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Using Google Cloud for data success

17 minutes and 30 seconds
Using Google Cloud for data success
Written by
Ryan Boog
Podcasts | Published January 7, 2021

On today's episode, we will be speaking with John Dingler of Shadow Soft about how using GCloud can bring data success for any business.

John is a savvy industry vet with a wealth of knowledge regarding cloud infrastructure. We used this opportunity to tie in his knowledge with practical business use cases.

Here is what was said on the podcast:

Welcome everybody to season 2 of The Happy Dog Sound Bytes podcast today's special guest is John Dingler with Shadow-Soft. Without any further introduction let's just dive right into it.

R: John, how are you doing?

J: I'm good Ryan. How are you doing?

R: I’m doing well. Thanks for sharing some of your time with us today. So instead of me giving you a big long intro, I'd like for you to tell me a little bit more about yourself and your business.

J: My name is John Dingler and I am at Shadow Soft. We are a systems integrator. We really want to focus on growing software companies to enable them to scale the infrastructure to meet user demand. Whereas traditional infrastructure where you had to procure and time intensive resourcing of infrastructure prohibited fast and efficient scaling. So we really want to partner with our clients to accelerate time-to-market, avoid that expensive license cost, and modernizing infrastructure using things like containers, Kubernetes and the cloud.

R: Nice. So you've been doing this for quite a while. Is that correct?

J: I have. My career is kind of focused, over the last -- unfortunately I'm telling my age -- but 25 years. You know, I grew up in the app-dev space originally and throughout my career I saw an important focus and need to really recognize the business needs before the technology to make sure that the technology solutions are really meeting the business goals and objectives of the organization.

R: You had talked about your original step into this is, this first introduction -- to say data driven projects -- was in the app Dev world. So, you were an application developer when you first started out? Or do you want to expand on that a little bit?

J: Sure, yeah, so I basically grew up first in web and web applications and then client server applications and then ultimately our cloud and cloud native applications. So my focus on data specifically was originally just specific to the applications that I was developing. Back in those days we didn't really focus more broadly to enterprise data and then subsequently monetizing data was not a focus so again, as maturity around technology and really I think as organizations and industries understood their data more, the focus was on how can they really leverage their data as an asset and subsequently monetize that data for both insights and gain within the business.

R: And that was probably invaluable for you and you're going on towards today, where you're getting more towards the business end of things having that developer background probably has assisted you in many ways.

J: Sure it helps me really bridge the gap between technology and again the business. And, reconciling not that the value that is required in a customer that's involved whether it's an organization in b2b, a single customer, it really helps to focus the technology on that value.

R: Perfect! I'm going to camp out on that just a little bit because that's where I’d like to discuss as well. Businesses that have a solution that just is not working with them with the data that they have. A lot of times we see this as the inherited an older piece of software that they've just ran with for a long piece of a long chunk of time or it could be that they're just using the wrong software in the wrong kind of situation, or they were advised poorly by someone who just did not they're doing, but eventually they will have a need to go to a cloud-based service. So instead of having, let's say they're the web applications in their website hosted on a service like GoDaddy or Namecheap or Liquid Web or something like that, where it is set it forget it more or less, they need to graduate to the service. Let's say Google Cloud or Amazon. In your opinion, I'm sure you've seen this before too, they're kind of stuck and they need to move forward into this better set up. What makes it a better setup? What makes Google Cloud or services similar to that a better service in general -- let’s say compared to those standard hosting platforms?

J: Right right. So I think it's a combination of the infrastructure and honestly the application architecture that organizations have traditionally built their applications on and in kind of where best practices is going on today. Specifically what that means is instead of again spinning hardware and the time that it takes to procure and in rack and network and equip the organization with folks to handle that structure. You can leverage both cloud and technology such as Kubernetes to make that a lot more economical and a lot more efficient. Again, going towards portability flexibility and productivity as an organization

R: Okay, and there's some people that are listening to us thinking “Kubernetes!”, but I've never heard of that word before -- the word is kubernetes. Can you explain a little bit more about Kubernetes in and what it can be used for?

J: Sure. So Kubernetes grew out of a project that was donated by Google and it first kind of went mainstream within what they call the Cloud Foundation which is a CNCF if you’ve seen that. And so from there it kind of, again it's open source, it kind of matured and grew into what it is today. The value of Kubernetes again going back to some of the things that were challenges before, it enables portability flexibility and what that means is Kubernetes can run on any container -- run time, it can run within on-prem, it can run within the public cloud, a hybrid solution, on and on. Going back to actually what Kubernetes is, it's basically on a run time, a container run time, that basically enables auto-scaling of infrastructure, virtual infrastructure if you will, to meet the demands of the applications. Subsequently it also is able to deploy across multi-cloud whether it is AWS, Google, Microsoft, and then it really lends itself to increase deployments too. So, organizing deployment into a repeatable in organized process again for expediency of deployments in efficiencies of resources as well.

