Although we use Intel’s NUC as a shorthand for the type of hardware deployed at the far edge, this recently-cancelled platform isn’t all there is. This episode of Utilizing Edge looks beyond the NUC, to platforms from Lenovo, Nvidia, and more, with Julian Chesterfield of Sunlight, Andrew Green, and Stephen Foskett. ARM-based solutions, many using the Nvidia Jetson platform, are particularly interesting given their low cost and power consumption and strong GPUs for edge AI. A hyperconverged stack runs all of the components required for high availability, including storage and networking, in software spanning all of the nodes in a cluster, and this is commonly deployed on low-cost devices at the far edge. The trend to deploying applications at the edge is driven both by new hardware and software capabilities and the changing expectation of consumers and businesses.
Hosts and Guest:
Stephen Foskett: Welcome to Utilizing Tech, the podcast about emerging technology from Gestalt IT. This season of Utilizing Tech focuses on Edge Computing which demands a new approach to compute, storage, networking, and more. I’m your host, Stephen Foskett, organizer of Tech Field Day and publisher of Gestalt IT. Joining me today as my co-host is Andrew Green, a veteran of our Edge Field Day and somebody I’m sure you’ve seen on the internet. Andrew thanks for joining me.
Andrew Green: Thanks for having me Stephen. It was great talking to you last time about near edge and far edge.
Stephen: indeed and that’s sort of where we’re going here today. First though, there’s been some breaking news in the industry as we’ve talked about for, well certainly at Edge Field Day and now on Utilizing Edge, the Intel NUC has been one of the, sort of poster boy of hardware that’s been used for edge deployment, especially at the far edge and Intel just announced this week that they are no longer, they’re going to be moving away from that business. They’re going to be no longer investing in it. I imagine that there is going to be some transition there but basically we’re at the end of the Intel NUC. What’s your response to that, Andrew?
Andrew: I’m curious what they’re going to replace it with to be honest.
Stephen: Yeah well it and I don’t know if they’re going to replace it with anything. I think they’re hoping that their ISV partners will step in and have their own alternative compact form factor PCs. So one of the companies that I’ve spoken with recently that knows quite a lot about this space and is very aware that the world is not just Intel NUCs, the world is a lot of other PC platforms and alternative low-powered platforms is Sunlight.IO and we’re joined today by Julian Chesterfield from Sunlight. Welcome to the show.
Julian Chesterfield: Thank you Stephen, thank you Andrew, very nice to be here.
Stephen so I know that, although as I said, a lot of the industry is really focused on the NUC and that sort of becomes shorthand, that’s not really the as dominant a platform as it seems right? I mean there are people using a lot of other devices at the far Edge, right?
Julian: For sure yeah and I think you know we’ve seen at the far edge you know there’s a plethora of, you know, different kinds of devices that are more purpose-designed for different solutions, you know, in particular I would highlight you know devices like the NVIDIA Jetson platform which comes in a you know variety of different form factors that has you know embedded GPU acceleration built into it that’s you know ideally designed for computer vision processing and you know AI workload processing at the edge. I think the yeah the the edge hardware space is certainly very, you know, more diverse and interesting I think than what we’ve become used to in the you know the core data center around sort of conventional server platforms and so on.
Stephen: Yeah there’s a bunch of alternative small form factor computers I mean certainly within the Intel space. There’s Lenovo, who have a great a range of these things, there’s also some, well there’s similar devices from Dell and HPE, but those are more desktop oriented, at least as far as I know. And of course then they have their own edge lines that are somewhat different in design from those small form factor PCs and then of course as you mentioned there’s the whole Arm ecosystem that I think we really haven’t talked about much. Are you seeing Arm at the edge?
