 Modernizing applications can be a complicated situation for many folks. It's useful to have some best practices and tangible steps that can remove friction and yield some quick wins. We're now joined by couch-based CTO Ravi Mayaram, who will cover how organizations can approach application modernization, what role the cloud plays, and what you need to know about building a business case. Ravi, welcome back to theCUBE. Good to see you again. Very good to see you. Thanks for having me, Dave. Yes, our pleasure. According to a recent couch-based digital transformation survey that you guys ran, about 650 respondents, CIOs, CTOs, et cetera, the inertia of legacy technology held back according to the respondents, 82% of enterprises from modernizing their portfolios in 2021. So I want to talk about the what and the why of modernization. Ravi, what does application modernization mean to you and why is it top of mind for organizations? Yeah, I think there have been multiple forces at work here for a while, and they have all come to a tipping point with the pandemic and it's a combination of factors and the legacy technologies were built for a different generation of applications. So it's a generational shift that we're undergoing. Part of it is the consumption model, which is all cloud-based and pay-as-you-go kind of stuff. The other is edge is in the middle of a lot of these conversations, together with the velocity variety of data that you have to actually sort of consume and results that you need to produce. These were all not what the sort of the infrastructure of old, on which the applications were built on stand for. So the infrastructure of the substrate requires modernization in order for the businesses to transform themselves. That's what's going on. We call it digital transformation from a technology perspective, but it's businesses that are transforming the business models in front of our eyes. We have seen the media go from set-top boxes to streaming everywhere. Like that, every business e-commerce has changed the way we sort of do any business. Gaming has changed the banking industry, the healthcare, everything is changing in terms of the fundamental movement, if you could sort of say that, is to reach the consumer directly and sort of disintermediate the intermediaries. And in that process, the technologies that we had used to build the last previous generation of applications no longer scale, no longer nimble enough, no longer cater to the modern, the needs of the modern data and the infrastructure on which we are standing of these applications. So that's what's driving the modernization effort. And in that, we have always started, say that a few years ago, that data is the new oil. So that plays a very critical role in how the data silos and infrastructure that enterprises have is what's holding them back. And this whole effort is in terms of modernizing that infrastructure through the modern means of the cloud computing, the modern serverless architectures and microservices and the edge and AI play an important role in this. So we're going to hear later from Amdox about their modernization and where couch base helps and fits, but I'd love to hear your perspective as to how couch base helps organizations modernize. Right, I think one of the fundamental things that has happened is that in the last 30, 40 years, the data infrastructure has sort of become a sprawl. We had built multiple systems, relational databases, caches, search systems, analytical systems, all requiring for us to move the data from one system to the other in order for you to get the value from those. And this is basically what we call as a data sprawl or database sprawl. And this leads to so many sort of downstream effects all the way from data not being available at the time when the customer is engaged to data governance, security and all those issues because the threat surface area is wide. And now you're putting all this infrastructure on the modern sort of cloud computing paradigm and the costs are sort of ballooning. And because those older infrastructures that were built when you deploy them on the cloud, it creates its ads to the complexity of the sprawl and on top of the cost of this. So a system like couch base is what simplifies this sprawl for our customers. And it is built for the modern sort of requirements of scale and performance, low latency and the flexibility of being able to sort of not have to go through this whole so cycle of whenever you have to have a change in your application that touches your data that it actually creates a huge tumult in those upgrades and all those life cycle having to carry pagers. I mean, that doesn't work anymore in these days of, you know, five, nine uptimes and 24, seven, 365 availability of your services. It's so in that area is where couch base sort of helps our customers to modernize their sort of data infrastructure. It fuses the multiple technologies that were spread across into one platform. So it gives a simpler programming paradigm. There is one way to scale, manage, administer, patch upgrade all that mechanism is sort of not just thought through and automated, but it also sort of centralized. This whole thing simplifies at the end of the day the total task of managing because the volume of data that you have to manage now is, you know, orders of magnitude, three to four orders of magnitude more than what it was just a few years ago. And so in that, containing the sprawl, agility of development are sort of and the simplicity of deployment and management are some of the key capabilities that enterprises look to us to solve. And in that, bringing in all the way from cloud to multi-cloud edge is how this sort of strategy evolves for enterprises. So square the circle for me, because in the panel we just had a lot of agreement with what you just said, lift and shift of legacy platforms doesn't work. It might work for the cloud vendor to get the data in the cloud, but it generally doesn't work for the customer. And you mentioned sprawl, we talked about this in the panel about data by its very nature is distributed. We talked about data mesh. There's a lot of skepticism around data mesh, but that's cool and you mentioned edge. So I'm interested in the cloud's role here is the idea that you're actually putting all this stuff in one place. How does that fit with the edge? Maybe you could help us understand your thinking of that and where the cloud fits. Yes, you know, it's about centralizing the data to a point and decentralizing. It's in the magic of how you actually enable that. For example, just your