00:00:02.760 --> 00:00:07.710
Alexandra: Right Hello everyone and welcome to today's webinar we're going to be breaking down.
00:00:08.099 --> 00:00:18.780
Alexandra: The merchant cloud trends this year for us state and local governments just let y'all know my name is Alexandra and I will be your MC during the session, so thank you for joining us today.
00:00:19.140 --> 00:00:28.650
Alexandra: Before we begin, I just want to go over a few housekeeping rules for so during the webinar microphones are going to be muted, however, the webinars formatted just be open discussion so.
00:00:28.950 --> 00:00:39.480
Alexandra: If you have any questions, please feel free to put them in the chat at the bottom of your screen the webinar is being recorded and will be sent to everyone, via email after the webinars ended.
00:00:40.140 --> 00:00:46.500
Alexandra: In about you know, two days or so you'll get an email of the recording and then one more thing after the survey.
00:00:47.010 --> 00:00:51.210
Alexandra: After the webinar ends, excuse me survey is going to pop up at the end of the webinar so.
00:00:51.420 --> 00:01:00.150
Alexandra: shouldn't take longer than 30 seconds it's just going to give us some insight on what materials, we should cover for for future webinars and will also include that in the follow up email.
00:01:00.780 --> 00:01:09.240
Alexandra: So with housekeeping rules out of the way I just want to introduce some give some background on our panelists for today's webinar we have miles Brown and Kelly need yes.
00:01:09.540 --> 00:01:19.800
Alexandra: So we have miles, who is the senior cloud and devops advisor at tech data exit certified he's got over 20 years of experience in the IT industry across a variety of platforms.
00:01:20.280 --> 00:01:27.600
Alexandra: he's recognized as an aws authorized instructor champion and a Google cloud platform professional architect an instructor.
00:01:28.020 --> 00:01:32.670
Alexandra: And miles has delivered award winning authorized IT training for some of the biggest copywriters.
00:01:33.120 --> 00:01:40.710
Alexandra: We also Kelly and Kelly has you know over 20 plus years better experience and the technical training world you know through her consultative.
00:01:41.040 --> 00:01:53.370
Alexandra: Sales approach she has helped thousands of students over the years, you know that she's their professional and career goals small learning and adapting to new technologies so with that said and introducing i'd like them to take away.
00:01:55.020 --> 00:01:56.790
Myles Brown: All right, thanks, a lot Alexandra.
00:01:57.990 --> 00:02:12.390
Myles Brown: So this is what we're going to cover today i'm going to cover most of the beginning and then Kelly will talk a little bit about you know how X certified can help specifically state and local government agencies get the training they need.
00:02:13.560 --> 00:02:23.760
Myles Brown: So we're going to start with a just a quick look at cloud usage across the state and local agencies, what kind of workloads people are running we'll take a quick survey of the.
00:02:24.270 --> 00:02:34.320
Myles Brown: Public cloud providers and maybe you know what what each does well then we'll look at sort of three trends that we see in state and local government.
00:02:34.830 --> 00:02:45.930
Myles Brown: And we'll finish off talking about you know how best to you know get your people prepared for you know cloud training, whatever that means it will see that it can mean a lot of different things.
00:02:47.400 --> 00:03:01.200
Myles Brown: So I will start with basically just some some info talk about trends that we see at state and local agency levels, probably the best.
00:03:03.060 --> 00:03:13.260
Myles Brown: Research i've done, you know is talking to customers Kelly, and I talked to customers all the time, finding out what they're trying to do, and you know.
00:03:13.800 --> 00:03:26.040
Myles Brown: A few years ago, obviously cloud was coming a lot of people hey we got to move to the cloud we've got to move to the cloud, but what we saw was the pandemic kind of change priorities, a little bit and for a lot of state.
00:03:28.260 --> 00:03:41.340
Myles Brown: cios there were you know, last year, they did a pretty big survey of the State cios task you know how has the pandemic impacted your your digital government services that demand for them.
00:03:41.790 --> 00:03:48.030
Myles Brown: And of course it's really accelerated right with a lot of places close either periodically or for long periods of time.
00:03:48.390 --> 00:03:54.360
Myles Brown: You know the idea that we should be able to get more and more of these services online, and so what we found was that.
00:03:54.900 --> 00:04:05.940
Myles Brown: You know those big cloud plans got put a little bit on hold, to make sure that you know the services were online, whether they were running in the cloud or not, you know and.
00:04:06.720 --> 00:04:15.630
Myles Brown: A lot of states sort of adopted this cloud smart strategy and, in fact, one of the questions that they asked of the 50 different cios was.
00:04:16.020 --> 00:04:19.590
Myles Brown: Does your organization have a strategy to migrate legacy Apps to the cloud.
00:04:20.340 --> 00:04:33.810
Myles Brown: And 49% of them said, we have a cloud smart strategy for all new applications to deploy to the cloud, and what that really meant was they're looking at a case by case basis of these workloads and saying is this.
00:04:34.230 --> 00:04:50.340
Myles Brown: A good candidate to move to the cloud If so, then let's do so right, and so what does it mean to be a good candidate is it something that will scale a lot better in the cloud, will it be much cheaper in the cloud than possibly running in our own data centers right.
00:04:51.720 --> 00:05:01.770
Myles Brown: Some in here look like 18% of them said, we have a cloud first strategy for all new applications, you know, there are some pushing ahead with hey we're going to the cloud, we know that.
00:05:02.070 --> 00:05:10.980
Myles Brown: Overall, this will save us money, it will scale better it will do all these things better for us, so that is our strategy for any new applications.
00:05:11.370 --> 00:05:21.000
Myles Brown: And then there's a few states that didn't have much, much of a strategy plan in place at all, and they were sort of leaving it up to agency by agency to decide what they were doing right.
00:05:21.660 --> 00:05:39.930
Myles Brown: But you see that most of them either are saying we're cloud first for all new Apps or we're looking at a case by case basis for new and existing Apps to see which ones move to the cloud so when we look at what kinds of workloads these the state and local agencies run in the cloud.
00:05:41.340 --> 00:05:48.720
Myles Brown: You know you get to the cloud in lots of different ways, you know i've dealt with organizations moving to the cloud for about 10 years now.
00:05:49.230 --> 00:05:53.400
Myles Brown: And what we see is that sometimes you go into a cloud because.