Julian: Yes for sure and you know we work with a variety of different hardware platforms but particularly you know Lenovo is a great partner of ours with their you know Think Edge portfolio and I think that’s quite indicative actually, you know. Lenovo have a spectrum of devices you know everything from you know small embedded Intel processors so they’re SE10 range which starts with a you know an embedded atom processor on it through to the SE70 which is based on the NVIDIA Jetson platform. So Jetson you know for those who are not familiar with it is based on… it’s a system on chip device that has a you know embedded Arm processor in you know built into the platform alongside the GPU acceleration hardware as well. And I think you know from our perspective and you know we’ve worked closely with the Arm architecture for number of years, I think it’s going to be an interesting space. You know Arm has a a very strong value proposition for these types of edge workloads where really the focus is around you know AI data aggregation and fast data processing. You know a lot of these edge applications that are driving this adoption of technology at the edge are applications that have to be able to do a lot of processing quickly and make fast decisions you know where you know latency is an issue you’ve got local control operations that need to be need to be executed autonomously at the edge and so I think um you know this is going to be a strong space for Arm particularly around the you know the power consumption. So the power footprint you know we see that you know often the requirement to deploy power efficient servers and you know lightweight platforms at the edge is one of the key driving decisions in selecting hardware for applications. So Arm lends itself very well to to that architecture but also the cost points as well. I think you know when you’re deploying infrastructure across thousands of sites in a very distributed manner, cost becomes a really significant factor in doing that.
Andrew: I think one of the factors where organizations are looking to control of those is in the types of devices that they’re looking to deploy at the edge. Those can range from like very very lightweight low power low data transmission sensors for IoT to fairly intensive you know computational power for AI and machine learning technology. But how do you exactly scale those resources so you can have a platform like them not only deal with those low power low data transmission once the one that actually do quite a few quite intensive computation?
Julian: Yeah I mean you know our approach is and I think the the thing that that differentiates us over other solutions that are out there is that you know we’re a full virtualization platform so we describe our technology as a true hyper-converged edge stack which means that we can run on you know very small lightweight hardware platforms. You know we can scale down onto you know very small sort of mobile device processor platforms all the way up to to larger data center infrastructure as well. I think the you know some of the requirements that we see that drive adoption of Sunlight like technology at the edge is this requirement really and and I think this challenge really grows as your infrastructure at the edge scales out and you have a lot more locations where you’re managing infrastructure. It’s really around you know building a cloud-like platform to be able to to manage infrastructure so being able to deploy applications on demand without having to send people physically to a site in order to install or to manage the infrastructure. So you kind of need to have this separation between the infrastructure management framework that runs on the hardware device and the applications that you deploy on top of that. The environments that we work with don’t necessarily have to have a lot of applications running on them. They might be single purpose devices that that run a particular application but having that ability to manage and control that application out of band from the hardware platform itself is really key. So you know in the the Sunlight stack for example we create because we’re a hyper-converged stack, we can provide redundancy and resiliency across multiple physical nodes which again becomes one of the key requirements for very large scale distributed edge.
Stephen: That’s one of the interesting things I think about a hyper-converged solution at the edge is that as you say it’s a highly available system. It has a lot of redundancy built in, but the redundancy is in software not so much in hardware and what that means is that you don’t have to invest so much in high availability redundant hardware. You can basically replicate those features in software. And so we’ve I think sort of got this idea that there’s sort of this ideal cluster of maybe three low-cost nodes running hyper-converge solution and that if a node goes out you can replace them. Is that what you’re talking about here is the idea that you would have maybe a three node cluster that is redundant and remotely managed?
Julian: Yeah exactly. I mean we can do it with two nodes um which is you know kind of an advantage as well but yeah it’s it’s exactly that. So you know we’ve seen hyper-converged infrastructure in the data center we’ve seen and that’s really where the the concept of hyper-converged evolved you know folks like Nutanix and VMware that designed you know, the software-defined data center uh to be able to leverage uh you know storage replication, you know software-defined networking in the data center all in software rather than having to have dedicated hardware appliances for storing data and replicating data and so on. So those concepts really evolved in the data center but actually we see massive applicability at the edge and I think even more so at the edge because you have the even greater challenge of in a data center you often have you know smart hands actually on-site in the data center where you’ve got technicians who can go in and help if you’ve got to pull out disk drives and you know power cycle a device or diagnose something in the data center you have that available, you know you have those sorts of resources available. At the true edge that really doesn’t exist. You know you’re talking about remote you know like in in the energy sector remote oil fields or you know on a bus or in a restaurant or something where it costs a lot of money to actually send people out to these sites so having the ability to use commodity hardware to some extent so you know lower cost infrastructure that you can you can drop in nodes that that look quite similar but be able to to build out the redundancy and that resiliency in the software stack itself um is is a really key aspect.
Andrew: So what kind of industries and use cases stand out for those edge deployments today?