traffic signal, your car, or if you're on a cruise ship, each one is an edge. They all generate petabytes of data and then you basically, you can consume that. But if you're going to stream all this data to a centralized place like a cloud, that's, you know, most of the data actually is not something that you're going to store forever. Those are, you know, topical and that information is required at the edge. You should synthesize that information and take the noise from it and discard the signal. So that's where the edge, typically the edge is not some, you know, personal device alone or IoT sensor sending data. That is also sort of one element of the edge. But the edge is about decentralizing the cloud. So to say, so you can have your topologies of not having all your data sit in the cloud, centralize someplace behind five firewalls. So when your application tries to reach that, all the latency comes into play. So that's what you want to decentralize and have the data available as close to the engagement of the data with the consumer of it. So in that is the decentralization strategy where you can have multiple topologies, a tree, a mesh, however you choose to, so that you get the data closest. It could be a mobile device. It could be a smaller deployment of a server. It could be a personal electronic device like a watch or it could be all the way in an IoT gateway. These are the various sort of decentralization of the data that has to happen. So it's about moving the data fastest. It's almost like CDN-ing of the data is what, sorry, for those, it's a content delivery network. It's what CDN stands for, where we used to actually move static content in the good old days. That's what made our web pages faster. Now we can actually move live data that much faster by using replication technologies. So when you move the data towards the edge, what you're trying to do is bring the data closer to the compute where it's actually happening, as opposed to keeping the data centralized someplace back in the cloud and server. And all your application logic is actually sitting on the device or on the edge. So you're constantly shoveling the data from the cloud to the edge, from edge to the cloud at the time of compute, as opposed to having it available at the time of the consumption of the data. That's where the paradigm shift is actually happening. And this basically is not about better user experience. It's also about back-end networking and other costs that you can actually gain from by not having to sort of repeatedly sort of shovel data back and forth. So that's the strategy that enterprises are adopting. Now this has become so to say core part of the architecture of modernization in terms of where everybody can see this has to move to and our edge and mobile product also plays a role. And that's one of the other elements, aspects of it that customers to look to us for. So it's a balance and couch base can play in both places. A lot of the data, if I heard you correctly at the edge is ephemeral, but if I want to do AI inferencing in real time, I got to do it at the edge. I can't send it back to the cloud and do the modeling post-process. That's not going to work. All right, let's talk about the business case. You know, we've hit on the what and the why, but how does it get paid for? Companies sometimes struggle to plan for and budget appropriately for their outcomes. What do customers need to know about how do they get this past the CFO's office for the other business decision makers? I think there is an opportunity cost with the sort of lack of modernization if people are doing their classic sort of, so to say, IT style budgeting, then it will just look like we have to modernize some older infrastructure. It's not about that, it's about modernizing or making your business relevant to the consumers because the way consumers go about consuming your services now is very different from the way you had originally imagined and built for. And in that lies the transformation, not to see this as a IT, just as an IT infrastructure modernization, but more from the standpoint of business transformation and the tooling that is required for this business transformation to be successful. So it requires the involvement of not leaving it to just IT oriented sort of thinking of modernizing, but from the standpoint of looking at the business and what are the transformations that they need to, if they don't keep up with the Joneses, they in this digital divide, they may find themselves in the sort of either the wrong side or in the chasm. So I think that mindset that sort of in addition to sort of IT pushing for this, it's got to have a C-suite sponsorship, understanding and sort of championing of this. Then those initiatives will succeed because it's not just the technology transformation, it is accompanied by business and sort of sort of a cultural transformation inside the enterprise. Yeah, and it's interesting in the survey, it was very much IT survey, I get that. And the IT pros, the CIOs, et cetera felt that that the IT organization was largely responsible for the digital strategy. And I think that was largely a function of we just came out of the pandemic or coming out of the pandemic. And so they had these tactical needs, but now you're saying, step back, align with the business, make sure the C-suite's involved and that's going to reduce the friction of getting this stuff paid for. Correct. And you know, this observation was also there if you must have noticed that, you know, many of these sort of transformative strategies, if you just leave it to like an IT thing, they end up being reactive. But the proactive strategies are the one that actually succeed because they understand that this is a sort of enterprise transformation, it could be disruptive, it is what is required for the enterprise to get to the next level or to be relevant in this sort of modern economy, if you would. So I think that is what people are reacting to is the fact that this pandemic has pushed people to modernize quickly. And that may have happened as a reaction to the reality of the situation, but more and more, even among these strategies and more and more initiatives that people are taking, they may have sort of a longer term, sort of thinking in this, that requires the, definitely without our teams not going to succeed. And they are going to be in the middle and they will be in the forefront of many technology decisions that they have to make. But having a C-suite level sponsorship in addition to that, with the impetus of what is the business transformation this is actually