(upbeat music) >> Hello friends and welcome back to theCUBE's Live coverage of AWS re:Invent 2022 from the Venetian Expo in Vegas, baby. This show is absolutely packed. Lisa Martin with Dave Vellante, Dave this is day two, but really full day one of our wall to wall coverage on theCUBE. We've had great conversations the last half day this morning already, we've been talking with a lot of companies, a lot of Amazonians and some Amazonians that have left and gone on to interesting more things, which is what we're going to talk about next. >> Well, I'm excited about this segment because it's a really interesting space. You've got a search company who's gotten into observability and security and through our ETR partner our research, we do quarterly research and Elastic off the charts. Obviously they're the public company, so you can see how well they're doing. But the spending momentum on this platform is very, very strong and it has been consistently for quite some time. So really excited to learn more. >> The voice of the customer speaking loudly, from Elastic, its Chief Product Officer joins us, Ken Exner. Ken, welcome to the program. Hi, thank you, good to be here. >> Dave Vellante: Hey Ken. >> So a lot of us know about Elastic from Elastic Search but it's so much more than that these days. Talk about Elastic, what's going on now? What's the current product strategy? What's your vision? >> Yeah. So people know Elastic from the ELK Stack, you know Elastic Search, Logstash, Kibana. Very, very popular open source projects. They've been used by millions of developers for years and years. But one of the things that we started noticing over the years is that people were using it for all kinds of different use cases beyond just traditional search. So people started using Elastic Search to search through operational data, search through logs, search through all kinds of other types of data just to find different answers. And what we started realizing is the customers were taking us into different spaces. They took us into log analytics they started building log management solutions. And we said, cool, we can actually help these customers by providing solutions that already do this for them. So it took us into observability, they took us into security, and we started building solutions for security and observability based on what customers were starting to do with the platform. So customers can still use the platform for any number of different use cases for how do you get answers added data or they can use our pre-built packaged solutions for observability and security. >> So you were a longtime Amazonian. >> I was. I was. >> Talk a little bit about some of the things that you did there and what attracted you to Elastic? 'Cause it's only been a couple months, right? >> I've been here three months, I think three months as of yesterday. And I was at AWS for 16 years. So I was there a long, long time. I was there pretty much from the beginning. I was hired as one of the first product managers in AWS. Adam Selipsky hired me. And it was a great run. I had a ton of fun, I learned a lot. But you know, after 16 years I was kind of itching to do something new and it was going to take something special because I had a great gig and enjoyed the team at AWS. But I saw in Elastic sort of a great foundational technology they had a lot of momentum, a huge community behind it. I saw the business opportunity where they were going. I saw, you know the business opportunity of observability and security. These are massive industries with tons of business problems. Customers are excited about trying to get more answers out of data about their operational environment. And I saw, you know, that customers were struggling with their operating environments and things were becoming increasingly complicated. We used to talk in AWS about, you know how customers want to move from monolithic applications to monoliths, but one of the secrets was that things were increasingly complicated. Suddenly people had all these different microservices they had all these different managed services and their operating environment got complicated became this constellation of different systems, all emitting data. So companies like Elastic were helping people find answers in that data, find the problems with their systems so helping tame that complexity. So I saw that opportunity and I said I want to jump on that. Great foundational technology, good community and building solutions that actually helped solve real problems. >> Right. >> So, before you joined you probably looked back, and said, let think about the market, what's happening in the market space. What were the big trends that you saw that sort of informed your decision? >> Well, just sort of the mountain of data that was sort of emerging. Adam Selipsky in his talk this morning began by talking about how data is just multiplying constant. And I saw this, I saw how much data businesses were drowning in. Operational data, security data. You know, if you're trying to secure your business you have all these different endpoints you have all these different devices, you have different systems that you need to monitor all tons of data. And companies like Elastic were helping companies sort of manage that complexity, helping them find answers in that. So, when you're trying to track intruders or trying to track you know, malicious activity, there's a ton of different systems you need to pay attention to. And you know, there's a bunch of data. It's different devices, laptops and phone devices and stuff that you need to pay attention to. And you find correlations across that to figure out what is going on in your network, what is going on in your business. And that was exciting to me. This is a company sort of tackling one of the hardest problems which is