Julian: Yeah that’s it’s a good question I mean I think there are obviously some industries that are a bit further down the road with adopting technology and you know actually bringing in technology and automation into edge environments. The industries that we’re focusing on mainly at the moment or we’re seeing the most demand from I would say are in the sort of in the hospitality sector so in sort of retail, you know, supermarkets, quick service restaurants, where you know there’s this requirement to you know margins are really tight. They’ve really got to try and optimize the cost of running those sorts of businesses. So being able to leverage smart technology if that’s in a restaurant for example bringing in kitchen automation, number plate recognition, you know customer tracking and and you know and things like that that in in the restaurant where where they can actually bring a you know higher quality of service to people but at a lower cost ultimately. You know we’re working with use cases in the supermarket sectors, quite an interesting use case where we’re developing at the moment with a customer which involves you know monitoring refrigeration units in supermarkets where you know a lot of these devices are quite smart now and the ability to be able to actually monitor and track when devices are not running efficiently or when they’re failing and they need you know an engineer to come out and inspect them and so you know being able to bring in technology like that can make smart decisions across you know a large number of IoT devices that are in that location. The other areas I think that we’re you know we see a lot of interesting growth is in the energy sector so whether that’s you know traditional oil and gas environments where you know the production and extraction of oil is you know leveraging technology to drive more autonomous decisions and to be smarter about that that process of doing that but also increasingly more in the sort of renewable energy sector, so things like solar power and you know wind farms where you know in the solar power sector where you’ve got you know lots of solar panels and you know the the ability to have smart controls to be able to you know some of these solar panels can adjust now to sort of follow the Sun and so on and you know being able to to have localized monitoring and alert detection you know triggering alerts if there’s problems in those environments. We’re seeing a lot more adoption of technology of course you know many of these locations are in you know quite extreme environments. They need to operate at very extreme temperatures or they may be out in you know areas that are not as accessible. So the assumption that that everything has you know high network connectivity, very reliable network connectivity is often not the case for these types of use cases. So I think having that that localized compute logic that can execute on site is very important. And then the other one I would highlight I think which is you know another area where we’re seeing a lot of technology adoption for edge use cases is in the industrial sector, so Factory Automation in particular being able to enhance quality control, being able to use things like computer vision apps to monitor safety in industrial locations, so making sure people are wearing the right clothing, they’ve got hard hats on, making sure they’re not walking in the wrong places. If you have you know delivery trucks coming into locations, making sure that they’re unloading safely and loading safely and so on. You know I think there are a lot of use cases for smart technology in those environments. And again that compute logic I think needs to be able to run local to where the actual data is being generated in those environments.
Stephen: Do you think that the driver for this is more driven by the new the technology Trends? You talk about IoT and machine learning and vision processing, solarpower, CNC Machining and all these kinds of things. Do you think that that’s driving these applications to the edge or do you think it’s the other way around? Is it consumer expectations and industrial expectations? Basically we live in a connected world, everybody’s got devices around them all the time. Is that what’s driving applications to the edge?
Julian: I think it’s probably the more so the former because I think the devices are getting more capable. I think there’s you know there’s more um standardization around these devices so it’s possible to you know to rather than having these closed source systems that have been very much dominated by you know particular companies that build control systems for these types of sensors and so on. I think what we’re seeing now is you know it’s more of an open space where you know smart solution companies can build software applications that are able to to access and store data from these devices and make smart decisions about them. So obviously there’s a demand from the consumer side to have you know better safety in these environments or better efficiency to be able to drive more output from an industrial environment but you know certainly I think the hardware capability is probably the thing that’s changed most significantly there.
Andrew: It seems like all of those use cases that are, that you’ve described earlier are about industries that have a physical presence like non-digital services for example like your IoT and your like you mentioned refrigeration monitoring computer vision for worker safety. It seems like it’s really bringing it and edge into the real world because a lot of other solutions that at least I’ve looked at for example like CDN based edges, they only talk about digital services. So how can I make my website faster or how can I you know enable remote working but it’s only a few solutions that can actually deliver those capabilities in the real world let’s say. How can I deploy this rugged computer compute hardware into an environment where it is withstand you know for example temperatures of 60 degrees or so?