going to achieve, those you will see will succeed a lot more because otherwise we see that, you know, good number of about 80% of these projects fail or they suffer delays or scale back or never get started because, you know, the understanding of what is the business value of it is perhaps not clearly articulated instead it just becomes a technology modernization conversation without accompanying benefit. Yeah, got it. Okay, you guys recently announced some updates to your platform. Can you run us through the highlights, you know, what the customers get and how it relates to this conversation, modernizing application strategies? Yes, so we will be releasing our couch-based server 7.1 and that is what will be the sort of underneath platform for the couch-based Capella, which is our D-Bast. Both have exciting innovations that we would be putting out. Let me just run through a few things on the couch-based server 7.1 because there are some amazing capabilities we have introduced there. We are really excited about the opportunities this brings couch-based into play. First is we have a brand new storage engine that we put in there, which significantly reduces the cost of running couch-based. With this capability, we can actually consume a lot less memory and that is like a 10x improvement on this one. So from that standpoint, we are 10x more efficient in terms of resource consumption, the expensive memory oriented resource consumption. This now allows couch-based to sort of not just cater to those high performance, you know, hyperscale scenarios that we are known for, but also the more the classic disk oriented applications which are not that performance sensitive but they're more cost sensitive. So that's a huge step forward for couch-based because there are a lot more opportunities where sort of we become that much more cost efficient for enterprises to run. And this is something that many enterprises have asked for and we know many more use cases where we would be more relevant with that innovation. In this has been a sort of a long journey building storage engines is a very difficult endeavor and we took that on knowing that what we can achieve here will be a game changer for couch-based and in terms of how the consolidation of multiple things that you can do in our platform just got this sort of boost of being able to do a lot more with a lot less resources. In addition to that, we have done enhancements to our analytics service with the work that we have done there. It can sort of do a lot more availability of the analytic service which strengthens the analytics side of the product which now allows you to run analysis on JSON straight up without requiring the operational side of the database. So you can just simply do straight off analytic stuff because it can now give you the higher availability and disaster recovery that you would want if you're going to depend on these systems. With that we are done with some real good work with Tableau integration which makes it easy to visualize this. And one of the important capability we introduced here is the on the entire platform is what we call as user defined functions. This now allows us to write custom logic in JavaScript in the server couch-based server. This helps you write procedural logic in the middle of SQL queries which is a humongous capability that the classical systems process now with that we have closed the gap. If you know how to program to sort of classical rational systems pretty much you have one-to-one equivalence of that in couch-based. So if you come from the good relational world it will be very easy for you to understand how to program in this modern no SQL systems which both supports SQL as well as the classic asset transaction capabilities. And last we expanded the support to ARM processors and typically ARM processors at least save you a quarter of your budget because of it being that much more cost efficient in terms of its operational and power capabilities. So with that net-net couch-based server becomes a lot more cost efficient and at the same time it also in one's pulse who becomes that database server which can both handle your in-memory capabilities that speed and a hyperscale as well as the classical use cases of being disk-oriented classical relational database use cases. So that rounds out our offering. It's been a long journey for us to get here from being the high performance, low latency system to the classical database use cases. Yeah, I mean, that's great. You got memory optimization. You mentioned the ARM base. Now you're on that curve, which is great. Software companies love when you get cheaper, faster hardware, you're making it easy to speak the language of traditional stuff. So that's awesome. You and I, you mentioned Capella. You and I talked about at Couchbase Connects, Capella. You've been moving hard with your DBAS strategy. How's it going? And then beyond these announcements, what should we look for from Couchbase? You know, our fundamental mission is to make the developer experience that much more easier, that much remove all the frictions that has existed for developers to adopt Couchbase. And the Capella strategy is to leverage the cloud. So you have number one, the ease of development, just bring your browser, start to learn, develop even simple sample applications and deploy them from there, you can scale and you can have production level deployments, that whole journey of a developer, along with the ability to sort of have your metered billing and pay as you go pricing, so that it becomes easier for developers to sort of consume this and show the value of what they can build here. That is our sort of journey of bringing it closer to our developers and make it simpler for them to sort of get started and build the mission critical applications that they have trusted to build on Couchbase to become that much more simpler, faster and easier for them. So that's the journey. So that's the kind of announcements you will see coming out in Capella. And for that, this 7-1 server is the platform on which we are sort of adding those capabilities to make a Capella that much easier for developers to adopt. Outstanding, you've been busy and it looks like you got a lot ahead of you. All right, we're going to have to leave it there, Ravi. Up next, we bring on the customer perspective with Amdox. They've got a real world example of a modernization journey that they go through. They had to modernize legacy Oracle WebLogic infrastructure with a microservices architecture and of course, Couchbase. Keep it right there. You're watching theCUBE.