Adam Worthington, Ethos Technology | IoTahoe | Data Automated
From. Around the globe, it's the cube with. Digital, coverage, of data automated. And event series brought, to you by IO Tahoe. Ok, we're back with Adam Worthington, who is the CTO and co-founder of. Each dose Adam good, to see you how are things across the pond. Thank, you I'm sure whether it's a little bit worse than yours is over the other side for traffic. Hey, so let's let's, send it up tell us about yourself. What your role is as, CTO, and and give us the lowdown on ethos. Sure, so yet, Adam Erikson as you said CTO and co-founder of. Ethos. That we're pretty. Young company ourselves that we're in our sixth, year and and. We, specialize. In, emerging. Disruptive, technologies, but within the infrastructure. Data Spencer kind of cloud space and, my. Role is the technical, lead so I kind. Of my job to be an expert, in order, for technologies, that we work with which, can be a bit of a challenge if you have a huge for phobias one, of the reasons we've got a deliberately focused one and, and. Also, kind. Of piece of the petrel validation, and evaluation. Of new technologies. And new, vendors. So, you guys are really. Technology. Experts data experts, are probably, also expert, in process. And delivering customer, outcomes. Right. That's. A great, word there Dave outcomes, I mean that's a lot of what I like to speak to customers, about and. Sometimes, I get that get lost, particularly with, with, in highly technical, fields like. Virtualization. Guy or network guy I can very quickly start, talking about the nuts and bolts of technology, and I'm, a techie I'm absolutely, a nerd like the best technical but. Fundamentally. We're putting in technology, to meet business outcomes, business, to. Solve business problems and, and. To enable, a, better way. Love it we love tech too but really it's all about the customer so let's, talk about smart data you know when you when you throw out terms like this is it kind of can feel buzz wordy but let's, let's get into the meat on it what does that mean to, you one, of the critical aspects, of so-called smart data. Coulomb. Probably. Helped to step back a little bit and set, the scene a little bit more in terms of kind of where I came from so and be such the problems I saw entities, so I'm, really. An infrastructure, or solution architect by trade and what. I kind. Of relatively. Organically, but over time my personal, framework approach I. Focused. On three. Core design principles, those simplicity. Flexibility, in addition whatever. It was I was designing and obviously. They mean different things depending on what the technology, area is that we're working with but, that's to be a pretty good step and. What. I realized. So we realize when we started was. That those principles, could, be it. Could be used more broadly in, that the, absolute, best, of a new breed of technologies, and those that really disrupt.
Significantly. Improve upon the status quo in one, or more of those three areas ideally. Also in, terms of being, more simple, more flexible, more efficient and. If, we look at, data. And the challenges, that organizations. And. Surprises, so. Organisations, of a particular size have around data, and smart. Pacer and the best way of doing things. Maybe it's good to reflect on what the opposite end of the story is kind of wide face is often quite dumb so. Position, approaches, we have limited. Visibility. Into the data that we're actually storing, and using within our infrastructure, and, what, we kind of ended up with over time through, no fault of the organizations, that have to be having the specified, there, are kind, of silos, everywhere, those silos, of expertise, so, whether, that be borne, out specialized. Themes for socialization. Networking. They face a dimension example, and silos. Of infrastructure, which creates. Face. Of fragmentation, those, copies, of data in different areas, of the infrastructure, and copies. Of. Replication. In that data set or replication. In terms of application, environment, and. The, facts kind, of what we tend to focus on and what. It's becoming, and. Resonating, with more and more organizations as. A survey. One, of the vendors that we work so it's actually our launch lenders, five and a half years ago a vendor called kahit series on annalisa days. They have it with a company, called Manson, born to, do a first, of our kind of global market survey, nine. Hundred respondents. All different sectors all different. Countries, so US UK Germany bunch, of others and, what, they found was pretty. Shocking it was a key city survey so it was focused on secondary, data but. These kind, of lessons learned for the information taken, out of that survey applies right, across the gamut of infrastructure, data organization, and. Just some stats just to pull out the from my notes, 85, percent of the organization, surveyed, store between two, and five it's, still a data industry, two and five public clouds sixty.
