these 2 disparate environments? You know, what's your security and compliance and your your risk program for these 2 different departments? And a lot of times, those answers, they just haven't gotten that far.

Jim: 30:15

They're thinking, well, I got a VM, I'm gonna move it up there, and it's gonna 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 we're we're just we're 5 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, you know, customers just they don't see. They don't see these things ahead of time.

Jim: 30:54

You know, I'll focus on on another another type of example, which is in the security space. Security is obviously an extremely hot topic right now. Yeah. It's it's it's one of the, if not the hot topic right now. And we deal with a lot of customers, you know, banks and and payment processors and other types of companies that have to conform to security hardening standards.

Jim: 31:20

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.

Jim: 31:49

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, you know, despite all of this work they did, they did all of this really great work.

Jim: 32:27

And then just because they took the easy path on something, real simple, all it took is any one of those to be compromised on the 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, you know, we can head we can help customers head off these problems before they get exploited.

Max: 32:51

I wanna go back to your earlier example because I think it's a very interesting point to talk about. So in education so a school. So, primary school, secondary school, call it, 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, right, to we need tech in order to actually function, to now we're actually functioning the business through tech, to now how do we excel as a business through this transition from from being a tech enabled business or a tech focused business into a data focused business.

Max: 33:25

You know, from a from a competitive advantage, you know, I don't care if you're a for profit or or not for profit organization. I mean, saying this is our graduation rate. I mean, that's a massive statistic to now track. And, you know, and that transition, that shift to say, okay. We're now looking at well, you know, our students have laptops, and so they can work on a laptop, and we're going to digital classrooms to actually say, okay.

Max: 33:48

Now we have all this predictive data that we are actually mining and doing something with to say, this is how we're actually affecting an outcome for the business that is positioning this business in a better better way. Right? You know, we're gonna get ahead of the market. We're gonna get ahead of the competition. We're gonna brand differently.

Max: 34:05

And this is a school. Like, who who thinks of a school as a as a as a data company? Right? Like, the school's not a data business, but, you know, here's here's an example of school's a data business. And if you take that out and you and you walk this, you know, into other other industry verticals, I mean, I have to imagine the examples of this become become massive.

Max: 34:22

I mean, you you said something about, you know, predicting when a machine goes down. Well, if you've if, you know, your 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 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?

Max: 34:43

And where's that balance? But, you know, taking and actually putting that data into play and saying, okay. You know, here's exactly when this machine needs to have a maintenance. Otherwise, it's gonna be a big problem. I mean, that that's a huge, massive financial advantage.

Max: 34:58

Forget, like, in the efficiency of the machine, but also in what you can deliver then to your customers and and your product. I mean, these it's a very interesting thought process when you look at it, you know, in in these ways.

Jim: 35:09

Yeah. 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?

Jim: 35:18

So nobody's in many cases, manufacturing is not building up massive, massive supplies waiting around for it to sell. So if you can determine that a particular machine and its particular part has been used so many cycles, its sensors are saying, we're about to have a problem, sort of like a smart data on a hard drive, and 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 get that particular part, you've minimized your revenue loss. You know, you're you're meeting your just in time schedules. You know, you're you're not down for, say, 3, 4, 5, or longer depending on where do you gotta You gotta get the parts from. And you've actually kept your business running largely on schedule.

Jim: 36:12

And those things all have revenue impacts, all of them. So that's an example in, 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.

Jim: 36:39

You can measure campaigns. You can measure response of campaigns. Then there's all these other variables that go into that where you can figure out competitive advantage against the companies that you're working against. This final stage of leveraging the data really is the most powerful stage. You got to keep the lights on.

Jim: 37:06

You've got to keep the transactional systems going. You got to take payment processors. You got to sell orders. You know, you got to process online or, you know, some other type of class for a university. But ultimately, when you figure out where you're gonna move the business to become better than everybody else, that's that final stage of leverage.

Jim: 37:29

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 can get 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 in containers and notebooks, and all these different pieces fit together in a pipeline to process data and ultimately get you to those answers.

Jim: 38:02

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 security concerns. There are still security concerns with the cloud. But I think that is all gonna dissipate. I look at some of the really big paradigm shifts that I've seen in the last 10 years.

Jim: 38:30

The first one I saw was virtualization. You go back about 10 years ago, and in 2 1,011 ish time frame, everybody was virtualizing their file servers. They were virtualizing Doctor, DevTest. But your mission critical database or applications, they weren't being virtualized. They were still on bare metal.

Jim: 38:52

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 it became a sea change. I'm telling in a very short period of time, we had customers asking for guidance on how to go from physical to virtual in even with their mission critical applications. Not 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.

Jim: 39:39

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 these cloud providers are doing security better than we ever could, you started to see this big migration again.