00:05:53.940 --> 00:06:00.030
Myles Brown: You know you buy some off the shelf application and it runs in azure, and so we say Okay, well, we have to do azure.
00:06:00.360 --> 00:06:12.360
Myles Brown: You know, even though most of our stuff is either maybe on pram or maybe even in some other cloud this APP wants to run in a particular cloud so we're going to use that cloud for that APP.
00:06:13.650 --> 00:06:23.010
Myles Brown: But most organizations, they start by re platforming they have some existing APP running in their own data Center and they they do a lift and shift into the cloud right.
00:06:23.370 --> 00:06:34.530
Myles Brown: Now, unfortunately, most existing Apps you have already you know you can move them to the cloud that doesn't mean they're going to be able to take advantage of all the benefits that the cloud has to offer right.
00:06:35.130 --> 00:06:42.240
Myles Brown: And so what we found was you know a lot of state and local agencies started to move to the cloud save five six years ago.
00:06:42.780 --> 00:06:46.650
Myles Brown: Then, about a year or two ago they started coming back and saying hmm.
00:06:47.130 --> 00:06:54.210
Myles Brown: We move to the cloud like we learned a lot about the cloud and moving a lot of Apps lifting and shifting them now, we want to.
00:06:54.570 --> 00:07:07.290
Myles Brown: You know re architect those Apps to make them take advantage of all the benefits right, and so this is where you hear this term cloud native applications building cloud native architectures.
00:07:08.070 --> 00:07:21.780
Myles Brown: And so you know, often that that really means we're building containerized microservices maybe we use something like Cooper nettie is to manage all these things, and so that's been a big shift that we see.
00:07:22.830 --> 00:07:24.570
Myles Brown: A major trend that will talk about.
00:07:25.950 --> 00:07:39.000
Myles Brown: another kind of sexy use of the cloud that we see these days is the concept of service architectures where you say i'm going to rely on my cloud vendor for more than just taking care of the physical data Center.
00:07:39.660 --> 00:07:50.730
Myles Brown: They can also take care of the operating system and patch that install my database and patch that you know I can use these sort of managed services that they have or even all the way up to server list.
00:07:51.000 --> 00:08:01.230
Myles Brown: Where you say here's some code here's an event that causes that code to run and I don't think about the physical servers the virtual machines I don't think about any servers.
00:08:01.830 --> 00:08:13.260
Myles Brown: All right, I want to get rid of you know Linux and windows administration completely and so that's a very interesting idea and it's it's really picking up a lot of steam.
00:08:14.250 --> 00:08:21.240
Myles Brown: The last thing that we see is once we've moved to the cloud we got a lot of Apps in the cloud we're generating a lot of data in the cloud.
00:08:21.600 --> 00:08:33.360
Myles Brown: And so now all of a sudden we've got all this data, usually stored in some central place and we say hey This makes analytics really easy because we've got all our data in one place right.
00:08:34.230 --> 00:08:45.450
Myles Brown: Even if we have some Apps that are running in the cloud and some running on Prem it's easy to kind of get all that data throw it all into whatever object storage, you have you know, an aws that would be s3 and.
00:08:45.870 --> 00:08:58.200
Myles Brown: or blob storage and azure where you say hey This is basically a data lake we just dropped all of our data in there and now let's start making use of that data to make data driven decisions.
00:08:58.680 --> 00:09:07.950
Myles Brown: Because that's very popular these days anybody who's a manager wants to be able to say hey I made this decision, because the data pointed in that way.
00:09:09.030 --> 00:09:18.930
Myles Brown: And so Those are some of the big types of workloads we're running in the cloud these days now, I just mentioned aws and azure those are certainly the two biggest public cloud providers.
00:09:19.290 --> 00:09:37.020
Myles Brown: We look at the timeline of when these providers came along aws kind of got their first right they started really a little bit before 2006 2006 when it started to look like it doesn't help it's the oldest and most mature platform it's also the most popular platform.
00:09:38.430 --> 00:09:44.550
Myles Brown: They got a pretty good head start on azure and Google cloud that came out in 2010 2011 right.
00:09:45.000 --> 00:09:55.410
Myles Brown: But as yours been chipping away at that market lead for a while right it's the second most popular it's very popular, especially if you're already a Microsoft shop.
00:09:55.680 --> 00:10:01.560
Myles Brown: right if you're doing a lot of.net development you've got sequel server database is not that much Linux you know.
00:10:02.190 --> 00:10:09.210
Myles Brown: As your mind make a lot of sense Google cloud is very popular with people who do a lot of machine learning and artificial intelligence.
00:10:09.750 --> 00:10:21.810
Myles Brown: And then you've got you know, IBM sort of threw their hat in the ring and Oracle cloud IBM has really fallen off, I would say Oracle cloud is is definitely the fourth place candidate at least outside of China right.
00:10:23.100 --> 00:10:27.600
Myles Brown: And then they're starting to win some business so it's worth looking at at least.
00:10:29.460 --> 00:10:40.380
Myles Brown: Now, when you look at you know what the industry thinks of these you know, probably the best place to get a sense of that is to go to gartner and gartner as.
00:10:41.520 --> 00:10:41.880
Myles Brown: Sir.
00:10:44.670 --> 00:10:45.900
Myles Brown: You know they publish this.
00:10:47.550 --> 00:10:59.610
Myles Brown: magic quadrant every year now the the 2022 one I haven't seen yet, so this is last year's but aws has always at that top right in the Leader category.
00:11:00.030 --> 00:11:12.870
Myles Brown: And they've been there for many, many years Microsoft crept up there, a few years ago and Google even has crept up there, the other two that we don't really talk about our alibaba tencent because they're really only in China.
00:11:14.550 --> 00:11:22.830
Myles Brown: But you know, according to gartner aws continues to be the best in its ability to execute but azure and Google cloud are really getting up there.
00:11:23.760 --> 00:11:39.480
Myles Brown: When we look at market share aws has about a third of the public cloud market as you're used to be about 15 and what's up over 20 then Google cloud, and then you know sort of the other players, IBM cloud is kind of an interesting one.
00:11:40.590 --> 00:11:44.700
Myles Brown: I would say that it's a shrinking it's quickly shrinking yeah.