Three Percent of organizations have, between four and fifteen copies, of exactly the same data, maybe. Nine out of ten of respondents, believe their organizations, secondly doing as fragmented across the silos that I touched on found is, or would become nearly impossible to, manage over the long term and. Ninety-one, percent of the vast majority of organizations leadership, were concerned about the level of visibility their, teams having today. So. They're the kind of areas, that a smart, approach new data will directly, address so reducing. Silos. So. That comes from simplifying. So moving, away from complexity. Of infrastructure, reducing. The amount of copies of data that we have across the infrastructure, and. Reducing. The amount of application, environments, that you need the different at different areas so. The smarter, we get with data is, in. My eyes anyway the further we move away from the most efficient living legacy. There was a lot in that answer but I want us kind of summarize it by if I can do talk you started with simplicity, flexibility. Efficiency of course that's what customers bought and then, I was going to ask you about you know what challenges, customers, are facing and I think you laid it out here but, I want to I want to pick on pick. Up on some of the data that you talked about the public cloud creep, I mean, that adds complexity, and diversity. In skill, requirements, the copies, of data is so true it is like data is just like. Like tribbles if you start Trek Fran it is they just you, know expand. And and replicate. So that's an expense, and it, adds complexity, siloed. Data means you spend a lot of time trying to figure out you know who's got, the right data what's the real truth so. A lot of manual, processes, involved, and then the visibility, is obviously. Critical. So those are the the problems. And, and of course you can sort of talked about how you address. Those but. But how does it work I mean how do I know there's what's involved, in, injecting, smarts. Into, your data lifecycle. But if we think about it so, in terms of the infrastructure, and let us say there are very good reasons why, customers. Are in the situations they have and then used in the situation, that they're in because. Of the, limits of. Traditional. Approaches, respective to look at something as fundamental as storage. Examples, and. And. Applications. That utilize data, something, as fundamental as back of an archive now, often, what that typically. Requires is.
Completely. Separate infrastructure, to everything, else but. When we're talking about the dataset so what. Would be perfect. Is if we could back, up the data and use, it for other things and, that's where a a. Technology. Provider like. So. Although it's their, technology is incredibly simple it's. Also incredibly powerful, and allows simplification. Consolidations things and then. If you look at just. Getting insider. At that basis. Fundamentally. Tradition approaches to infrastructure, they're put in for a point purpose, of putting for a point requirement, and so. Therefore though it wasn't really incumbent on them to, expose. Any information, out of the data that's stored within these traditional, infrastructure solutions, which makes it really tricky to do, anything else, outside of the application. Mode and, that's that's where something like ayat. Aho can come in in terms of subtracting. Away the complexity, more directly, delivery, business insight. So. These are the kind of key, areas so I think one of my actually. Did enough is quite ready but genuinely one of my favorite, quotes, is from the French philosopher and, a map fishing Blaise Pascal, he. Says if I get this right I'd have written you a shorter letter but I didn't have the time so there's real I love that quote for lots of reasons i. Rectification. In terms of what we're talking about it subsidies. Actually really complicated, to develop. A technology capability. To make things simple do more directly, meet the needs of the business through X so, you provide self-service. Capability. I don't just mean self-driving. I mean, making, data and, infrastructure, make sense to the business users that are using it my belief is that. Technology. Shouldn't. Mean that the users of the technology have, to be technology expert, what. We really want them to be and they should be a fitness, expert, and any technology they use should enable and inform. What they're looking to achieve about. The types of technologies. That get me excited they're, not necessarily. From an equity. Complicated. Technology perspective but, those that are really. Focused, on simplicity. Capabilities. Information. Yeah. Okay so you talked about backup, you know we're gonna hear from cookie City a little, bit later and, beyond. Backup data protection data, management that. Insight, piece you talked earlier about visibility, yeah that's what I Oh Tahoe, is bringing table, with its software, so that's another component of the tech stack if you will and. Then, you talk about simplicity we're gonna hear from fewer storage they're all about you know simple storage they call it the modern data experience, I think so so those are some of the the aspects, and your, job correct, me if I'm wrong is to kind of put that all together in, a solution and then, help, the customer, you know realize that what we talked about earlier that business out. And that's, it's. Fitting, that both sides and understanding, both sides so and, it key to us and, our ability to be able to deliver on exactly what you just said it's being experts. In the capabilities, and new and better way to doing things but, also having, the kind of the, business understanding. To be able to ask the right questions, to identify, how, newer, better approaches, it, has all these issues and, yeah. You touched on yet three vendors that we work with, that you have on the panel very. Genuinely, of I think, is the most exciting. And innovative technologies.