helping you understand your operating environment, helping you understand and secure your business. >> So everybody's getting into observability. >> Yep. >> Right, it's a very crowded space right now. First of all, you know it's like overnight it just became the hottest thing going. VCs were throwing money at it. Why was that and how were you guys different? >> Well, we began by focusing on log analytics because that was the core of what we were doing. But customers started using it beyond log analytics and started using it for APM and started using it for performance data. And what we realized is that we could do all this for customers. So we ended up, sort of overnight over the course of three years building that a complete observe observability suite. So you can do APM, you can do profiling, you can do tracing, sort of distributed tracing, you can do synthetic monitoring everything you want to do, wheel user wondering. >> Metrics? >> All of it, metrics, all of it. And you can use the same system for this. So this was sort of a powerful concept, not only is it the best in leading log system, it also provides everything you need for complete observability. And because it's based on this open platform you can extend it to a number of different scenarios. So this is important, a lot of the different observability companies provide you something that's sort of packaged and as long as you're trying to do what it wants to support, it's great. But with Elastic, you have this flexible data architecture that you can use for anything. So companies use it to monitor assembly lines, they use it to monitor dish networks, for example use it to not only manage their fleet of servers they also use it to manage all their devices. So 25 million desktop devices. So, you know, observability systems like that that can do a number of different scenarios, I think that's a powerful thing. It's not just about how do you manage your servers how do you manage the things that are simple. It's how do you manage anything? How do you get observability into anything. >> Multiple use cases. >> Sorry, when you say complete, okay you talked about all the different APM, log analytics tracing, metrics, and also end-to-end. >> Ken Exner: End-to-end, yeah. >> Could you talk about that component of complete? >> So, if you're trying to find an issue like you have some metric that goes into alarm. You want to have a metric system that has alarming. Once that metric goes in alarm you're going to want to dig into your log. So you're going to want it to take you to the area of your logs that has that issue. Once you gets to there, you're going to want to find the trace ID that takes you to your traces and looks at sort of profiling, distributed tracing information. So a system that can do all of that end-to-end is a powerful solution. So it not only helps you track things end-to-end across the different signals that you're monitoring, but it actually helps you remediate more quickly. And the other thing that Elastic does that is unique is a lot of ML in this. So not only helping you find the information but surfacing things before you even know of them. So anomaly detection for example, helps you know about something before you even realize that there was an issue. So you should pay attention to this because it's anomalous. So a lot of systems help you find something if you know what to look for. But we're trying to help you not only find the things that you know to look for, but help you find the things that you didn't even think to know about. >> And it's fair to say one of your differentiators is you're open, open source. I mean, maybe talk about the ELK stack a little bit and how that plays. >> Yeah, well, so the great thing about this is we've extended that openness to both security and to observability. An example of this on the security side is all the detection rules that you use for looking for intrusion all the detection rules are open source and there's an entire community around this. So if you wanted to create a detection rule you can publish an open source, there's a bunch in GitHub you can benefit from what the community is doing as well. So in the world of security you want to be supported by the entire community, everyone looking for the same kind of issues. And there's an entire community around Elastic that is helping support these detection rules. So that approach, you know wanting to focus on community is differentiating for us. Not just, we got you covered as long you use things from us you can use it from the entire community. >> Well there implies the name Elastic. >> Yeah >> Talk a little bit about the influence that the customer has in the product roadmap and the direction. You've talked a little bit in the beginning about customers were leading us in different directions. It sounds very Amazonian in terms of following the customers where they go. >> It does, it actually does, it was one of the things that resonated for me personally is the journey that Elastic took to observability and security was customer led. So, we started looking at what customers were doing and realized that they were taking us into log analytics they were taking us into APM, they were taking us into these different solutions, and yeah, it is an Amazonian thing, so it resonated for me personally. And they're going to continue taking us in new places. Like we love seeing all the novel things that customers do with the platform and it's sort of one of the hallmarks of a great platform is you can have all kinds of novel things that, novel use cases for how people use your platform and we'll continue to see things and we may get taken into other solutions as well as we start seeing things emerge, like common patterns. But for now we're really excited about security and observability. >> So what do you