 Hi, from Orlando, Florida, it's theCUBE, covering Microsoft Ignite, brought to you by Cohesity, and theCUBE's ecosystem partners. Welcome back to theCUBE's live coverage of Microsoft Ignite here in Orlando, Florida. I'm your host, Rebecca Knight, along with my co-host, Stu Miniman. We're joined by Andrew Liu. He is the Senior Product Manager at Azure Cosmos DB. Thanks so much for coming on the show, Andrew. Thank you for hosting. You're a first-timer, so this will be a lot of fun. So, talk to me a little bit. Azure Cosmos DB is a database for building blazing fast planet-scale applications. Can you tell our viewers a little bit about what you do and about the history of Azure Cosmos? Sure. So Azure Cosmos DB started with about eight years ago, where we were also outgrowing a lot of our own database needs with what we had previously built. And a lot of the challenges that we had was really around partitioning, replication, and resource governance. So I'll talk a little bit about each one. Partitioning is really about solving the problem of scale, right? I have so much data, doesn't fit on a single machine, and I have so many requests per second, also doesn't, can't be served out of a single machine. So how do I go and build a system, a database that can elastically scale over a cluster of machines, so I don't have to manually shard and as a user have to shard a database across many, many instances. This way I really want to be able to scale just seamlessly. The velocity problem is we also wanted to build something that can respond in a very fast manner, in terms of latency. So it's great and all that, we can serve lots of requests per second, but what is the response time of each one of those requests? And the resource governance was there to really actually build this as a cloud-native database, in which we wanted to exploit the properties of our cloud, we wanted to use economies of scale that we can have basically data centers built all around the world and build this as a truly multi-tenant service. And by doing so we can also for the total cost of ownership for us, as well as guarantee predictable performance for the tenants. Now we did this for initially our first party tenants at Microsoft, where we've made a bet on everything from our Microsoft Live platform to Office to Adger itself, is built on Adger Cosmos DB. And about four years ago we found that, hey, this is not really just a Microsoft problem that we're solving, but it's an everybody problem, it's become universal. And so we've launched it out to the open. Yeah, that's a great point and I want you to help unpack that for us a little bit, because we've been saying on theCUBE for many years, distributed architectures are some of the toughest challenges of our time. But if I'm a Facebook or a Google or a Microsoft, I understand some of the challenges and I understand why I need it. But when you talk about scale, well, scale means a lot of different things to a lot of different people. So how does Cosmos, what does that mean to your users and users? Why do they need this? Haven't they just built some microservices architecture and they'll just leverage what's in Azure and things like that. How does this global scale impact the typical user? So I'm actually seeing this come in different types of patterns for different types of industries. So for example, in manufacturing, we're commonly seeing Cosmos DB used really for that scalability, for the right scalability and having many, many concurrent writes per second. Typically this is done in an IoT telemetry or an IoT device registry case. So let's use one of our customers, for example, Toyota. Each year they're shipping millions of vehicles on the road and they're building a big connected car platform. The connected car platform allows to do things like whenever an airbag gets deployed, they can go and make sure and call the driver, hey, I saw the airbag was deployed, are you okay? And if the user doesn't pick up their phone, immediately notify emergency services. But the challenge here is if each year I'm shipping millions of vehicles on the road and each of them has a heartbeat every second, I'm dealing with millions of writes per second and I need a database that can scale to that. In contrast in retail, I'm actually seeing very different use cases. They're using more of the replication side of our stack where they have a global user base and they're trying to expand an e-commerce shop. So for example, ASOS is a big fashion retailer. They ship to 200 different countries globally and they want to make sure that they can deliver real-time experiences like real-time personalization and based off of who the user is, recommend a set of products that is tailored to that user. Well now what I need is a data set that can expand to my shoppers across 200 countries around the globe and deliver that with very, very low latency so that my web experience is also very robust. So what they use is our global distribution and our multi-ray mastering technology where we can actually have a database presence similar to like what a CDN does for static content, we're doing for a dynamic evolving content. So in a database, your workload typically, your data set is evolving and you want to be able to run queries with consistency over that as opposed to in a CDN, you're typically serving static assets. Well here we can actually support those dynamic content and then build these low-latency experiences to users all around the globe. The other area we see a lot of usage is in ISVs for mission-critical workloads and the replication actually gives us two awesome properties, right? One is the low latency by shipping data closer to where the user is, but the other property you get is a lot of redundancy and so we actually also offer industry-leading SLAs where we guarantee five nines of availability and the way we're able to do so is with a highly redundant architecture, you don't care if, let's say, a machine were to bomb out at any given time because we have multiple redundant copies in different parts of the globe, you're guaranteed that your workload is always online. So my question for you is when you have these, you just described some really, really interesting customer use cases and manufacturing and retail, do you then create products and services for each of these industries or do you say, hey, other retail customers, we've noticed this really works for this customer over here. How do you go out to the community with what you're selling? Got it. So we actually found that this can be a challenging space for some of our customers today because we have so many products. The way we kind of view it is we want to have a portfolio so that you can always choose the right tool for the right job and I think a lot of how Microsoft has evolved as a business actually is around this. Previously we would sell a hammer and we tell you, don't worry, everything's a nail. Even if it looks like a screw, let's just pretend it's a nail and whack it down. But today we built this big, vast toolbox and you can think of Cosmos DB as just one of many tools in our vast toolbox. So if you have a screw, maybe pick up a screwdriver and screw that in. And the way Azure works is then if we have a very comprehensive toolbox, depending on what precise scenario you have, you can kind of mix and match the tools that fit your problem. So think of them as like individual Lego blocks and