Video: Edge Delta CEO On Scalable Observability For A Data Rich World

hey Channel insiders welcome back to channel Insider partner POV your source for untapped opportunities and unfiltered opinions in the it Channel all to help you make Better Business decisions I'm your host Katie boso my guest today is ozan unlu CEO and founder of edge Delta a startup using expertise and AI to create the Next Generation observability platform for a world where company data is growing at an explosive rate Oz on welcome yeah thanks thanks for having me kitty thanks so much for being here I have heard so much about Edge Delta in the past couple weeks leading up to us getting to record very excited to see that you came with swag and you got that plant in the background to be able to match the the logo as well so thanks for being prepared on that level yeah I I uh you know try to make sure that I have a green thumb and and try to keep many things alive including including the startup and that way you know the startups in the plans can be alive and Thrive so let's talk a little bit about Edge Delta when did you enter the market and just talk to me a little bit about how you describe what Edge Delta is and does yeah so we got our initial seed round of funding just over four years ago at this point four and a half years ago and so for Edge Delta we're in the observability space and interestingly enough when I think about and I've been in this space for about almost 20 years at this point when I think about 20 years ago the data volumes that were being created compared to today were obviously minuscule but even going back to seven or eight years ago the average customer might have only had maybe 5 or 10 gigabytes of machine data they were creating every single day and machine data is kind of defined as logs metrics events traces Etc you know the same customers that we saw that had 5 or 10 gigabytes this was you know about seven or eight years ago they now have close to let's say five or 10 terabytes and some of the customers that we work with some of the large organizations we work with have pedabytes of data there every single day and so it's not just that the data volume is growing a little bit it's that it is orders of magnitude larger than it was earlier and I think for that you do need a brand new architecture I think if you look at you know the concept of databases or data stores or data warehouses that concept that has existed for a long time if you look at streaming platforms you know most notably platforms like kfka for instance they've also existed for quite some time and probably got more popular over the last five or 10 years and then we look at what Edge Delta is doing is a very unique third part of the architecture which is how do you have distributed pre-processing and pre-aggregation of your data sets and also how do you use pipelines to be able to have a full understanding and control of your data set so realistically we're looking at ourselves as kind of a Next Generation observably platform and at starts with observ pipelines and that ends with the ability to curate data to be able to have continuous inferencing from AI I'm curious to know with the customers that you work with why are they seeing such an explosion of data is it having anything to do with the amount of the way they're doing work because they're siloed now since the pandemic is there anything you can point to in which you could say this is the reason the data is just exploding for them I think just the architectures are changing so much right you know I had the privilege of working at Microsoft uh this is you know uh quite some time ago but you know at the time at Microsoft there were a lot of resources that we had to be able to go spin up virtual servers or virtual resources or even physical machines that we had access to and Microsoft was probably one of the very few companies at that scale that had those type of resources and so I think you know today uh sometimes people call them Cloud babies right like the companies that are created and exist in the cloud and for some of these new companies they have a tremendous amount of infrastructure that they can go and and spin up very quickly so you combine that with like containerization Technologies like kubernetes and all of a sudden you have a lot of components all of which creating a lot of data and you know it's not just that the data is growing in in a single Vector it's that it's growing in numerous different factors and so you know in that case The Matrix gets quite big and therefore the data sets get quite big so I think that's just in general for uh companies it's not just simply hey I had you know a thousand customers yesterday and then a week from now I have a thousand and one with the change in architectures and microservices models and everything else uh we are seeing just such a massive uh growth of of data also you know I think the timeline The Horizon of a growth of a company is also accelerating right so you're seeing companies grow a lot quicker in which case you know the same architecture and the same observ platform they want to implement today might not scale to what they need tomorrow or next week or next month a lot of that growth especially as we see so much m&a activity going on in both the channel the it vendor space the technology of vendor space so I can imagine that there's a lot more needed when it comes to that observability speaking of which talk to me about Edge Delta's differentiators in the observability space it's a term that I hear a lot more now uh this is obviously not the only company that does this and specializes in it but where did you see a gap that needed to be filled by Edge Delta's existance we are the original player in the space doing intelligent pipelines that are the most flexible that're the most scalable and they allow you to have full understanding and control of your data sets so you know we're pretty proud about that um that's really from an end to-end scenario we again look at you know databases or data warehouses or data stores we look at streaming platforms and we look at the edge you know our name obviously Edge Delta is kind of a throwback to that right it's saying hey observa pipelines start at the edge your data starts at the edge and we are the original players in that space the other part about it is that AI although extremely powerful is very difficult to build a business on if you're not hyper aware of margins right and so in our space where so much data is created you cannot take the same lazy approach of saying well for instance you know in observability you could say hey I have a low value data set it's very large I want to go throw that in S3 first right S3 is obviously Amazon's you know object storage um obviously Azure and gcp have their equivalents as well and you can do that and you can say I want to go work with this data later well with very large data sets you actually have to find a way to curate that data and to pre-process and pre-aggregate and effectively figure out of all this data of all these