That Are out there, okay. The, storage and i/o time but, pure is a great one so yes a lot of the. Way that they've made their way in the market is through simplicity. And, through. Reducing. Data, redundancy etc. But, another, area that I really like is with. Their platforms, you can do, more with less and that's not just about the. Easting data redundancy. That's about creating, application, environments, that can service, their, in the infrastructure, to service different requirements, that are able to. Do. The random, i/o thing without getting to kind of low-level tech as well as the sequential so what that means is you don't necessarily have, to move data from, application. Environment aids do one thing manipulate, it and then move it to the application environ fee application. Environment, 3 in terms of an analytics, and a left-to-right workflow, and, keep the data where it is use, it for different, different. Requirements, within the infrastructure, and again, be more with less and what that does it's not just about simplicity. And efficiency it, significantly. Reduces the time to value at that basis as well about, again resonate, that I was to pick up a soundbite that the resonates, with all of the vendors we have on the panel later there's, a way that they're able to have. A better a better PCO, better ROI and, significantly. Reduce the time to value of data that. All happens but, to answer your question yeah you're. Exactly right so it's key to us to kind. Of position understand. Customer requirements, position the right technology, with the right hands has, been achieving visa. Adam. I wonder if you could give us your. Insights. Based on your experience, with customers, in terms of what, success looks, like I'm interested in what they're measuring I mean I'm big on into. N cycle, times and taking a systems view but of course you, know customers, they, want to measure, everything whether, it's your productivity, of the developers, or you, know time to insights, etc, what are they what are the KPIs, that are driving, success, and, outcomes. Double, kpi's. And. Historically. In our space they've always been a bit woolly when you talk about total. Cost of ownership you, talk about return on investment, we talk about time to value and, I've worked in many, different types of companies and many different types of, infrastructure. Often, quite complicated requirements. And in destructive servicemen, and, being, able to put, together anything, particularly. Realistic that. Gets proven out once the solution gets put in around ROI and TCO is. Challenging. But now with, these newer best approaches, that are more, flexible and more efficient, enables. You to really. Build. A true, story, and, and. Replicate. Whatever you kind of promised around kind of our like TCO and the key thing is to say from data enough that a couple of times now it's, time to value so that what we what we help in terms of the scoping. And in, terms of the understanding, what the requirements, are we specifically. Call out this. Is outcomes, what, what, organizations, are looking to achieve and then tack on those metrics I do. Those do, those outcomes but what that does is a, few different things but it provides. A certain success criteria. Whether that success criteria, within the proof of concept was specified theory of an overall solution we put in and being. Able to speak, that language and, as, I, said before broad, directly, meet the needs of the business we check in a kind of crystallized. Defined. Way is. We're. Only realistic, to be able to do do that now with the technologies.
That We work with authority. In borderline. Think about the business case the ROI of benefit, over cost of benefit obviously lower, TCO you lowered the denominator, you're gonna increase the the output and the value and, but I would I would really stress that I think the numerator, ultimately, especially. In this world of data is, the, most important, and I think the TCO is fundamental. It's really becoming, table stakes you got to have simple you got to have efficient, you, got to be agile, but it's it enables, that, that, numerator, whether, that's new customer, revenue maybe, you, know maybe cost savings across the the business and again that comes from taking, that system's view do. You have examples that, you can share with us even if they're anonymized, the customers. That you you've worked with that or maybe a little further down on the journey or maybe not and things that you can share with us that are kind of proof points here so it's. It's. Quite easy and, very gratifying, when somebody's spoken soon a customer, that we know you've been doing it this way for years and this is the way that your infrastructure. Architected looks like you don't architecture. If you did it like this if we implemented this technology, or this new approach then, we will, enable. You to something. As simple that often really powerful is reduce your battle, creek from a storage perspective. I've worked on a project where a customer reduce. Their footprint. From I think, it was it was nine it's just under ten it was nine fully, loaded rap tracks we, should just full of this with providing. The fundamental. Underlying, storage architecture, and they were able to consolidate, that that, down and to provide additional capacity. Significantly. Greater performance in, less than half or. Looking. At the mentioned, data protection earlier so another. Organisation this is a project, which is just coming nearing completion at the moment huge, organization. If literally, petabytes, of data that. Was that was servicing, their their, backup an archive and what, they had is not just this greens of data they, had become, Brian saying five different backup applications, that, they have dependent. On the, what. Area, of infrastructure, they were backing up so whether. It was virtualization. That was different who they were back in at beady things if, they of backing up another, database environment, very something, else in the cloud so, a consolidated. Approach. That work that we recommended, it work with them on they were able to, significantly. Reduce complexity, and reduce. The amount of time that it's system what. They were able to achieve and, this. Is again one of the key were crimes they have safe Donna, above the threshold have being able to back up all of them when. They tried to do at, the our test who.