00:11:46.620 --> 00:11:58.350
Myles Brown: Anyway, that's sort of how things have gone now the case for each well aws is popular sometimes things are popular because they're popular you know it's easy to find somebody who knows aws.
00:12:00.930 --> 00:12:01.800
Myles Brown: there's a lot of.
00:12:02.940 --> 00:12:12.180
Myles Brown: things out there to help you learn it right, it probably has the least amount of downtime of the big three it's hard to get hard numbers on this, I used to have.
00:12:12.900 --> 00:12:19.800
Myles Brown: used to be a pretty good application that would go and look at the downtime of all the public clouds I don't know what happened to them, they seem to have disappeared.
00:12:20.310 --> 00:12:30.150
Myles Brown: But for a long time now aws has had some public outages in fact they had sort of two events last year, and so everybody gets scared you know.
00:12:31.230 --> 00:12:42.180
Myles Brown: When when say azure has an outage you don't hear as much about it, because you know the Internet still fine when aws is down half the Internet doesn't work and people lose their mind.
00:12:43.140 --> 00:12:51.090
Myles Brown: But, but they still seem to be the most dependable of all of them, I would say the best overall in terms of breadth and depth of services.
00:12:51.990 --> 00:13:03.930
Myles Brown: The most mature and popular service options, including aws Lambda, so why would you use anything else, well, a lot of people use azure because it's easy to embrace they already have.
00:13:05.850 --> 00:13:20.820
Myles Brown: They already have licensed they already have contracts with Microsoft because they're probably already using office 365 right if you're a.net shop they've got a great platform as a service for you know.net applications.
00:13:22.050 --> 00:13:33.090
Myles Brown: they're also very popular with hybrid organizations do to azure stack which is sort of a you buy this hardware and you run in your own data Center, but you can run as your services, just like in the cloud.
00:13:33.960 --> 00:13:39.150
Myles Brown: Now the other vendors have that but, but as your stack seems to be the most popular of those.
00:13:40.200 --> 00:13:46.950
Myles Brown: And last thing either had a presence in many other countries, you know this isn't so interesting to you to state local people, but.
00:13:47.910 --> 00:13:57.810
Myles Brown: But you know that that they did get some popularity in Europe because they had presence in countries that maybe the other cloud vendors took a little while to get there.
00:13:58.170 --> 00:14:10.290
Myles Brown: So so as you're picked up some market share, just because of that now Google cloud is a very distant third place, but it is pretty popular with organizations that are heavy in machine learning right.
00:14:10.800 --> 00:14:16.050
Myles Brown: Google actually built tensorflow, which is a very popular framework for doing machine learning.
00:14:16.800 --> 00:14:23.580
Myles Brown: Based on their deep expertise of you know r&d and machine learning, and so they do a pretty good job of running that.
00:14:23.850 --> 00:14:37.950
Myles Brown: Now, Google also created Cooper daddy's and they do a great job of managing they have a gk he the Google Cooper daddy's engine for running those kinds of workloads but all the cloud vendors have some sort of Cooper daddy's service to make it easier.
00:14:39.570 --> 00:14:53.400
Myles Brown: Google cloud you I mean it's hard to say again, but they may have the cheapest pricing it's very hard to compare given enterprise agreements and volume discounts it's very hard to get an apples to apples kind of comparison.
00:14:54.750 --> 00:15:03.420
Myles Brown: When it comes to hybrid environments, they do have something called an SOS which helps them with hybrid and multi cloud environments aws also has something called outposts.
00:15:03.750 --> 00:15:10.470
Myles Brown: But I would say again if you're more if you're really serious about the hybrid thing as your tends to be where people go for that.
00:15:12.090 --> 00:15:20.820
Myles Brown: For running the exact same workloads on Prem and in the cloud and and maybe you know, having to really control that on Prem stuff.
00:15:22.350 --> 00:15:28.230
Myles Brown: But here's The thing that we find is that hybrid and multi cloud is a very big trend that we see right.
00:15:28.530 --> 00:15:30.840
Myles Brown: People don't want to put all their eggs in one basket now.
00:15:31.050 --> 00:15:41.730
Myles Brown: You kind of have to figure out what what do we mean when we say multi cloud is hybrid part of that or not, you know, because sometimes you'll see a diagram like this, this is from FLEX era state of the cloud report.
00:15:42.090 --> 00:15:48.420
Myles Brown: Where you know of all the enterprises that they looked at 92% they considered multi cloud.
00:15:48.840 --> 00:15:58.590
Myles Brown: But that multi cloud was still most of them were just hybrid cloud where they have some workloads running in their own data Center in some in the cloud and some sort of framework to make that work.
00:16:00.210 --> 00:16:08.310
Myles Brown: Not that many people had production workloads in multiple public clouds but we're starting to see that a lot more, because some of the.
00:16:09.150 --> 00:16:14.280
Myles Brown: Certainly, you know, in the federal government that seems to be a big push.
00:16:15.240 --> 00:16:25.050
Myles Brown: State and local is is less of a big push but we're seeing it more and more now why would you do this, I mean hybrid kind of makes sense, you already have data centers.
00:16:25.380 --> 00:16:34.920
Myles Brown: You invested dash in building them and filling them right you're not just going to turn your back on that you've already got them, so you wouldn't throw them away.
00:16:35.340 --> 00:16:41.640
Myles Brown: So hybrid cloud makes a lot of sense and a lot of times when you start with hybrid and you start using the cloud.
00:16:42.060 --> 00:16:59.730
Myles Brown: Maybe, just as excess capacity and we sometimes call that cloud bursting right so where you primarily run your workloads on Prem, but when things get really busy right maybe you run some of those exact same workloads in cloud now here we're running this webinar on zoom.
00:17:00.780 --> 00:17:05.520
Myles Brown: At exit certified we've been using zoom for our virtual training, since it came out in 2014.
00:17:06.030 --> 00:17:16.470
Myles Brown: And they told us early on, because we helped them beta test, a lot of stuff they said they were at that point running everything in their own data centers but they we use aws when things got busy now.
00:17:16.860 --> 00:17:24.150
Myles Brown: A few years later pandemic starts, all of a sudden zoom gets very, very popular now they're using multiple cloud vendors for excess capacity.
00:17:26.220 --> 00:17:40.200
Myles Brown: But, but another reason people go multi cloud is they want to use multiple public cloud vendors, to avoid lock in maybe or to take advantage of the sweet spots that each provider does best right.