terabytes and potentially pedabytes what are the unique things that I want go you know effectively tokenize and put into uh an an AI model for even if it's just for for inferencing and that is uh an entire kind of you know science and business on its own so I would say specifically in observability an area that has a lot of data sets being created um at all times I would say that we are at the Forefront of also being very differentiated in the market for how do we curate observability data sets to be able to get continuous inferencing from these models without uh giving away this recipe for the secret sauce so to speak can you talk to me a bit more about how AI is used can you walk me through maybe a scenario in which AI we see it in real time functioning uh inside of the edge Delta product yeah so we just released our uh first real big AR feature called on call AI and so what on call AI is much like its name might suggest is that there's a concept of on call in observability which is basically hey who's the first person that goes and takes a look at something when there's an alarm or there's an issue or there's an alert or there's you know something that basically says hey even if it's 3 in the morning the person has to wake up they have to open their laptop you know as their eyes are adjusting they're trying to figure out what's going on with the infrastructure that is a reality for many people that are you know in the SR devops uh observability space and on call AI the very first thing it does is it says hey why don't we have an AI first take a look and we are big Believers that at the end of the day AI can look at things it can have opinions it can even recommend things but ultimately the engineers the professionals they do need to decide right and so on call AI is really kind of a technology that is on that same wavelength which is effectively hey let's go and and have ai do the first pass and say hey what are the issues that are happening right now in real time what do we suggest as a potential resolution and it allows them to instead of you know waking up at 3 in the morning and starting at square one maybe they're starting at Square you know four or five right where it gives them a little bit of a head start to say okay maybe this is right on the money maybe it's a little bit off but you know either way I'd love to have another opinion that just informed me in real time so I've already thought of the tagline on call AI giving Engineers more hours to sleep yeah yeah that's that's not bad I'd love to talk about your customer experiences with Edge Delta can you point to a a specific customer success story in which you were able to help a customer have a better business outcome we actually did just release a great video that includes benus CTO of box they're a very happy customer of ours and we're very appreciative of the partnership with them and I thing for them as as Ben talks about in the video there is this concept of optimizing data sets right and so you know if you take a look at logs for example not every single log is super critical and when you're creating terabytes or even pedabytes of log data a day not every single piece of that data needs to go through a very expensive ingestion architecture and so you know uh the concept of pipelines then enables you to uh apply this concept of data tearing and that and many times can reduce your cost by you know 90 95 even 99% in in certain cases now we never like to promise 99% we don't even like to promise 90% but the reality is for for certain use cases and certain you know data sets you absolutely can reduce your costs quite a bit the other part of it that that really helps out is that it allows you to have a full understanding of your data sets and how they're being used and so you know you might look at your data sets and say hey these log messages are you know whether we're doing log to metrics conversion on them and we're seeing those metrics on the dashboard or we're alerting on the metric that comes out of the log or we're alerting on the logs themselves there's a lot of different use cases that that you can use this data for and just having an understanding of what data is being used and what data is not being used uh I think that's a really big value for organizations moving on from there I'd love to talk about the hyperscalers that edge Delta Works with and helps run on top of can you talk to me about your relationship with them and which one specifically you're you're working in tandem with yeah I I would say that we're you know working with the big three so my background I was actually a software developer um on the Azure team um in a different Lifetime and so you know obviously we we work with Azure quite a bit we also have a lot of our infrastructure that's on on AWS and then you know I was just at Google next uh which is gcps Big conference down in Vegas a few weeks ago so I think what we try to do is is stay pretty agnostic a lot of our customers Al also are big Enterprises that want kind of you know their multicloud strategies so we have to make sure that we're potentially up and available in in in multiple different clouds so you know I would say we do have our preferences on what we do with which hyperscaler but that being said I think we're seeing a huge kind of shift in the space obviously due to AI is is a big part of that right we saw what Microsoft was doing with their investment in open Ai and I think in many ways Amazon and and gcp kind of got caught a little bit on their back foot but you know then they're making their own kind of strides and Investments there as well with adbs bedrock and and gcp is doing their own things as well so yeah I think I think it's an exciting space I think you don't ever want to shut the door on any hyperscaler uh so I think they all have their place and they all have their pros and cons and what they're good at going on from there the channel overlap that edge Delta has do you work with other channel solution providers whether they be msps vars integrators can any of them find a benefit in working working with Edge Delta to be able to close more deals with customers or maybe enter a market they hadn't been in before yeah absolutely and I think you know the way that we like to approach new Partnerships is really to look at hey are there just simply one or two customers that we can go and talk to and go you know really allow them to pull their observability initiatives in a much more modern Direction uh and I think for us you know if you look again at that three different components of observability you know one being your store the second being the streaming layer Edge Delta really is that third piece of the puzzle and I think for us uh we are very happy to work with any type of partnership or Channel partner if we've identified hey you know we have a customer over here that you know they've been using Splunk for years or they've been using data dog for years and whether the system is just getting kind of old and and and the performance is kind of degrading or if the