>> Narrator: From Burlingame, California, it's theCUBE, covering Sumo Logic Illuminate 2019! Brought to you by Sumo Logic. >> Hey, welcome back everybody, Jeff Frick here with theCUBE. We're at Sumo Logic Illuminate at the Hyatt Regency, San Francisco Airport. Our second year here, about a thousand people, third year of the conference, a really good vibe. You know I think some of these cases where the marketers really come to Sumo Logic in terms of data and data monitoring, and there's so many applications that are business and security, and operations. We're excited to have our next guest. He is Lior Mechlovich. He's an architect at Informatica. Lior, great to see you. >> Great to see you, too. >> Absolutely, so you said you've been coming to this for a couple years, just kind of general impressions as it's grown. >> Sure, it's my third year, it's grown very nicely. Always exciting. I think there's a very nice vibe to this conference. I always learn new things so we've been with Sumo for more than four years now for Informatica. And excited as always. >> Yeah, and we've been covering the Informatica show. I think we've looked it up, since 2015 so, we've been doing a lot of work and you guys are right in the heart of this whole data thing, >> Right. >> And you been part of the kind of migration from pretty much pure on-prem, to Cloud. There's rush to public Cloud, and then now kind of this Hybrid model. So you kind of look at the data perspective you know, what's kind of your take as this thing has evolved over the last several years? >> Sure, so we have been around for 26 years. I think building a lot of on-pram, data platforms for being the enterprise Cloud data management that Informatica sells with basically getting your data inside our outside the organization from Clouds, on-pram, or whatever integration pattern you have and we decided four or five years ago to be a Cloud-first company and migrated most of our products to be on Cloud to provide them as a service. And for us, it was a huge journey, we needed to take some offering that we had in the Cloud, some products, and really revamp and building a new microscopic architecture and then slowly migrate all the customers. It took us over a year to make that. We currently run on all three Cloud providers. And really using Sumo mentoring tools to really understand the impact that we have on our customers during this migration. It was a very successful. They hardly noticed that-- >> Oh good. >> Only the nice UI, but they hardly noticed the problems. I mean we really changed a lot of things. >> What is some of the things you learned in that process that you can apply now with just some of your customers in terms of data migration and operating in a Cloud situation versus a traditional data center? >> Sure, so I would definitely highlight the need to be able to roll back and the need to always keep really good money to working it and understanding how the end user getting impacted. And so we really kept that in mind. Everything we do try do always do it side by side, and then when we migrate we're really sure that it is successful and there's no impact on the customer. So I think that's definitely too, harshly monitored everything and be able to roll back when you need to, because you will need to at some point. >> But the rollback is funny, because it use to be you had you know the release cadence was significantly slower than now. And now you've got all these kind of micro pushes that are going on multiple times a day. >> Yeah. >> So how does that impact kind of keeping that safety net? That rollback safety net? >> So it's interesting. So we actually don't deploy that many times a day. Where we can really impact the customer so we deploy the things that are not customer urgent impacting production more, but still the really heavy productions of the thrilling part of the customer; we try to minimize that and make it very customer aware okay. >> So basically they choose their own windows of maintenance and all that. But our customers again hospitals, all kinds of very important, then we are in charge of the data byte in those places. So we don't want to just push whatever we can. We really cannot take that, even a rollback of 1%, it can be very bad so we're a bit more conservative models of deployments, but actually that means we put a lot of effort in our monitoring. What is going on doing those deployments. >> Right. All right, so what are the big trends that happen? I mean containers have been around for awhile, but we really saw kind of the rise of containers in terms of the popular consciousness with Docker couple three or four years ago, and then a couple years ago the Cooper 90's coming in for the orchestration. From your point of view how had those things impacted your world, and how you do your job, and take care of your customers? >> Sure, so for us Cubernetics is really a great opportunity to standardize the way that we deploy across different products. So we have our platform, but we have also different products; different people across the globe. We're a very multi-globe organization, and to get a standard like Cubernetics to help us standardize to get more releases, more stable environments that really solves a lot of problems, because we had this migration that I talked about really left us with a lot of clusters across the globe, different time zones. It was really hard to standardize on the pipelines, and to deploy to really minimize the problems that we give to the end user at the end. >> So we really took that opportunity to use Cubernetics, to use containers to minimize the difference it has from the developer machine all the way to production. To automate the most we can so when it's really is excelling in this. Yeah, so that's where we really... took those containers apart. Today we are in migrating, so not all of that, but we truly see the benefits of standardization, of immutable infrastructure as that key