00:17:40.800 --> 00:17:50.730
Myles Brown: there's not that many organizations that are really, really running the exact same workload, you know and saying hey I don't care whether this runs in aws or azure or Google cloud.
00:17:51.600 --> 00:17:54.840
Myles Brown: If you did want to be able to do that, to really get rid of that.
00:17:55.470 --> 00:18:01.740
Myles Brown: You know vendor lock in the problem is you kind of have to use them, the lowest common denominator.
00:18:02.040 --> 00:18:11.100
Myles Brown: You know what to every cloud vendor half they have this concept of a virtual machine that I can run and a bit of storage, you know, but I can't use all the bells and whistles.
00:18:11.610 --> 00:18:21.180
Myles Brown: So if you're going to run those kind of multi cloud workloads you might be trying to rely on some sort of a framework that might provide some of that.
00:18:21.450 --> 00:18:34.350
Myles Brown: You know platform as a service kind of thing, so these days, something like red hat open shift is a very popular way of building cloud agnostic workloads but you still get some cool services around it.
00:18:35.910 --> 00:18:46.890
Myles Brown: Even Cooper nettie is helps with that little bit speaking of Cooper daddy's you know trend number two is cloud native technologies and that's that's the hottest buzzword probably these days.
00:18:48.120 --> 00:18:54.990
Myles Brown: it's a big idea where we incorporate a lot of the devops concepts to try and get the most out of public cloud usage.
00:18:55.440 --> 00:19:00.210
Myles Brown: And in fact there's a consortium of companies call you know, called the cloud native computing foundation.
00:19:00.990 --> 00:19:09.630
Myles Brown: And, basically, you know their idea is, we want to build and run scalable applications in modern, dynamic environments like public private hybrid clouds.
00:19:10.170 --> 00:19:16.530
Myles Brown: And what are the technologies we're going to use to do that containers service meshes microservices and so on.
00:19:16.830 --> 00:19:26.910
Myles Brown: And the big idea is we're going to get loosely coupled systems that are resilient manageable observable really able to take advantage of all that the cloud has to offer.
00:19:27.420 --> 00:19:37.290
Myles Brown: Now, you may not be a very technical person and so we're not going to go too far down this road, but I do want to kind of highlight a couple of those terms, a little bit.
00:19:37.860 --> 00:19:41.970
Myles Brown: First, one is that concept of microservices right, and this is a.
00:19:42.690 --> 00:19:52.440
Myles Brown: Pretty big buzzword these days in development if you build your own software well most organizations used to build their software as one big unit right.
00:19:52.710 --> 00:20:03.720
Myles Brown: Okay here's my application and we called it, you know continue considered a monolith it's got everything in one executable and so that unit of deployment is the whole application.
00:20:04.290 --> 00:20:13.050
Myles Brown: it's not very easy to work on little parts of the application and independently build them and test them and scale them and iterate on each one separately.
00:20:13.620 --> 00:20:24.540
Myles Brown: And so the idea of microservices is let's take this big monolithic application and blow it up into hundreds or even thousands of little micro services and they just do sort of one you know.
00:20:25.290 --> 00:20:34.950
Myles Brown: One main task, and then you know the micro services can be independently built tested scaled and then you compose them together to build your applications.
00:20:35.790 --> 00:20:50.190
Myles Brown: And in devops parlance, we might use a to pizza team, which is you know this small cross functional group of maybe a few developers a couple testers one or two operations people you know you make a group of maybe eight or 10 people.
00:20:50.670 --> 00:21:07.800
Myles Brown: And they're in charge of a few microservices from end end right build the roadmap gather the requirements build the micro service test it put it into production, you know support it in production make changes to it over time and you're in charge of that whole thing.
00:21:08.880 --> 00:21:20.640
Myles Brown: To pizza team is that term that you know Amazon COM actually you know that's how they they blew up their big application back in the early 2000s from a monolith into thousands of microservices.
00:21:20.970 --> 00:21:24.090
Myles Brown: And then they have these various teams working on different microservices.
00:21:24.810 --> 00:21:33.150
Myles Brown: Now, how to implement those well one way to implement them it's become very popular is this concept of containers, you might have heard the term docker right.
00:21:33.540 --> 00:21:42.510
Myles Brown: there's there's different ways to build containers and Linux certainly at containers long before, but when docker came out in 2013 it quickly became very popular.
00:21:43.530 --> 00:21:49.800
Myles Brown: The idea of these docker containers, you could run them anywhere, so I could build this container on my laptop.
00:21:50.070 --> 00:22:03.570
Myles Brown: And then I could I could easily you know provide that to somebody and they could put it into our on Prem data Center or launch it into a cloud, and it was always the same, it was the code and all the dependencies and it ran the same, no matter where it went.
00:22:03.990 --> 00:22:10.680
Myles Brown: So that got us over the hump of some of the problems of development, where a development team builds the APP gives it to the production.
00:22:10.980 --> 00:22:18.570
Myles Brown: P, you know the the operations team to put into production and then all of a sudden it's broken, because that environment doesn't quite look like our development environment.
00:22:19.110 --> 00:22:27.390
Myles Brown: They kind of got around that and it was a nice way to implement microservices docker hub was a nice way of finding existing containers and building on top of them.
00:22:27.900 --> 00:22:41.190
Myles Brown: And you can't discount this doctor had a pretty good logo, you know it all kind of hit at the right time and it became very, very popular, and so this idea of containerizing your applications made a lot of sense.
00:22:41.850 --> 00:22:49.560
Myles Brown: The problem is, if you've got hundreds of these little containers, maybe and you're running multiple of them, you could have thousands of containers that you have to deal with.
00:22:50.460 --> 00:22:57.840
Myles Brown: And the job deciding where to host these you know hey if i've got a bunch of physical machines, where, am I going to run all these things.
00:22:58.800 --> 00:23:10.650
Myles Brown: And load balancing across them you needed some sort of container orchestration tool, and so the docker team created something called swarm there were some other options aws built something called PCs.
00:23:11.130 --> 00:23:14.820
Myles Brown: But the one that really stuck came from Google and it's called Cooper nettie.
00:23:15.510 --> 00:23:28.350
Myles Brown: And it's kind of become the de facto standard and so now everybody who's doing containers, not everybody, but, most people doing containers are saying hey i'm going to manage all these containers using a framework called Cooper 90s.