whether you're building like a Death Star or an X-Wing, you can go and assemble the right pieces for your application. Andrew, some news at the show around Cosmos DB. Share with us what the updates are. Oh, sure. So we're really excited to launch a few new features. The highlights are Multimaster and Cassandra API. So Multimaster really exploits the replicated nature of our database. Before Multimaster, what we would do is we would allow you to have a globally distributed database in which you can have right requests go to a single region and reads being served out of any of these other locations. With Multimaster, we've actually made it so that each of those replicas we've deployed around the globe can also accept right requests. What that translates to from a user point of view is number one, your right requests are a lot faster. They're super low latency, single digit millisecond latency in fact, no matter where the user is around the globe. And number two, you also get much higher right availability. So even if let's say we were having a natural disaster, we had a nasty hurricane, as you know, passed through on the East Coast last week. But with a globally distributed database, the nice thing is even if you have, let's say, power disruption in one region of the world, it doesn't matter because you can then just fail over and talk to another data center where you have a live replica already located. So we just came out with Multimaster. The short summary is low latency rights as well as high available rights. The other feature that we launched is Cassandra API. And as you know, this is a multi-model, multi-API database. What that means is what we're trying to do is also meet our users where they are, they are as opposed to pushing proprietary software on them. And we take the whole concept of vendor lock-in very, very seriously, which is why we make such a big bet on the open source ecosystem. If you already have, let's say a MongoDB application or a Cassandra application, but you'd really love to be able to take advantage of some of the novel properties that we've built with building a fully managed Multimaster database. Well, what we've done is we've implemented this as a wire level protocol on the server side so you can take an existing application, not change a single line of code and point it to Cosmos DB as a backend and then take advantage of Cosmos DB as your database. Yeah, one of the interesting things, if you look at the kind of changing face of database is it's how users are being able to leverage their data, you talk about everything from, I think Cassandra back and some of the big data discussions today, everything's AI, which I know is near and dear to Microsoft's heart, Satya Nadellan talking about, how do you think of the role of data in this solution set? Sorry, can you say that one more time? So how customers think about leveraging data, how things like Cosmos allow them to really extract the value out of data, not just be some database that kind of stuck in the backend somewhere. Yeah, yeah, I mean, a lot of it is the new novel experiences people are building. So for example, like the connected car platform, I'm seeing people actually build this and take advantage of new novel territories that a traditional automobile manufacturer used to not do. Not only are they building experiences around how do they provide value to their own users like the airbag scenario, but they're also using this as a way of building value for their business and how to make sure that, hey, when next time you're up for an oil change, that they can send a helpful reminder and say, hey, I noticed your different oil change in terms of mileage. Why don't I just go set up an appointment just up for you, as well as other experiences for things like when they want to do fleet management and do partnerships with either ride-sharing companies like Uber and Lyft or rental car companies like Avis, Hertz, et cetera. I've also seen people take advantage of taking kind of new novel experiences through databases, through AI and machine learning. So for example, the product recommendations. This was something that historically, when I wanted to do recommendations a decade ago, maybe I have some big beefy data lake running somewhere in the back end. Might take a week to munch through that data, but that's okay, a week later. Once I'm ready, I'll send out some mail, maybe some email to you. But today, when I want to actually show live right when the user is browsing my website, my website has to load fast, right? If my goal is to increase conversions on sales, having a slow running website is the fastest way for my user to click the back button. But if I want to build real-time personalization and want to generate, let's say, a recommendation within 200 millisecond latency, well, now that I have databases that can guarantee me single-digit millisecond latency, it gives me ample time to actually improve the business logic for those recommendations. I want to ask you a question about culture, because you are based at the mothership in Redmond, Washington. So we heard Satya Nadella on the main stage today talk about tech-intensiveness and this idea, tech-intensity, sorry, this idea that we need to not only be adopting technology, but also building the latest and greatest. I'm curious about how that translates at Microsoft's campus and sort of how this idea infuses how you work with your colleagues and then also how you work with your customers and partners. I think some of the biggest positive changes I've seen over the last decade has been how much more of a customer focus we have today than ever. And I think a lot of things have led to that. One is just the ability to ship much faster. As we move to cloud services, we're no longer in these big box product release cycles of building a product and waiting like one or two years to ship it to our users. But now we can actually get some real-time feedback. So as we go and ship and deploy software, we actually deploy even on a weekly cadence over here. What that allows us to do is actually experiment a lot more and get real-time feedback. So if we have an idea, and rather than having to go through a long, lengthy vetting process, spending years building and hoping that it really pays off, what we can do is we can just go talk to our users and say, hey, you know, we have an idea for a future. We'd love to get your feedback. Or a lot of times, honestly, our customers actually come to us. We're so tightly engaged these days that when users even come to us and say, like, hey, what do you think about this idea? It would really add a lot of value to my scenario. We go and try to root cause that, really get an idea of what exactly that they need. But then we can turn that around and blazing fast time. And I think a lot of the shift to cloud services and being able to avoid the overhead of, well, we got to wait for this ship train and then wait for the right operation personnel to go and deploy the updates now that we can control our own destiny and just ship on a very, very fast cadence. We're closer to our users and we experiment a lot more. And I think it's a beautiful thing. Great, well, Andrew, thank you so much for coming on theCUBE. It was fun talking to you. Well, yeah, thank you for hosting. I'm Rebecca Knight. For Stu Miniman, we will have more from theCUBE's live coverage of Microsoft Ignite coming up just after this.