R: That’s a great explanation of it. Some practical examples of what you were talking about with Kubernetes is that it can be used to let’s say scale up, for example. If you’re a company that has a website or web application that can get a sudden burst of traffic, let’s say you have an Ecommerce website, and then Black Friday and Cyber Monday is around the corner and you’re thinking “Oh my goodness, I need this thing to scale”, and that’s where Kubernetes can come in handy. It can just automatically scale for you and take up more resources are needed so you're not caught in the busiest time of the year, that your site is going down, that Kubernetes saved your rear end on that. That's one example. How have you seen Kubernetes practically used on, let's say, a business-to-business setting?

J: Yeah I mean business to businesses setting, one other aspect of Kubernetes is it allows you to segment, say the businesses that you're serving. What I mean by that is instead of having a what we call a single tendency application where all your clients get the same experience the same as a structure the same environment and allows you to segment those environments such as to where each customer specifically has essentially their own environment and it can scale accordingly as segmenting their data, segmenting their application logic from save some of your other customers that you're serving from a B2B perspective.

R: Very nice! I've seen it on your website that you work with Kubernetes. This is something that you advertise, that you are Kubernetes specialists.You guys have worked with it for many years, correct?

J: Absolutely! Yeah and inside another bit of information specifically about how Shadow-Soft is our open source roots and we partnered with Red Hat very early on and subsequently other companies and open source projects to really leverage the value of Open Source and how it integrates into other applications within the organization.

R: And you talked about open source and basically having data that can integrate within other applications. That is a good segue here to the next topic I want to discuss and it's just data in general. You’ve been in business for a long time. You have seen a lot of things in your day and you have seen, I'm sure, businesses either misuse or not taking full advantage of the data that they've had at hand. So, what ways have you seen a business misuse or maybe maybe not take full advantage of the data that they've had?

J: Sure. So, I worked with a large company in the last few years that was trying to aggregate their application logs, their metrics, networking information and then they were doing it siloed right? And each group within the organization was trying to do it their own way. What resulted was inefficiencies and not being able to really harness the collective value of pulling that data together to respond to say scaling problems or network outages, that type of thing. So that was kind not a misuse but kind of not optimizing know or taking advantage of collectively centralizing their data. The good news is once they did they were really able to get a overall view of their organizations where they can manage each of the pieces of data in really bring those together to paint a picture that maybe they couldn't see individually.

R: They basically had a view of “Section A has these errors” “Section B has these errors”. But in general they just had no idea because the left hand wasn't talking to the right hand?

J: Right, right. In really the action was more from a historical perspective and in once they started aggregating their data and getting more near to real time they began to have predictive capabilities they’d not only respond to their data but they're forecasting and and predicting based on their data.

R: That I guess that's a feature that I've seen, and I know I'm sticking primarily with Google Cloud here, but Google Cloud has some services with artificial intelligence, machine learning and have you been able to integrate any of those services into an application before?

J: Sure. Actually yes so that there's tools within each of the cloud platforms that do this. But, essentially what that allows you to do is leverage again the power of the cloud. Going back to the power of cloud vs on-prem, it allows you to leverage some of these Ai and ML capabilities that you don't necessarily have within your data center or within your on-prem infrastructure and solutions. And so, saying all is to say, we can couple both on-prem solutions and data with the power of cloud data services that really focus on this emerging and cutting edge solutions and capabilities to do things that companies couldn't do so 10 years ago or was maybe even unthinkable.

R: Interesting. And so an example of that, if you're interested in in maybe machine learning, and I'm trying to tie it together with the example that you had before, is it possible to have your machine learn when there are going to be traffic spikes and more less predict when we might need resources before it even happened? So let's say 4 Sundays in a row at 6 p.m. you get a decent spike. On that fifth Sunday is it going to be able to learn that maybe we can adjust our infrastructure for that or is it set up a different way than that?

J: I think you're exactly right. I mean there's different ways to do it but the net of it is that you can use models and algorithms to predict based on the data that is being ingested. Then going back to Kubernetes and cloud, even cloud-native infrastructure, you can basically scale your applications and your infrastructure based on timing. Say you have more demand in the morning or in the afternoon you can you can have scaled infrastructure at different times or responding to a perceived trend that it’s learning within the machine learning component.

R: It would have noticed too, if you're using Amazon or Google or any of those bigger services for these more enterprise level cloud setups, that they have these extra software chunks that you can have weave in your application. Like we've mentioned before there's machine learning. There's a whole bunch of different features you can weave into what you have there. So what's one often unused feature that you've seen in one of these called platforms?

J: Interesting question. I mean so there are some interesting services that are emerging like text recognition and text-to-speech things like that. That maybe not necessarily or not being leveraged they're just emerging so people are trying to figure out, organizations are trying to figure out, how to leverage them. And then also just to going back to core data, the data platforms like Athena and things like that right?