00:23:29.250 --> 00:23:46.140
Myles Brown: And, of course, you know running Cooper nettie there's a little bit overhead in there and some some management to do well all the cloud vendors have now created services to help with that, and so, no matter which public cloud you're in they've got a service to help you run that.
00:23:47.610 --> 00:23:54.300
Myles Brown: The other way to implement microservices if you don't want to go down that container road is well like I said before, service.
00:23:54.690 --> 00:24:02.610
Myles Brown: Where where you write a function it's very developer centric and developer writes some code and then says here's the event that causes that code to run.
00:24:02.880 --> 00:24:13.320
Myles Brown: could be hey somebody uploaded a file okay that kicks off this code to run and look at that file and do something with it or it's Friday night at 10pm.
00:24:13.800 --> 00:24:20.430
Myles Brown: Based on that time of day that's an event go run this code right, you can have all kinds of things that cause the code to run.
00:24:20.910 --> 00:24:29.820
Myles Brown: And the idea is you no longer worried about the servers the operating system high availability scalability deploying the code somewhere.
00:24:30.180 --> 00:24:37.440
Myles Brown: You know, as a developer I write the code, I say and I write it as an event driven model, so I say here's the event that causes the code run.
00:24:38.040 --> 00:24:48.660
Myles Brown: Where does it run I don't know I don't care it's a bit of a misnomer obviously their server somewhere, but they're not servers I worry about it Okay, all I do is pay for how long that code takes to run.
00:24:49.740 --> 00:24:59.460
Myles Brown: In aws it's called Lambda that's the service compute service in azure they have, as your functions Google cloud as Google cloud functions, you know very, very similar content.
00:24:59.850 --> 00:25:08.910
Myles Brown: Is that is becoming kind of the big thing to a nice way, so this is another alternative for doing those cloud native microservices.
00:25:09.960 --> 00:25:19.260
Myles Brown: Now the last trend that we see is all about cloud analytics machine learning Ai so it's probably best to talk a little bit about the different kinds of analytics.
00:25:19.770 --> 00:25:27.870
Myles Brown: The first kind of analytics we run into is called descriptive analytics, and this is where you're sort of looking looking backwards in time.
00:25:28.170 --> 00:25:38.250
Myles Brown: And you say what has happened right, so our data we've been collecting data and putting it into data warehouses for 20 years you know 30 years 40 years probably.
00:25:39.420 --> 00:25:53.550
Myles Brown: We use bi tools like IBM cognos or power bi or tablo is a very popular tool, where I can connect to a relational database and build dashboards and reports and it's basically just.
00:25:53.910 --> 00:26:03.090
Myles Brown: You know, writing some sequel queries for me under the covers so we get people that are very good at at being able to take that data and translated into information that.
00:26:03.420 --> 00:26:10.200
Myles Brown: Non technical people can use right we've been doing that for a long time right so it's kind of looking backwards.
00:26:10.530 --> 00:26:18.300
Myles Brown: The next step is where you're looking for predictive analytics forecasting right that kind of thing this is where you make use of machine learning.
00:26:18.690 --> 00:26:22.650
Myles Brown: And this is where most people are now right we've been doing.
00:26:22.950 --> 00:26:29.160
Myles Brown: descriptive analytics and we will continue to do that predictive analytics is where you know we're starting to do a lot of machine learning.
00:26:29.370 --> 00:26:41.460
Myles Brown: Now machine learning is something that's been around for a while now, it used to be the purview of just a few nerds who really knew a lot about math and computers and, whatever your problem domain is.
00:26:42.300 --> 00:26:51.000
Myles Brown: But the problem is now there's a lot of companies where that machine learning is doing mission critical stuff, and so we really have to get this right.
00:26:52.080 --> 00:26:59.850
Myles Brown: The last sort of step would be what we call prescriptive analytics where we say what to do right, it makes heavy use of machine learning but.
00:27:00.630 --> 00:27:10.860
Myles Brown: If this happened What should our business do right very different kind of idea and just to get these three types of analytics you know kind of straighten your mind i've got a little anecdote.
00:27:11.430 --> 00:27:25.260
Myles Brown: here's the anecdote let's say we have a lioness you know she's there in the jungle and she's very lazy but she's rich so she hires a data scientist to say, I want to help and help me hunt for creatures in the jungle.
00:27:26.040 --> 00:27:34.140
Myles Brown: Well, the first thing the data scientists does they study historical data and provide the lion is with report of where did she find her prey in the last six months.
00:27:34.380 --> 00:27:41.850
Myles Brown: which should help her decide where where she should go hunting right that's that first level descriptive analytics looking and saying hey our best.
00:27:42.330 --> 00:27:45.240
Myles Brown: prediction of the future is what happened in the past right.
00:27:45.780 --> 00:27:53.970
Myles Brown: Next, the data scientist estimates the probability of finding given pray at a certain place in time using some advanced machine learning techniques.
00:27:54.240 --> 00:28:05.220
Myles Brown: that's where we really get into forecasting predictive analytics so instead of her just looking at what has happened in the past and make guesses about the future we've got better predictions right.
00:28:06.000 --> 00:28:12.720
Myles Brown: But the next level is where the data scientists goes and identifies roots in the jungle for the lioness to take.
00:28:13.050 --> 00:28:21.300
Myles Brown: And maybe and maybe digging some trenches in certain places, so that she can really minimize her efforts at finding bread.
00:28:21.750 --> 00:28:36.690
Myles Brown: Right that's where you're really doing some some optimization right and and into you know that idea of hey even digging the trenches for us so that we can really you know make our life easy.
00:28:37.830 --> 00:28:49.320
Myles Brown: So that's that's different kinds of analytics now why would we want to do this in the cloud well first off we said a lot of applications are moving to the cloud, so the data is there already right so it's a good place to do it.
00:28:50.370 --> 00:28:59.970
Myles Brown: And you can use many of the same analytics techniques that you've been familiar with right so for since the 90s i've been doing data warehousing my first data warehouse I built was in 1997.
00:29:00.540 --> 00:29:09.300
Myles Brown: We took data from a few different transactional databases, we extracted transform it loaded into a data warehouse right, so we call that atl.