Jim: 40:03

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 gonna escalate or it's gonna accelerate the rate of Cloud adoption. It it just feels that way. You know, we're we're dealing with a lot of customers that say, you know what?

Jim: 40:33

Here's an example. You know, we had a customer that had to go real quick, obviously, shut down their doors, get everybody working remote. They had Office 0 365 AD, they had on prem AD, and it was only synchronizing one way. 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.

Jim: 41:02

Well, you go in, you re architect a bidirectional solution. Now you've got self-service password resets. People would go up into the Office 365 side of things, reset their 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. In some cases, they already had those plans and they're just accelerating them because the need is there.

Jim: 41:37

But these are the types of challenges that customers, you know, are are 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 colo locations all around the world. And so we know how to tie in those, you know, 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 10 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.

Jim: 42:31

And we're now to the point where we've really got the process refined.

Max: 42:36

Hi. I'm Max Clark, and you're listening to the Tech Deep Dive podcast. At ClarkSIS, 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, ClarkSIS has helped hundreds of businesses source and implement the right tech at the right price. If you're looking for a new vendor and wanna have peace of mind knowing you've made the right decision, visit us at clarksys.com to schedule an intro call.

Max: 43:01

I'm I'm laughing at something you said and then then, you know, begrudgingly going to the cloud and then being happy when they get there. I mean, it's it's like virtualization. You said it. You know? You you you maybe you put off virtualization for a long time, and then you do it.

Max: 43:12

And it's like, oh, this is amazing. Why did I do this beforehand? And then you go to the cloud, and you're like, oh, wow. This is amazing. Why didn't I do it beforehand?

Max: 43:18

But then it it's it solves and makes some things easier, and it makes other things harder. I mean, the complexity that you can find in cloud environments is incredible. Remote access, connectivity, security, you know, all these other layers, you know, are things that I mean, some an IT person is not gonna migrate to the cloud and be less busy. I 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 wanna do more.

Max: 43:47

And then it's okay. Well, now we have more to do. We're just not managing physical boxes, you know, spewed around anymore. I'm also very curious what's coming down the road as it relates to, you know, remote or distributed work. And I'm not feeling like an absolute like, it's absolutely gonna be remote, or it's absolutely not, or I I think it's gonna be some variation of it.

Max: 44:08

But the the demands of flexibility of being able to support your internal and external so your internal, you know, employees and customers and your external customers from anywhere at any time, I I think that has shifted, and and companies are going to be looking at that and thinking about that going forward in a much different way.

Jim: 44:28

Yeah. I think you're right. And 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, leverage that data and 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.

Jim: 44:52

You know? You don't know. You go into the the office. People walk by your your your office or your cubicle, and you get caught up in conversations, and you go to lunch and or you go to the cooler, and that it's another 5 or 10 minute conversation. And the next thing you know, you've lost a third of the day.

Jim: 45:09

And, literally, some customers are measuring market, improvement in efficiency. And so you're right. I don't think it's gonna 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.

Jim: 45:46

I don't know. We'll we'll we'll see how it all pans out. But you can obviously save on lease utilities, all the other office, you know, 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.

Jim: 46:18

I don't know. We'll have to see.

Max: 46:19

You gave 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 and, you know, for rearchitecture, you know, project, you know, how how how is the cloud decision and which cloud I mean, how does that work out? You know, when you when you look at it from a customer standpoint and you're making that recommendation and guidance for them, I mean, what are the big knobs that you're looking at or or decision levers to make you know, to 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 life cycle. Like, ultimately, what we think that they might be doing with their data. But upfront, what we're looking at is so right out of the gate when we're doing an assessment for a migration of the cloud, we're doing a rightsizing exercise. This is the this is one of the number one things that we find customers run into problems is they take a look at their current, resource setup.

Jim: 47:33

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.

Jim: 48:05

We do very, very detailed performance analysis of the servers, 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 an education system on Azure. Then ultimately, what types of tools are you using? What are you ultimately going to do with your data?

Jim: 48:37

All these things matter, in whether one is better over the other. What we're finding more and more is the 2 are starting to come closer together. I'll take a look at, for example, the database world. AWS, great. I don't wanna disparage them.

Jim: 48:57

They've got RDS for Oracle, MySQL, SQL Server, a bunch of other things, and is 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?

Jim: 49:23

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.

Jim: 49:53

You know, some, companies work heavily off the Microsoft stack. They're very comfortable, you know, just building C Sharp services and 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 gonna use that data going forward.

Jim: 50:21

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 if you go there.

Max: 50:36

We we used to call those layer 8 issues. Right? You know, the the the people overlaying everything else that are influencing some other decision.

Jim: 50:44

Yes. Yes.

Max: 50:45

And, of course, Microsoft, if you're an existing EA customer, you know, 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, and and the decision whether or not the company's on Office 365 or G Suite factors in, and are you already on Amazon or not? But, you know, up to up to a certain point, there is a a reasonable amount of portability between the clouds. I mean, you could switch between one and the other if made more sense for you down the road. So, I mean, this isn't necessarily a permanent decision.