Julian: Yeah I think for sure I mean it’s you know it’s interesting that you know the… I think it is these more sort of traditional industries almost that are you know starting to or finding themselves having to modernize in order to stay competitive and you know to really leverage technology to assist with that. It’s you know certainly our experience and and you know obviously we focus on you know I mean there are particular areas where our technology has most applicability but I think you know we’re finding that it is the more the sort of traditional industries that are looking to modernize um that are the ones that are actually going to be the earlier adopters of edge technology. I think you know obviously there you know other areas you know we haven’t talked about smart vehicles and things like that. You know we have some exposure in those sorts of areas. But I would say that you know in general a lot of the awesome, the smart automation, that’s going into you know things like self-driving cars and so on is highly regulated and it’s you know quite controlled in terms of you know the types of technologies that are allowed to be deployed in vehicles from a safety point of view and so on. So it tends to be you know and I think we see that a lot of the technology in that industry is evolving in a particular direction where you know or many manufacturers are adopting similar approaches to the way they do things. Yeah that’s certainly been our experience.
Stephen: Well that’s an interesting point you bring up Julian because one of the factors at play here as well is non-traditional platforms for edge compute so I think a lot of us have, again back to the my opening statement about the you know the sort of stereotype of you know I’ve got three Intel NUCs in my quick serve restaurant, I think that a lot of this stuff is not being deployed on a platform at all like that. I know that some of this is being deployed in embedded devices in routers, in industrial settings, you know we might find hyper-converged infrastructure and multiple hyper-converged nodes being deployed in things that don’t look like computers at all. And then you bring up self-driving cars and of course there’s an entire world of sort of Last Mile Edge that on the consumer side that we’ve heard some whisperings about as well deploying things even as far as consumer premises. What do you think of these non-traditional locations for edge platforms?
Julian: So yeah I mean every environment is somewhat different. I think you know, if you take the restaurant use case you know the Intel NUC is a good example. It’s not a particularly ruggedized platform, it’s something that you can put in a corner, you can stack it up, but it’s not something that can operate at very extreme temperatures or it could be you know can tolerate a lot of ruggedized movement and so on. It’s not really designed for that sort of use case obviously you know ruggedization comes at a cost. So you know I think you know we use this term a lot, you know the edge appropriate hardware and I think edge appropriate really varies depending on the type of use case. There is in general though I think a desire in the industry to be able to move towards more general purpose platform, so being able to deploy onto a more general purpose x86 based architecture or an Arm-based architecture where you know if you’re a solution provider having a choice of hardware platforms is smart because it you know de-risks you know to a large extent and also you know can reduce the cost. If you’ve got you know if you’ve got hardware platforms that are capable of servicing many different types of applications and many different industries then it means that you know I think every everyone can benefit from that sort of efficiency of cost in terms of the manufacturing process and the you know the cost of the devices themselves. I think you know cost is a really significant factor we see in a lot of these these edge environments very much more so than it had been traditionally for enterprises in the data center. I think as we move more out towards the edge and it becomes much more of an operational part of the business where you know every you know if you take the restaurant use case, you know, the restaurants operate on very tight margins and you know of course if you have a large technology cost to actually deploy technology in those restaurants, then that eats into the margin of each of those individual locations. So you know being able to find cost-effective solutions which you know I think comes down to this desire to be able to deploy on more you know general purpose type infrastructure.
Andrew: I want to switch up the gearing a little bit and ask you about the security aspect. What exactly do we need to be concerned about with security here? Is it the runtime security? Is it activity or what should we look at exactly?
Julian: Yeah good question. I think there are a variety of factors. So you know when you’re putting infrastructure out at the edge, you know you have to start thinking about physical security on the devices so you know being sure that a device hasn’t been tampered with, being sure that you know somebody hasn’t been able to you know modify the operating environment for the device. So trusted boot things like that are important but also at runtime itself, you know, having a very tight control over you know because now you have a very distributed attack surface from a security point of view. You need to think about you know being able to secure the access to the services that are running at that local point but also so being able to trust the integrity of the data that’s coming in from your sensor, IoT devices, or whatever that data source might be. You know, I mean our approach to the security of the environment itself is you know of course we’re a software-based platform so you know we work with software solutions that can plug in to our environments. We actually made an announcement not too long ago that we’re partnering with a company called EdgeLabs who have a sort of distributed edge security perimeter type solution which is you know a very interesting very interesting use case for sure and it allows you to across a distributed footprint to be able to look for different types of attacks that might be in to be able to alert for different types of attacks that might be occurring in any of those sort of age locations but equally to be able to respond to that and to be able to lock down attacks that you know whether it’s distributed denial of service or some sort of intrusion detection, being able to lock that down across a distributed foot print. You know if you think about it from an operational point of view as you scale up to thousands or many thousands of sites. It becomes really hard to be able to do that traditional sort of security maintenance in a relatively manual way. You know you need to rely on the tools and the technology to assist you with that. So yeah so I think you know security is certainly is a challenge and the more distributed you become, the more you have to think about you know how you want to you know what are the potential vulnerabilities that you have that you’re exposing as part of that. And you know how do you secure against that? One of the design aspects of our technology is that you know we create a a very small footprint. So Sunlight is designed to execute with a really tiny footprint you know very limited, just a few hundred megabytes of memory, very limited resources itself, but that also extends to the exposure of services. So you know we limit the number of services that are actually run and that are actually exposed to the outside. So every edge environment can create a secure tunnel back into the centralized management framework and really it’s a trusted relationship between the edge environment and the centralized manager. So we try to really minimize any services that are exposed locally just to the applications themselves to whatever services they need to expose.