00:29:09.780 --> 00:29:18.600
Myles Brown: The data warehouse itself was just a huge relational database, but one that was tuned for the kinds of queries that we asked in in analysis.
00:29:19.230 --> 00:29:30.540
Myles Brown: And then you connect your bi tools your business intelligence tools to it right, and so, most of the data warehousing and atl tools and bi tools, you can use those in the cloud or outside of the cloud that's fine right.
00:29:30.960 --> 00:29:41.280
Myles Brown: But what we really see is that the cloud does offer some really nice benefits when the data gets big and these days everybody's got big data right if you've got a popular website.
00:29:42.150 --> 00:29:47.700
Myles Brown: You know, every time somebody clicks there's a lot of data being collected right, and so you have big data.
00:29:48.270 --> 00:29:58.350
Myles Brown: And what we find is that the cloud has very cheap very durable storage and seemingly infinite scalability right and often seamless scalability.
00:29:58.800 --> 00:30:08.910
Myles Brown: And so that fits really well with big data right we have this sort of saying you know i'm a hadoop guy I have been doing for a long time now, you know.
00:30:09.420 --> 00:30:19.590
Myles Brown: We have the same if it takes 10 machines 10 hours, it takes 100 machines one hour right that's assuming whatever you're processing is can be sufficiently parallelized.
00:30:19.890 --> 00:30:31.530
Myles Brown: 10 machines takes 10 hours 100 machines would only take one hour right, the problem is in the old on Prem days I can't afford to go buy 100 machines, maybe I don't have that much capital to spend right now right.
00:30:33.180 --> 00:30:37.050
Myles Brown: But in the cloud it turns out, where you pay by the hour for vm.
00:30:38.310 --> 00:30:55.980
Myles Brown: 10 machines for 10 hours is the exact same price is 100 machines for one hour, so the economics of the cloud really make it better to do things you know massive scale hey I can let's get 100 Meg let's get 1000 machines running in parallel and get this job is done as quickly as possible.
00:30:57.330 --> 00:31:07.440
Myles Brown: And the public cloud vendors all offer really great services, so you don't have to go in and even use the traditional hadoop distribution and go and install that on a bunch of vm in the cloud.
00:31:07.860 --> 00:31:14.550
Myles Brown: They all have some sort of hadoop service already, and maybe even a server this one, where you don't have to think about the server.
00:31:16.320 --> 00:31:31.080
Myles Brown: And then you look at some of the newer cloud analytics companies and they work well with data in the cloud so so companies like snowflake and data bricks you know they'll they they know your data is sitting in aws s3 buckets and that's what they expect to grab it from the news.
00:31:32.160 --> 00:31:42.810
Myles Brown: Well, that that next level of machine learning sort of data science type of thing we find that hiring data scientists is hard right there's been a big glut you know in in.
00:31:43.290 --> 00:31:48.930
Myles Brown: How many data scientists were graduating you know they've been working on it for a while.
00:31:49.140 --> 00:31:57.480
Myles Brown: But the problem is that a data scientist is somebody who's pretty good at math they know stats really well, they also know computer science, they have hacking tech skills.
00:31:57.840 --> 00:32:03.540
Myles Brown: And they have some expertise in the domain, whatever your business is doing whatever your your application is.
00:32:04.230 --> 00:32:11.220
Myles Brown: So if hiring a data science hard to do then maybe we take somebody who has two of these and teach them the third one right.
00:32:12.150 --> 00:32:19.410
Myles Brown: Now the hope is that in the future machine learning expertise just becomes another sort of tool in the engineers tool belt.
00:32:20.280 --> 00:32:29.730
Myles Brown: And this is happening right we're starting to say that you know because it's hard to find machine learning expert maybe a product that has machine learning built into it already.
00:32:30.360 --> 00:32:49.800
Myles Brown: is good so there's a lot of auto ml tools, this is a big a big trend we're seeing, not just in state local but across the entire industry we're seeing a lot of applications that have machine learning built into them so that we don't have to all be experts in data science.
00:32:51.720 --> 00:33:02.250
Myles Brown: And the other big thing we're seeing analytics is the automation of all the tasks involved in grabbing the data and massaging it and putting it cleaning it up and getting it where we need to.
00:33:04.050 --> 00:33:06.060
Myles Brown: You know, trying to to sort of.
00:33:08.460 --> 00:33:16.560
Myles Brown: automate all those mundane repetitive tasks, so, in the end, you know we see there's a lot things happening in the cloud.
00:33:17.400 --> 00:33:29.130
Myles Brown: And that's because moving to the cloud isn't as simple as hey we're changing from Oracle database to postgres you know if that's all it was you wouldn't hear people talk about the cloud every day right moving to the cloud.
00:33:29.640 --> 00:33:40.530
Myles Brown: Is is not just changing who runs the data Center although that's certainly part of it right, I want to get out of the business of building and running and scaling data centers and just.
00:33:41.040 --> 00:33:44.190
Myles Brown: Let that somebody who does that really well do that right.
00:33:44.700 --> 00:33:59.280
Myles Brown: So most organizations, when we move to the cloud or cloud journey is probably three things one, yes, we start using a public cloud provider, but to We further embrace devops those culture and tools right, so that we can build.
00:33:59.970 --> 00:34:08.370
Myles Brown: Software quickly and make changes quickly and maybe the third is adopting microservices architecture to get the most out of that cloud.
00:34:09.510 --> 00:34:21.240
Myles Brown: And really what that means for most people who are in charge of it teams is that moving to the cloud can mean having to learn all kinds of new skills and various technologies.
00:34:21.870 --> 00:34:33.270
Myles Brown: Now, at exit certified we're partnered with all the major cloud providers, and we certainly have their authorized training you want aws training, you want to add your training Oracle cloud training we got it all.
00:34:34.050 --> 00:34:40.410
Myles Brown: So where there's a vendor of choice we partner with that, but that's just the beginning that's the public cloud training.
00:34:40.830 --> 00:34:53.100
Myles Brown: around it we've now got this whole suite of different kinds of training that you might need now, I see Alexandra put into the chat the link for this cloud centric that's what we call our sort of.
00:34:53.940 --> 00:35:04.710
Myles Brown: suite of offerings and so a lot of it has to do with containers and cloud native or devops kind of practices automation is a big part of it.
00:35:05.670 --> 00:35:13.980
Myles Brown: Private and hybrid cloud, and some of the some of the tools people use like vmware or open shift to make that happen and then all the sort of analytic stuff we talked about.