Max: 51:13

It's just a this is right with the information that we have. And if that information drastically changed in a year or 2, like, maybe we we we look at this differently.

Jim: 51:22

Yeah. Exactly. You know, and again, how are you gonna 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.

Jim: 51:39

Everything else is around that to make it work. You're looking at in the Azure World Cosmos DB, and you look at Aurora DB 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 1? But that's what's coming out.

Max: 52:07

You've you've invested 1,000,000,000 of dollars to make that happen as the answer to that question. Right?

Jim: 52:12

Well yeah. And and 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 we had a customer that went with Synapse. And Synapse is, you know, very powerful, but it it consumes a lot up in in Azure.

Jim: 52:34

And ultimately, they 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 in one of their offerings. And then that becomes not only a cost effective, better more cost effective solution, but one that solves their problems better.

Jim: 53:12

And then if the ROI on the migration is good, there 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 50% of their compute was running Linux and not Windows. I mean, that's I mean, that's a pretty shocking statistic when you think about Microsoft and Azure, and and the majority of their compute is not running Windows for compute. I mean, that's that that says a lot about what's happening in these cloud platforms and and where these platforms are going.

Jim: 53:46

Yeah. No. I I agree a 100%. I 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 gonna go anywhere.

Jim: 54:02

Who's really gonna use this? Yeah. Linux is stable. We get all that stuff. But you're right.

Jim: 54:06

You know, when you look at companies that are truly analyzing 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 think. You would think that would be a small percentage. I'm fairly certain in the SQL Server world, SQL Server on Linux is still very small percentage. But companies are looking at their stacks, they're looking at stability, they're looking at their internal capabilities. You're right, we're seeing these mixes and matches and combinations of technology that 10 years ago, we probably didn't see nearly as much.

Jim: 54:53

You saw Oracle, Unix, Linux. You saw MySQL, Linux. You saw SQL Server, Windows. And these walls are starting to, break down, and these these technologies are starting to mix.

Max: 55:07

And this goes back to something you said earlier, which is, you know, IaaS or, you know, infrastructure as a service or PaaS. You know? Right? 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 of do you even care about the application, or you just care about putting data into it and retrieving data out of it?

Max: 55:27

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, oh, my management problems are over. You know, you even take a a PaaS solution. You still can have locking blocking, you still can have performance problems. There's a lot of things that don't necessarily solve themselves.

Jim: 55:59

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 there, and it's just gonna run forever without problems. So there is a managed services component here.

Jim: 56:22

Even if that managed services 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 gonna have performance problems, or along the way, you could have still could have corruption. You have to look for things like corruption because if you don't, then eventually, it's gonna 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, you know, velocity and capability. Right? You know, do you bring a managed services provider in that has expertise and is efficient at tracking, you know, these activities and and looking for these things and keeping up to date on these things?

Max: 57:09

Or do you wanna develop that internally and and staff it and support it and train? And or do you wanna focus on your applications and your business? Right? And, like, finding finding that line, you know, it's a very specific question, and it's very personal to each company. Right?

Max: 57:26

Each entity has to figure out where those lines are, you know, for themselves.

Jim: 57:31

Yeah. And, you know, we talked a little bit earlier about the half an SME problem. When you talk about, do you wanna do it internally? Do we wanna 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.

Jim: 57:50

You might need 25% of an FTE for an architect. You might need 25% of an FTE to handle your Azure security setup, creating your availability sets, you know, a a variety of other functions. You might need half an SME to do database administration for you. Or do you really wanna go out and buy or or hire 3, 4, 5 SMEs that are not gonna be fully utilized? Again, that's where I think we can come in and augment an existing staff and help that staff just fill in the gaps.

Jim: 58:27

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 counterproductive to that. And then secondarily, you touched on the other part is, many business 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 data center 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. That's not a new concept. That's been discussed for years years years.

Jim: 59:28

But in the current environment, I think the whole remote workforce enablement, the change, the accelerated potential accelerated change to the cloud has companies rethinking, should we outsource part of our IT function, save some money in the process, and not burn out our internal IT staff that we wanna 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 are coming together, and we'll have to see how it all plays out. But, you know, I think we're in probably the 3rd potentially, the 3rd big change that has happened in the last 10 years.

Max: 01:00:19

I mean, that's crazy to say. Right? In just in just in 10 years. Well

Jim: 01:00:23

Yeah. Yeah. IT moves fast.

Max: 01:00:26

It does. Jim, thank you very much for your time. This was fantastic. I appreciate it. It's been a pleasure.

Jim: 01:00:32

Yeah. Thanks a lot, Max. I really appreciate you having me on, and it was great talking with you as well.

Max: 01:00:40

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.

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