see, so security's a big space, right? >> Yep. >> You see the optiv taxonomy and it makes your eyes bleed 'cause there's so many tools in there. Where do you fit in that taxonomy? How do you see and think about the security space and the opportunity for your customers? >> Yeah, so we began with logs in the security space as well. So SIEM, which is intrusion detection is based on aggregating a bunch of logs and helping you do threat hunting on those logs. So looking for patterns of malicious behavior or intrusion. So we started there and we did both detections as well as just ad hoc threat hunting. But then we started expanding into endpoint protection. So if we were going to have agents on all these different devices they were gathering logs, what if we also started providing remediation. So if you had malicious activity that was happening on one of the servers, don't just grab the information quarantine it, isolate it. So that took us into sort of endpoint protection or XDR. And then beyond that, we recently got into cloud security as well. So similar to observability, we started with logs but expanded to a full suite so that you can do everything. You can have both endpoint protection, you can have cloud security, all of it from one solution. >> Security is a very crowded market as well. What's your superpower? >> Ken Exner: What's our super power? >> Yeah. >> I think it, a lot of it is just the openness. It's the open platform, there's the community around it. People know and love the, the Elastic Search ELK stack and use it, we go into businesses all the time and they're familiar, their security engineers are using our product for searching through logs. So they're familiar with the product already and the community behind it. So they were excited about being able to use detection rules from other businesses and stay on top of that and be part of that community. The transparency of that is important to the customers. So if you're trying to be the most secure place, the most secure business, you want to basically invest in a community that's going to support that and not be alone in that. >> Right, absolutely, so much that rides on that. Favorite customer example that you think really articulates the value of Elastic, its openness, its transparency. >> Well, there's a customer Dish Media Dish Networks that's going to present here at re:Invent tomorrow at 1:45 at Mandalay Bay. I'm excited about their example because they use it to manage, I think it's 10 billion records a day across 25 million devices. So it illustrates the scale that we can support for managing observability for a company but also just sort of the unique use cases. We can use this for set top boxes for all their customers and they can track the performance that those customers are having. It's a unique case that a lot of vendors couldn't support but we can support because of the openness of the platform, the open data architecture that we have. So I think it illustrates the scale that we support, the elasticity, but also the openness of the data platform. >> Awesome and folks can catch that tomorrow, 1:45 PM at the Mandalay Bay. Last question for you, Ken, is you have a bumper sticker. >> Ken Exner: A bumper sticker? >> A bumper sticker you're going to put it on your fancy sexy new car and it's about elastic, what does it say? >> Helping you get answers out of data. So yeah. >> Love it, love it. Brilliant. >> Ken Exner: Thank you. >> Short and sweet. Ken, it's been a pleasure. >> It's been a pleasure being here, thank you. >> Thank you so much for sharing your journey with us as an Amazonian now into Elastic what Elastic is doing from a product perspective. We will keep our eyes peeled as Dave was saying. >> Ken Exner: Fantastic. >> The data show is really strong spending momentum so well done. >> Thank you very much, good to meet you. >> Our pleasure. For our guest and Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live enterprise and emerging tech coverage. (upbeat music)

>> Narrator: From around the globe it's theCUBE, with digital coverage of AWS reinvent 2020 special coverage sponsored by AWS global partner network. >> Hello, and welcome to theCUBE virtual with our special coverage of AWS reinvent 2020 with additional special coverage of APN partner experience. We are theCUBE virtual and I'm your host, Justin Warren. And today I'm joined by Angelos Kottas who is vice president of product marketing at elastic and he comes to us from San Francisco. Angelos , welcome to theCUBE. >> Thank you, Justin. A pleasure to join you. >> Great to have you here. Now. I've been a big fan of elastic for a while have used your products in a variety of circumstances? You're big partners of AWS and have seen quite a bit of change over the last couple of years. We were talking just before we came on air. Maybe you could talk us through what elastic is doing with AWS and a little bit about those changes that you've seen over the last >> Absolutely one period. >> Sounds good Justin. So first of all many people know elastic as the makers of elastic search. One of the most popular open source of search engines and along with elastic search we have Kibana and beats and Logstash and many people know us as the Elk Stack, right? And so clearly we have roots in the open source community and people have used us for custom applications for years and years. One of the key changes over the last few years is that we've realized that many customers were doing some of the same things with elastic. So we said, what if we really focus on end to end experiences for our three core use cases? And so we chose three use cases and built solutions around them. What is enterprise search, right? Which is how do you find information on your website in your application or in your workspace? The second is observability. So