00:35:14.610 --> 00:35:19.500
Myles Brown: And so we kind of look at it, as hey when somebody comes to you and says, I need cloud training.
00:35:20.010 --> 00:35:32.250
Myles Brown: You got a few questions to get to the root of what do you really mean do you need a couple of introductory classes from aws or are you going to have to start doing containers and Cooper nettie you know what does that really mean.
00:35:32.790 --> 00:35:49.710
Myles Brown: And so, this is what we've been using to talk to customers for a little while now and Kelly talks to our customers all the time, especially the state and local customers that's that's been her business for 20 years we both worked for exit certified since.
00:35:51.270 --> 00:35:52.350
Kelly Nevius: 2001.
00:35:52.710 --> 00:35:52.950
00:35:54.540 --> 00:35:57.030
Myles Brown: I guess, I guess, I technically came in 2000.
00:35:59.010 --> 00:36:10.950
Myles Brown: I was contractor, I was in and out a bunch of times but i've been here full time for a long time, and so you know, maybe Kelly, you can talk to what are some of the things we can do specifically for state and local.
00:36:12.300 --> 00:36:13.650
Myles Brown: government agencies.
00:36:13.890 --> 00:36:27.810
Kelly Nevius: Okay perfect yes thanks miles Thank you everyone for joining us today I do see several familiar names and as Alexander mentioned after the session you're going to receive an email with a couple questions so we'd appreciate, if you take a minute.
00:36:28.530 --> 00:36:33.180
Kelly Nevius: fill that out for us give us some feedback on what would be of interest for a future topic.
00:36:34.230 --> 00:36:54.570
Kelly Nevius: So how can we help our government customers, well, we have a few contracts in place that make procurement easy, we have our GSA and our cms contracts, the GSA is available to not only federal agencies but also state local and education institutions, these contracts are quick and easy.
00:36:55.980 --> 00:37:06.840
Kelly Nevius: quick and easy way to procure training at discounted prices, we also offer a prepaid training account where you can bank your training funds for a year or more.
00:37:07.200 --> 00:37:24.990
Kelly Nevius: Based on a training plan that we can help put together for you, you receive monthly statements, reflecting the classes that have been booked against the account and the employees that took each class so there's accountability there and then we also release promotions, from time to time.
00:37:26.100 --> 00:37:26.730
Kelly Nevius: And so.
00:37:27.810 --> 00:37:35.520
Kelly Nevius: yeah Thank you currently we have our summer promotion, which is valid for classes booked by August 29 so you only have a few more weeks left.
00:37:36.120 --> 00:37:50.700
Kelly Nevius: And you just have to complete the course by November 30 2022 so you receive $100 off each day of training so, for example, a five day class on our public schedule, you would receive $500 off.
00:37:51.930 --> 00:37:59.070
Kelly Nevius: If we do a private class, for your team, then you can take off $500 per day of the training.
00:38:00.180 --> 00:38:09.270
Kelly Nevius: Now, if our GSA price for the course is less than the summer promotional price you're entitled to the GSA price okay.
00:38:10.710 --> 00:38:14.760
Kelly Nevius: And then, as far as benefits of working with exit certified.
00:38:15.930 --> 00:38:22.740
Kelly Nevius: Thank you miles, so I would be your dedicated account manager for those that haven't worked with us yet.
00:38:23.610 --> 00:38:31.260
Kelly Nevius: Like Michael said i've been with the Organization for over 20 years i've worked with both public and private sector currently i'm.
00:38:32.100 --> 00:38:40.500
Kelly Nevius: Strictly working with public sector, I understand the government and the various procurement processes that are in place.
00:38:40.980 --> 00:38:52.470
Kelly Nevius: And I am quick to respond and easy to work with customer service is my priority, and I know how difficult in this day and age, it is to get good customer service.
00:38:53.460 --> 00:39:02.340
Kelly Nevius: And we also have a very seasoned bench of instructors that are cross trained across the various technologies like miles, for example.
00:39:03.900 --> 00:39:11.280
Kelly Nevius: And we do consider ourself a one stop shop, as you saw on the last slide of the cloud centric diagram.
00:39:11.700 --> 00:39:28.620
Kelly Nevius: We offer training for all of those vendors, we can help with most if not all of your training requirements, and if there are classes, that your team needs that you can't find on our website reach out to me, and if and i'll do research and see if it's something that we can offer for you.
00:39:28.950 --> 00:39:40.350
Myles Brown: yeah that's that's one of the big things we've been doing is is really you know there's there's emerging technologies, where we don't we don't have it on our website, yet, but we have this large roster of.
00:39:41.130 --> 00:39:51.420
Myles Brown: contractors that we We very much trust, some of them work for us exclusively, but they are external contractors and they are usually closer to.
00:39:51.870 --> 00:40:01.920
Myles Brown: You know the the newest projects, and so you know there's always some new open source project and they say okay i've got training on that if there's a vendor of nope we're typically.
00:40:02.190 --> 00:40:12.390
Myles Brown: partnered with that vendor and will offer their authorized training, but those little little Open Source things that fall through the cracks we usually have somebody that we can find that knows it.
00:40:13.050 --> 00:40:22.710
Kelly Nevius: Yes, absolutely and then we also have flexible training programs and format so, for example, live virtual training that's what we're doing today over zoom.
00:40:23.130 --> 00:40:30.930
Kelly Nevius: We call this I mvp because it's more than just virtual we have a live producer like Alexandra.
00:40:31.170 --> 00:40:42.660
Kelly Nevius: She works with our students to ensure they're they're logged in their audios working their videos working and that just allows our instructor to focus on delivering the training for the class.
00:40:43.380 --> 00:40:49.680
Kelly Nevius: So that's that's something that I don't think other vendors offer and we're very proud of that.
00:40:51.060 --> 00:41:02.370
Kelly Nevius: We can also deliver on site training at your facility and we do we've opened up our training centers again across the US, so we can also you can send your stuff to our training centers.
00:41:03.660 --> 00:41:08.250
Kelly Nevius: We also have self paced training, so if that's of interest to your employees, we can offer that.
00:41:09.210 --> 00:41:19.500
Kelly Nevius: But the big thing is, we have are the largest guaranteed to run schedule in North America and that's huge you're working on projects, you have deadlines your staff needs to be trained by a certain date.