Andrew: Yeah I think you hit the nail on the head there. You have a very wide attack surface area with this. So I think your job is on somebody who manages to major deployment is to minimize it as much as you can and as you mentioned, if you need to have non-technical people installing or you know working nearby those devices at the edge, you need to make sure that they’ve not been tampered with, they have secured and I think everything like that. And on the other hand, you need to have your role-based access controls isolation and segmentation nutrition prevention detection systems. So your job here is really as with any other environment to minimize the tax service area and mitigate any vulnerabilities?
Julian: Yeah yeah for sure. I mean yeah role-based access control is another interesting aspect you know in many of the use cases we’ve talked about you know these organizations have different operational teams that might be divided by regions. So for example you might have a a North American team that manages infrastructure in a particular area, you might have a European team or you know different areas globally where you’ve got folks who are responsible for managing that infrastructure or to responding to issues that might occur in that infrastructure. So being able to have role-based access control across the system that allows you to isolate access to specific areas of resource is another requirement. Let’s say for a lot of these types of use cases.
Stephen: And I would bring up the aspect of this out of box experience as well because as you brought up you know you don’t have a lot of people there you need to be able to as you know you’ve said to me personally previously regarding your solution you need to be able to take it out of the box plug in the cable and it just goes.
Julian: Exactly yeah it’s the the plug and play you know edge has to be really simple and actually that’s one of our taglines is you know edge simplicity the more distributed you get the more complexity that can potentially add. So you know you need to make it as simple as, you know, we refer to the, sort of the home broadband modem model where you know we’ve all become used now to you know receiving when you sign up. When you subscribe to a broadband service, a device arrives in the mail, you unbox it, you plug in to your you know phone line or whatever the you know the connection may be and you apply power to it everything else just boots up and it kind of manages itself or at least you’ve got some centralized dashboard where you can go in and switch on services and do things like that. That’s really you know in our view that’s how the edge needs to be and you know the types of use cases we’re talking about where it’s got to be as simple as it ships out from the factory pre-installed and pre-configured ready to stand up. Now there are of course some exceptions to that. You know we also work in industry environments where you know perhaps for security reasons it might need to run in an isolated environment or it might need to be it may be in a location where actually there is no network connectivity, so it has to run completely autonomously. But you know a large part of the challenge to delivering edge services even in those environments is the ability to to pre-set up the environment and then to be able to drop it in so that it can execute. So really yeah that’s that’s been a core aspect of our architectural design for solving these challenges at the edge.
Stephen: So I guess to summarize again although we often talk about this sort of ideal of yeah we’re using some mini PCs that are a quick serve restaurant the edge is a very different space than that and a hyper-converged low powered low demand solution is a good one and it’s one that we’re seeing a lot more of. How would you summarize the state of the edge, especially the far edge client world right now and where do you think it’s going?