think about software development software in every industry. What about dev ops? What about performance? What about consistency and last but not least, especially you know, with some of the current transitions in digital transformation, think about security. Think about your network security, your endpoint security and how you have visibility across your entire IT ecosystem. So we've chosen those three solution areas and put significant engineering into building out that experience. How quickly can we deliver value, how pre-built can the configuration be the integrations be, the workflow, the reporting and the dashboards around those use cases. The last piece, which is very relevant for reinvent is the transition to cloud, right? So we still offer a downloadable software and many of our customers and users download the elastic stack and deploy it on-prem and hybrid cloud environments. But one of the fastest growing deployment models is in the public cloud. And of course, elastic cloud on AWS is one of our major routes to market, happy to meet many of our customers where they are, which is on AWS. >> Oh it's great to be able to have that choice I think that people can download the software try and get it, get comfortable with it but then people often find that actually running software yourself, there's quite a lot of work involved in doing that. I know that I, I've experienced that myself. Just little things like maintenance and so on. So it sounds like you're actually taking care of a lot of that for customers if they move to the cloud service. But is there anything else special about the cloud service that customers might not be that aware of? >> Well, I mean, choice is a big part of it and so it's not just do I choose cloud it's wearing cloud. So we've actually, we now run elastic cloud in over 40 regions around the world. So we can be close to you in terms of latency, and in terms of performance, in terms of data sovereignty we can be local to your environment. The other aspect it's not just how we simplify deploying elastic. You know, clearly we architect it we install it, deploy and upgraded for you. But also we have focused quite a bit on integrating cloud data sources. So with AWS, as an example, we look at all of the applications and data sources that you host on AWS. And we think about how do we get those data streams how do we get that data directly integrated into elastic. One final piece, actually which I forget sometimes it's not the technical side. It's the business side is the commercial integration, right? So we are, you know, very happy to to be listed on the AWS marketplace. We've made it easy for you to find, deploy and actually build through your AWS commercial agreements via the marketplace integration. >> Right, so easy to get started and to start using it and search is certainly something that elastic is famous for. But you mentioned observability there, a bit of a question I have around observability is, is it that just a fancy way of saying monitoring? There seems to be this, this buzzword around the place. So what do you mean when you say observability? >> So one of the key foundational principles of the elastic observability solution is that, you know you want a unified data database a unified place to store all that data. So it is stretching across logs metrics, application traces it's bringing together a common platform that lets you look at different aspects of observability. So whether you're doing end to end application traces or whether you're just collecting infrastructure logs and looking at performance metrics it's kind of across the board, even looking at things in our most recent release that just came out last week, you know expanding on user experience, monitoring and synthetics. So you can optimize web interactions and web experiences, for example. >> Right. Okay. So there's a bunch of different types of data that are involved there. I know traditionally people would silo those off into a specific customized thing just for that particular type of workload. What is it about elastic that means that you can put all of these in one place? >> Yeah. You know, one of early catchphrases for what does elastic do? What do we focus on? The value we deliver is speed, scale and relevance. And so one of the things that is famous about the elastic way of doing things is the way in which we index data on ingest and so that you can get search queries that return within milliseconds and so that performance characteristics. A second one is scale. And this is actually really key, not just for observability but right next to observability, you get security as well. We like to say, if you're going to observe you might as well protect as well. So when you expand to that universe you have not just hundreds of devices you might have thousands or tens of thousands of devices that you are ingesting information whether it's operational data, whether it's security data. So scale becomes extremely significant. How can you scale horizontally and vertically and maintain that performance even when you are in a fortune 500 scale infrastructure The last piece is relevance. And so, you know that data it's not just about knowing what to look for. It's about using things like machine learning and anomaly detection to uncover unusual patterns of behavior and proactively alerting and making that visible through notifications and through alerts that can actually integrate not just with your elastic operations but actually with third party software. Maybe you want to trigger a service now ticket or a, you know, a Slack integration and all of that is part of the elastic platform as well. >> Right? Okay. So by putting everything kind of in one place that is around what you're talking about. So we have enterprise search and then to be able to find things