Been. Everything back up in a, secondary datacenter, they weren't able to achieve it with in the end of time scales, as via this. Day disaster. Recovery and business continuity plan. Dictated, so with this were able to prove them with a kind, of proof, just. Before they went into production a day our test using the new approach and they were able to recover, everything. The entire infrastructure. In. Minutes. That city in terms of all production the, production workload. At this was in comparison, to ours, and that was those hours is just with a handful of workloads, they, were able to get up and running with the entire estate, in. Think. It was something like an hour and the core production, systems. They were up and running practically, instantaneously. So, if you if you look at really kind, of stepping back what these customers, are looking to achieve they want to be able to if, there is any issues recover from those issues as quickly as possible understand. What they're dealing with from an industry, reduce. Us and. Another. Customer. That we worked with recently what they have, huge, challenges around. And they were understandably. Very scared, about GDP, are so this was a little while ago actually. It, still it's not a conversation, has gone away just for everybody, I still speak to issues, and concerns, around GDP are and flying, understanding. Where their data store than putting them in a in a position to be able to effectively react, the subject that's that's request that was something that was a key, metric a key target for an, infrastructure, solution, that we worked with and we were able to provide. Them with the insight of the day into, their dataset and, enables. Them to work react, to compliance. And adhere to yet subject, that touch request that we created, in. Significantly. Less time and. Awesome thank, you for that I want to pick up on a little bit so the first example is you get your infrastructure, in order you bust down those silos and, what I've when.
I Talk to customers and I've talked to a number in banks, insurance companies other, financial services of manufacturers. When, they're able to sort of streamline that. Data. Lifecycle. And bring in automation. And, intelligence. If you will what, they tell me is now they're able to obviously, compress, the time to value but, also they're. Loading, up on way more initiatives, and projects that they can deliver for the business and you talk more about about. The line of business having. Self-serve. The, businesses, feel like they actually, are really you know invested, in the data that it's their data that it's not you. Know confusing, and a lot of finger-pointing so, that's, that's. Huge and I think that you, know your, other example, is right on as well of really. You know clear business value, that organizations. Are seeing so you know thanks for those you, know now is the time really to. Get. These houses. In order if you will because it, really drives competitive, advantage especially take, your second example in this isolation, economy, you know being able to respond, to things like privacy. Or just increasingly, critical by, Adam give us the final thoughts bring us home in this segment. And. Something, yeah, we didn't particularly, touch on but I think is it's, kind of funny, probably, hidden it isn't spoken about as as much as I think it could be it's that traditional, approaches, to infrastructure we've already touched on, there. They could be complicated, and, there's. Lack, of efficiency, impact. A. User's, ability to be agile but, what you find with traditional approaches, and you've already touched on some of the kind of benefits of new approaches, there it's, that they're often very prescriptive, they're designed for a particular firm, the. The infrastructure, environment, the way that it's served up for the users, in the kind of a package, kind of way means. That they need to use it in that bit in whatever, ways indicators. So, that kind of self-service. Aspect. Comes. In from a flexibility. Standpoint, that these platforms, in this platform approach which is the right way to address technology. In my eyes enables. It's the infrastructure. To be used flexibly of, it the business users and the data users. What we find is this in. This, capability, into their hands they start innovating, in the way that they. Use that they and the. Way that they bring benefits and, if a, platform, is too prescriptive and, they aren't able to do that so what you're doing with these new approaches, is get, all of the metrics that we've touched on is fantastic, from a cost standpoint from a disability standpoint. But what it means is that the innovators, in the business the ones that really is really understand what they're looking to achieve they now have the tools to innovate, with us now I think and I've started to see that with projects that we've completed if, you do it in the right way if you articulate. The capability. And you empower, the business users in the right way then, they're, in a significantly. Better position, these businesses do they give an advantage, of this and really. Kind. Of match and significantly, beat off from their competition in. Super. Adam I mean nearly exciting, space and we spent the last 10 years gathering, all this data you know trying to slog through it and figure it out and now with the tools that we have and the automation capabilities it. Really is a new, era of innovation. And, insight, so Adam where they didn't thanks so much for. Coming in the cube and participating, in, this program, now. And Counting times than that thank you very much today a four by four million. All. Right stay safe and thank you everybody this is Dave Allante for the cube.