00:41:20.040 --> 00:41:30.030
Kelly Nevius: Having that guarantee to run is you can ensure that your employees will get the training when they need it so that's that's a huge huge benefit.
00:41:30.570 --> 00:41:40.500
Myles Brown: yeah yeah and we are starting to get more and more onsite requests, you know I think probably before the pandemic we're probably doing about 60% virtual 40%.
00:41:40.890 --> 00:41:55.140
Myles Brown: either in our Center or on site had a customer and then that just switched to 100 for a while now we're starting to open up our training centers we're starting to get more requests and our instructors are ready to travel for sure.
00:41:56.220 --> 00:42:02.640
Myles Brown: Some of them, you know thrive on the travel but but yeah the the guaranteed to run thing is big for us.
00:42:03.540 --> 00:42:12.630
Myles Brown: Certainly, our aws schedule, you know all the major classes, you know you can find an architect on aws class at least one a week.
00:42:13.380 --> 00:42:28.140
Myles Brown: That is guaranteed to run and that's that's difficult to find in a lot of vendors, we are just starting to get back into Oracle cloud infrastructure and we're going to GT are some of those dates, we are now GT hiring a bunch of as your classes.
00:42:29.820 --> 00:42:32.340
Myles Brown: Even if you run if you've got.
00:42:32.370 --> 00:42:47.490
Myles Brown: You know, four or five people, we can probably quickly flip it the gdpr you know what I mean but, but you know the nice thing is when you only have one or two people that need to take the class that guaranteed to run is is very, very good.
00:42:48.600 --> 00:42:51.090
Myles Brown: I guess, we need to figure out how to contact you Kelly.
00:42:51.150 --> 00:42:51.870
You got some info.
00:42:52.950 --> 00:42:56.520
Myles Brown: yeah Alexandra can throw that in the chat as well, so people have it.
00:42:57.480 --> 00:43:03.180
Kelly Nevius: Excellent absolutely any questions reach out i'm happy to help.
00:43:04.350 --> 00:43:17.370
Kelly Nevius: You know if you have training for your team, and you need you know some some direction i'm happy to set up a call with miles or one of our other season instructors to kind of run through the the requirements and see how we can help.
00:43:18.690 --> 00:43:19.410
Myles Brown: Excellent.
00:43:20.550 --> 00:43:27.030
Myles Brown: All right, well, I think that's our main our main content we left ourselves a bit of time for questions.
00:43:28.200 --> 00:43:37.320
Myles Brown: I see one question here is about the oh yeah we mentioned here a dedicated training portal they asked what is that.
00:43:37.860 --> 00:43:39.390
Kelly Nevius: So, so we have.
00:43:40.500 --> 00:43:49.590
Kelly Nevius: A government portal so essentially you can register you use your government email address, and what will populate is the GSA price.
00:43:50.700 --> 00:43:56.550
Kelly Nevius: And if, for some reason it doesn't populate just email me call me, and I can figure it out for you.
00:43:57.450 --> 00:44:09.060
Myles Brown: Okay, so that link that we put in for government training solutions that will take you to it's basically a skin version of our website that just has different pricing for GSA right.
00:44:09.240 --> 00:44:12.870
Kelly Nevius: Correct yes dedicated to our customer our government customers yes.
00:44:13.080 --> 00:44:20.580
Myles Brown: We can even you know what we've done for certain customers is if you've got a project, where you say well we're taking some aws training.
00:44:20.820 --> 00:44:34.170
Myles Brown: we're taking some non vendor you know some other $8 docker training and some machine learning and so instead of pointing people to our public website that's got.
00:44:34.650 --> 00:44:41.820
Myles Brown: You know, thousands of courses that we can we can kind of skin it just for your agency.
00:44:42.270 --> 00:44:58.020
Myles Brown: So that you see only the courses that you've authorized, and then a lot of times we hook that in with that with that FLEX account so that they don't even have to credit card, you know it all just chips away at that that money that you parked with us.
00:44:58.470 --> 00:45:15.180
Myles Brown: So we can always do that you know, usually we only do it when there's a kind of a larger program at work, but but that's that's another kind of way that we can build like a dedicated training portal just for your agency or just for this project really.
00:45:17.100 --> 00:45:21.990
Myles Brown: that's it's pretty easy for us to do it, so we don't we don't charge for that everything's pretty easy.
00:45:23.130 --> 00:45:25.770
Myles Brown: um any other questions.
00:45:44.250 --> 00:45:46.020
Myles Brown: You can just throw them in the chat you know, like.
00:45:47.070 --> 00:46:03.240
Myles Brown: Kelly was saying we we use zoom as our as our the backbone of our I mvp you know virtual training platform, but obviously this is a more of a webinar style where where we just chat in a regular class where you might have a dozen people you know.
00:46:03.840 --> 00:46:14.130
Myles Brown: We very much encourage everybody to turn on their cameras and the unmute and ask questions, it feels like a regular class, this is sort of so we can open it up to as many people as possible and.
00:46:14.700 --> 00:46:26.580
Myles Brown: We don't have to worry about everybody being off mute and everything else, so this is a little different experience than our normal classes, but, but if you can find the chat you can throw questions in there.
00:46:28.890 --> 00:46:32.220
Myles Brown: Anything else anything else on your end Kelly.
00:46:33.150 --> 00:46:39.780
Kelly Nevius: I don't think so Alexander did you put the survey link or that will come out after the session.
00:46:39.930 --> 00:46:50.070
Alexandra: Correct so once I am the webinar there's going to be a pop up of that survey again two questions 30 seconds of your time it's just going to help us generate some ideas on what future content that we can.
00:46:50.340 --> 00:47:07.380
Alexandra: go over for some future webinars so greatly appreciated any feedback that would be great again, we also are sending out this recording in a post attendee webinar and that will also include the survey link, so we just ask that you fill that out with you have 30 seconds of your time.
00:47:08.100 --> 00:47:20.460
Kelly Nevius: awesome and please take advantage of our summer promotion, you have a few more weeks August 29 complete the class by November 30 so thanks again for your time today thanks miles thanks Alexandra yeah.
00:47:20.490 --> 00:47:24.000
Alexandra: Thank you miles and Kelly great lot of information, and thank you all for joining today.