Julian: yeah I think it’s a very exciting space and you know of course we’re hearing a lot of buzz about it in general in the you know general sort of analyst space. I think you know edge technology is starting to be more widely adopted and we’re seeing a huge you know plethora of different applications and solutions that are coming along. I think that it’s going to take time to evolve. It takes you know large enterprises you know these are you know traditional enterprise verticals that you know takes them time to really try out and adopt this sort of technology, And actually one of the things that we see today is some of the initial requirements for deploying edge are that you can run both these legacy applications that you know I mean, let’s face it, edge technology has been around for a long time it’s not not something that’s suddenly appeared overnight so there are a lot of legacy applications that run perhaps on some older sort of legacy windows environments that have been on dedicated hardware running in these locations you know one of the requirements that we see is the ability to be able to support both the legacy apps running in a you know multi-tenant sort of virtualized way but equally being able to bring in these newer sort of containerized architectures that are you know based around you know platform solutions like Kubernetes and Docker and so on that you know we can we can drop onto Sunlight in parallel to the legacy stuff that has to run. And I think that will be you know certainly the first adoption of edge for many of these environments is is that sort of getting over that initial hurdle but then being able to really leverage the power of the edge and you know having a a more general purpose like a distributed cloud type environment allows them then to innovate and bring in new solutions and you know start leveraging more technology as and when they can.
Andrew: so there was a big chasm besides running workloads on premises when you needed it and those newer types of edge technologies and I think it took us about twenty years to get across them but right now I think your solutions and similar solutions are those that actually enable those through edge use cases and the key here is not only can I run something locally but can I run something locally and manage it from a central location and have those distributed across wherever my my geographical presence is and I think that’s the key part that’s enabling those edge solutions and is bringing technology into the real world. We’re not just obstructed like behind a computer we can actually you know go out and interact with it we can we can be monitored we can be safer and we can be faster.
Julian: yeah absolutely I mean the the reality is that um you know and and I’m sure you guys have heard various statistics around this but the reality is that increasingly more and more data, enterprise data, is going to be generated outside of the core data center. So you know you have this challenge around you know where do you where do you put the compute processing capability to actually manage and process that data and the answer is invariably it’s going to be it varies, right. There will be a hybrid solution where you know there are use cases where you want to be able to aggregate and process large amounts of data efficiently in a core cloud environment but you know I think having the ability to process data on demand at the edge and react to that data is very important. So you know it’s not a straightforward division between you know this is what runs at the edge, this is what runs in the core datacenter. I think it’s very much a hybrid environment. And so you know sunlight certainly can help Enterprises bridge that uh chasm as you say between you know being able to choose what is the right location actually to to run and execute the the processing of that data and you know our view is that you know you’ve got a centralized control component that gives you a single pane of glass but you know ultimately you have to be able to manage the applications and the workloads and be able to deploy them in the appropriate place.
Stephen: Yeah and I would say too in my opinion I think that the classic sort of data center concept of here are our servers and we’re running our things on our servers is increasingly going to get blown up by the edge by the proliferation of different types of devices by the requirements of deploying there and I think increasingly we’re going to see aa very different infrastructure there and technology like this like you’re describing especially bringing in lower powered alternative platforms ruggedized platforms other devices I think is really going to kind of lead the way toward that. Well thank you so much for joining us today this has been a really fascinating discussion Julian. I appreciate your thoughts on on the changing client footprint at the edge. Where can people connect with you and continue this conversation with you?
Julian: Yeah so thank you very much for inviting me. It’s been great to join I mean if anyone wants to to learn more about Sunlight and our solutions and you know the best place to go to is our website so sunlight.io and you know we have a lot of information there and information on how to connect with us and to reach out. You can also subscribe to our newsletter and we can keep you up to date on you know new technology that’s coming and um uh customer uh use cases uh as as we as we deploy them in you know lots of new and interesting locations. And there’s also a blog coming up and we encourage everyone to you know take a look at that and read some of the different viewpoints around you know deployment of edge and some of the challenges around deploying edge technology.
Stephen: How about you Andrew? what are you doing these days?
Amdrew: So I’m neck deep in security at the moment which is always fun. If you want to get in touch with it you can do at andrew.green at precision.com or you can drop me an email at AndrewGreen at GigaOM.com if you have a edge like solution that you’d like to be featured in one of our reports.
Stephen: Excellent thank you so much. And as for me, you’ll find me here at Utilizing Tech every Monday on the On-Premise IT Podcast most Tuesdays and of course on the Gestalt IT News Rundown on Wednesdays. Thank you for listening to Utilizing Edge, part of the Utilizing Tech podcast series. If you enjoyed this discussion please do give us a subscription, you’ll find us in all your favorite podcast applications and you’ll also find us on YouTube. This podcast was brought to you by GestaltIT.com your home for it coverage from across the Enterprise. For show notes and more episodes head over to our dedicated website UtilizingTech.com or find us on Twitter and Mastodon at Utilizing Tech. Thanks for listening and we will see you next week.