component for us. >> This is just so great, because you have such a longitudinal point of view having been in. The company's been at it for awhile, and you've been at the company for awhile. So another topic I'd love to get your thought is just kind of this exponential explosion of data. I mean it would be curious not to know the numbers, but kind of the scale of data in which you guys are dealing with for you customers, and how that has changed over the last several years before you even really factor in IOT, and this next kind of machine to machine explosion? >> So we definitely see that explosion of data. It's not just the explosion. It's also the different types, and where data has been on-prem, now moving to Cloud. Where do people want to run off all those work loads? As of course a lot of feedback for us as well need to support all the Cloud providers when we use to do a lot of Hadoop on-prem, right? It's all changed now too. >> All the Cloud providers, the data it's theirs. So the data move, data locality is a big thing, Now we need to run all those things on the Cloud. So, I don't remember the exact numbers. I guess we're doing something of 2.5 billion transactions a month for like number of records that we serve. That being we usually just see more work loads, more people, more use cases for onboarding more data from Cloud applications. The data became more dispersed not just more data, but the sources has become like everybody needs to integrate Salesforce or Workday with their on-prem that gives unique opportunities for this kind of data. >> Well, it's funny when you talk about the workloads, because it always use to be, do you bring the workload to the data or the data to the workload, and a knock on the Cloud is that you got to get all the data into the Cloud, and pay for the transport of the data. And there's data gravity that said once you have it in a central location like that the opportunity to put applications against that data is much much higher than if you're bringing the data to the application. You see and how are customers taking advantage of that opportunity? >> So for sure we saw they did that move to the Cloud. When we started from on naked Cloud 10 years ago our entire model was hybrid, so we can stick around on-prem, because the data was on-prem, and since then our hybrid model that you still run both on-prem and on Cloud, you can see the change right? You can see more of our agents. We have an agent based architecture to really being deployed much more on easy 2's, on AKS or whatever to run those workloads in the Cloud. >> Right, but I would imagine the number of workloads applied to each data set now have increased significantly, because now it's in that central repository. >> Yes, and definitely you can see those data legs being built, and mostly in the Cloud. That gives unique opportunity. >> So just get your perspective after a couple days here. I know you haven't been here for a couple of days. We're just getting started at this show. What does Sumo Logic bring to you and your team? What does it enable you to do that you couldn't otherwise do? Why are you happy to be a customer of Sumo? >> Sure, so four and foremost it's the democratization of data. I really like to say that internally. In an organization that's spread across the globe, really sharing insides based on data, it's very important. When you have many R&D centers that can just send this summary; send the data and show people what they mean saves so much time, and so we use it across. We use the customer success, product management to understand feature being used, SRE's, developers. All of those really can communicate based on data. In this Microsoft Office tool you cannot do it without that. You cannot do it without linking, because the different products that we onboard on the platform will not be able to communicate effectively without that. So that's very important, and giving that landing pages dashboard templates for onboarded services to have this kind of standard to follow to monitor how to operate that's very important for us. >> That's great. Go ahead. I'm sorry I interrupted you. >> Sorry, and the key place that we brought Sumo in is basically for instant management. So how to understand when something doesn't work just to try to understand the blast radius, which products are impacted. We have a variety of products, so just in minutes we minimize that in four hours to minutes trying to understand what exactly is going on. Who's impacted to update the customer  and all that. >> I love the part you talked about the democratization, because again I talk about it all the time, and I'll talk about it again, but to drive innovation in a company I think such a key piece of it is to enable more people to have more information, and the tools to manipulate that information, so they see opportunities to make improvements here, there, and otherwise and it sounds like you guys are really using it for that. >> Definitely. Definitely. >> In this case. >> You know when you get some people that you never knew that even though we have a customer support guys that did some crazy dash wars that we had no idea it's possible even, and they really getting chance to work with customers better to really tell the customer, "Oh, you just did that and that. "Maybe you'll try this option." And we found that even communicating, and really minimize the time it takes for them to figure out what's going on that it's been really impactful. >> With no call to It to help (laughs). >> And it was never the intent, so we wanted to allow dev's and off's to operate, and all of a sudden you're getting customer support without even telling them. >> Good, well Lior thanks for sharing your story and really appreciate you taking the time. >> Thank you. >> All right, he's Lior. I'm Jeff. You're watching theCube. We are at Sumo Logic Illuminate 2019. Thanks for watching. We'll see you next time. (upbeat techno music)