costs are out of control or if they're just wanting to go in a new Fresh Direction Edge Delta is going to be the future of the architecture that's underlying for observability and so we're always happy to chat about that I think you know our product also can get up and running in minutes you know we have a an open trial that anyone can go use and so we typically like to come in and talk to the customer and really work with them and then last week just I was I was traveling in uh in Texas and uh we got we got a new customer up and running in a matter of minutes I think it was three or four minutes that they created their account you know added some sources immediately started seeing insights it's quite fun funny because from like a proof of concept or a proof of value perspective realistically the red tape is much more in the actual business process whereas the the technical requirements uh literally can be solved in minutes so I think we'd be excited to work with any new partner and I think for us instead of trying to boil the ocean it's really about identifying one or two you know potential customers that we can work with and the other part of it is that we're really confident in the product so you know we want to put the product first we want to get it in the hands of our potential end user and you know I think the product can do lot of that work itself very well said and very interesting to hear about that relationship that they can expand on with you I want to talk about you now let's talk a little bit about your career in researching you it was really interesting to learn what you've done you mentioned working with Microsoft but you've also worked with other vendors that I would never have said this before but you've worked for Boeing which I think is amazing you've worked for sumotech you've worked as a nanoscientist that's your your background talk to me about your journey to becoming CEO and founder of edge Delta just walk me through that career path and where you said hey there's an opportunity for me in this space that perhaps is nothing like what I'm doing right now talk to me about your journey when I was in the nanotech field uh you know I I was still a student at University of Washington and the most interesting part about that if you look at let's let's take Reddit for example um I think Reddit is famous for some new technologies posted and then I think the top comment is always like cool we'll see it in like 20 years once it's prized right I think there's so much very intriguing and interesting things happening in the research space that realistically won't get productized at a massive scale anytime in the next 10 or 15 years that was my experience at nanotech was there were some phenomenally amazing things that you could do in nanotech but realistically the big problem was how do you actually get it to work at scale one of those examples was you could literally spit into like a petri dish and you could take a carbon Nano tip and you could basically go and look under a microscope after putting it in the saliva and you could look and you could see actually oh are there like cancer particles uh in in someone's life even to the point where you could identify to say okay what type of cancer or where where where in the body is that cancer 20 years ago the challenge was like well you can manufacture these nanot tips so us as effectively in the lab as as scientists we had to manually with with our bare hands basically pull out and manufacture these these nanotips one by one and so you know there was a lot of research at the time going into how do you basically create these these Nano tips at scale you know when I was at Microsoft uh I was always a good developer at Microsoft you know I think for for Microsoft standards I don't think I was ever a superstar so you know I think for for me and I had some friends that were saying hey look you have some some soft skills you have some business understanding as well you know I'd hate for you to only live in the code sometimes I look back and actually that was the most fun I ever had in in in Tech but you know it definitely did draw me to go to sumal logic where you know I was the first uh sales engineer on the midmarket team there and the sales engineer or solution architecture or field engineer there's a lot of names for that role but that really allowed me to kind of marry not only my technical expertise but also my business Acumen and being able to kind of have the soft skills and and presentation skills and being able to work with customers so the most exciting part about that probably in that transition was you know at Microsoft you you work on a single project for maybe six nine months and maybe you know more about that area than anyone else in the world but then maybe 95% of that knowledge or experience doesn't really translate to the next role when you're when you're working with so many customers and I think in my first year there I probably worked with 200 300 different customers you get to see a very very large breadth of understanding of what's happening in the market you know how are various different organizations kind of implementing these Technologies and so whereas I was very very deep in certain areas at Microsoft the kind of breath at at Sumo logic was was a breath of fresh air for for sure and so from there being able to have both a technical and a business background um I was able to identify certain things in the market and that's what I always try to um encourage early Founders that have kind of Ambitions to be entrepreneur and be a founder and create their new thing is make sure that you are an expert in the space make sure it's an area that you have years and years of of intimate knowledge on and therefore you can make a very educated understanding and and a guess of hey here's a a gap in the market and here's where I want to go build my my initial MVP if I am an IT buyer if I am in the channel and interested in working alongside Edge Delta or I just want to learn more where can I go we are always happy to chat you can go to our website and you can sign up for a demo and we will jump on a call with you and walk you through our product but it's also open so you can go right to our website you can start a free trial and try it yourself edgd delta.com uh you can you can either request a demo or you can try it yourself and we'd love the feedback amazing thank you so much for your time today ozan I look forward to having you back in the future absolutely thank you Katie thanks so much to ozan for joining me today and thank you for watching or listening to this episode of Channel Insider partner POV you can check out all episodes on our website Channel insider.com or watch on our YouTube page at Channel inssider newws and Trends you can also listen to the podcast version on your favorite podcast listening platform like apple podcasts or Spotify don't forget to like subscribe and follow to never miss an episode once again I'm Katie boso and I'll see you next time

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