R: I've never told you this story before. An application that we've built in the Google Cloud infrastructure, and you'd mention text to speech, we had a situation where there was an auctioneer. And the way he operated was he had an earpiece in. Before any of the work that we did he had a physical person standing next to him on a cell phone talking to a website operator. That way he could do in-person auctions and then if something happened online the online operator talked to the person next to him on the phone, which relayed the message to the in-person auctioneer. What we were able to do is take the web application that ran the auction software and do the text-to-speech. And so the microsecond that somebody bid on something it went straight to the ear of the auctioneer and there was no lapse in time. That was a pain point - was the relay going back and forth sometimes auctions will close before people can bid and there's a lapse in time. So, using an earpiece and it spoke “the new high bid is $1” and right away he could announce it to the crowd there. It was literally the crowd and people online within microseconds reacting with each other which is pretty neat so that's a fun story that we've had to do with it text to speech before.

J: Yeah that's great! That's great! And then just coupling on that when you get some of those capabilities of speech translation, leveraging as some of these other services, they go beyond say English and other languages.

R: I bet you there's some larger institutions, whether they're medical or academic, or anything like that that might have tons of PDFs and word docs and things like that, that just sit in a folder. You had also mentioned that text recognition -- that there is software that can just dive through the folder and actually allow you to search within these obscure file types in there and use that for searchable data. Is that true?

J: Absolutely. And they do it for a couple reasons right? So I could be validating the information that you submit. It could be today like in the tax industry, scanning tax forms to extract the information and then subsequently feed it into another system for processing. It could be applied to medical information as well really though the possibilities are endless I think in that regard.

R: And you mentioned some success stories. Do you have any other good success stories of when a business was “in the Dark Ages” and then kind of moved in to this Enterprise Cloud platform and what good it brought them?

J: Yeah absolutely, so I'll go back to just over the last, in my career 20-25 years, that the trend was creating applications and then adding functionality on top of functionality on top of functionality in so fast forward say 20 years and that kind of paint you into a corner where your applications are hard to scale it's hard to add functionality, it’s hard to remove functionality and quite frankly it's it's hard to leverage new technologies that weren't more available when those applications were birthed. So what I've seen a lot of my customers really are trying to evolve from that model, and that paradigm, into more on demand infrastructure microservices where it’s very targeted functionality that you can execute on demand and then connect those services together to make larger applications. And so that the evolution of that looks like basically going from that monolithic application and as you go into the cloud to leverage the cloud infrastructure and the efficiencies of the cloud that they're taking the time to really decouple those monolithic applications to where they can modernize and scale faster to respond again to ultimately the business goals and objectives.

R: Nine times out of 10 you scale faster you make more profit!

J: It's not just your time-to-market, it's time to resolution. So going back to go CICD and integrated testing, and those types of tools within the cloud, and to be able to respond to outages and resolutions more quickly.

R: That also affects the bottom line too, because if you don’t address things right away, well that's every minute that you're down for some company that is lots of money. I think we are going to transition into the fun part of a podcast and this is what I call the lightning round. So I'm going to surprise you with a few questions here and there just a handful of questions getting to know you that you, John Dingler a little bit better. So are you ready for some lightning round questions?

J: Let’s do it

R: Alright the first one’s a very easy one -- what is your favorite food?

J: My favorite food, besides anything in front of me, I'd have to say Mexican food.

R: Are you saying tacos, enchiladas, is there any specific kind of Mexican food?

J: Quesadilla -- obviously the chips are pretty addictive I guess.

R: My last food question is are you a guac or a no guac person?

J: Definitely guac.

R: Okay cool. Next question on the lightning round if you could get anything for Christmas what would it be?

J: What would it be? World peace! Now just kidding. Maybe a big yacht to sail the seas on. That would be nice.

R: Next question in the lightning round? Mac or PC, Google or Apple?

J: For those that know me there is definitely no question I am a Mac person for sure. When it's off to Apple versus Google but I see obvious capabilities in Google as well and I actually use both of them which is an interesting pattern I guess.

R: How do you use them both in tandem?

J: I like the connectivity of all my devices on Apple but I tend to use my emails and in some of the platforms of Google as well.

R: Next question in the lightning round, do you have a favorite movie or TV series?

J: I would have to say maybe all-time I grew up in the Seinfeld and Friends era and then I understand that Game of Thrones for instance is a great series. Unfortunately I haven't seen it which might be a shocker to folks but it's definitely on my list.

R: What does your future hold?

J: That's a great question if I had the answer to that… but what does my future hold... I have several kids and a growing family and I obviously want to focus on that but aside from that business-wise I'm really intrigued by where technology is going it kind of reminds me of a little bit of era and watching companies evolve and mature from what we were talking about right - these legacy applications and static infrastructure if you will. I'm really interested in growing and in seeing that grow in our business.

R: Speaking of your business you’re a representative of Shadow Soft. How do people get in touch with Shadow Soft?

J: So we have a website, it's We have several folks that you can get in touch with. They can contact us through our website or they can contact me directly as well.

R: Perfect, alright, well John I appreciate your time as a great podcast is great talking to you and enjoy the rest of your day thank you very much!

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