we're collecting all of the data that we need to find things. And then you touched on security at the beginning and we're starting to talk around security there. So I'm keen to move on to that >> (chuckles) >> By looking at all of these, these different, these signals we can hopefully then manage some of security which I know is very much front of mind for everyone over the last year. Cyber security has very much come to the forefront of everyone's thinking. >> Absolutely. And you know, we've been on the network side of security for some time. So we've had our SIM solution, you know security information event monitoring, but we made a very strategic acquisition a little over a year ago. We saw that a critical piece of visibility is also the end point. And so we partnered with end game and eventually we acquired end game to create end to end visibility on that security. So it is being able to connect, you know the path of data from your servers and network devices all the way to the end points. And an example of the power of this unified architecture is the new elastication that we introduced in beta a couple of months ago. We said, what if we had a single deployment that both does endpoint protection and does malware scanning of your endpoint devices while also ingesting data into your observability systems. And so that's kind of the power of the platform the ability to use common infrastructure common integrations, so that every use case you adopt on top of elastic, it sort of multiplies the value you're getting from using elastic as an infrastructure player. >> Alright that's a good combining a couple of different things into the one tool that you can use. I know sys who I'd spoken to are quite concerned about the proliferation of tools that they have in their environment, it seems that they've bought lots of different things but a lot of them are kind of sitting in a drawer, not really being used. And partly, it's just, we we have so many different ways of dealing with these issues. None of it's really flushed out or sorry has been fully fleshed out that we definitely know this is the one true way to solve this. So what are you hearing from customers as they start to use these security functions? What are they telling you about the way that they're managing security in their environments? >> Well, you know, we think about a few different personas in the security market, right? We think about threat hunters, for example who are looking to identify threats, we're looking at the operations team that do the cleanup that do the you know, the resolution of security threats. And we also, so there's a, you know, there's two competing terms in the security market. We have security operations in the observability world. We have dev ops, right? And, and developer, you know, the continue of developer and deployment into a dev ops role. And so we're starting to see this concept of DevSecOps, right? What if there is a unified set it's not all things to all people and that's an important thing, right? We're not trying to be, your single security vendor for all IT security needs, but instead we're saying, what if you had a security operations analyst, a thrent Hunter an executive, a CSO who's looking for, you know an overall level of threat or compliance to policy and you can bring those experiences together through the elastic security solution. >> Right? So it sounds like you you're trying to allow people to work in the way that they need to providing them the tools that suit their particular circumstance. >> That's right. That's right. I mean, in terms of how do you define success? You look at metrics like meantime to resolution, you know can we reduce the meantime to resolution or you look at law collection and how much more efficiently can you collect logs? You look at asset monitoring and what percentage of your IT infrastructure you actually have unified visibility into, you know we have one great cloud customer OALEKS group. They are a popular online marketplace, you know and they quoted to us that they had a 1900% increase in law collection, right. In terms of scope of what they are collecting logs on they reduce that MTTR by 30% for security incidents so dramatically streamlined and shortened the exposure. And then they increased asset monitoring by 35% across cloud, as well as on-prem. And I think that's the other piece is that, you know whether you deploy your security in the cloud or on-prem you are looking to secure your hybrid environment. And so being able to take data feeds from your SAS partners from your infrastructure running on AWS as well as from those endpoint devices. >> Well, it sounds like there's plenty of scope of interesting things for people to come and have a look at it, at elastic. So, Angelos, thank you so much for joining us here, please. Thank you to my guests Angelos Kottas, vice president of product marketing at elastic. You've been watching theCUBE virtual and our coverage of AWS reinvent 2020 with special coverage of APN partner experience. Make sure you check out all our coverage on your desktop laptop or on your phone, wherever you are. I've been your host, Justin Warren. And I look forward to seeing you again soon. (upbeat music)

>> Good morning, everyone. My name is Sudip Datta. I head up product management for Infrastructure Management and Analytics at CA Technologies. Today I am going to talk about the key pillars for modern analytics and monitoring for hybrid cloud. So before we get started, let's set the context. Let's take a stock of where we are today. Today in terms of digital business, software is driving business. Software is the backbone, is the driving force for most of the business services. Whether you are a financial institution or a hospitality service or a health care service or even a restaurant service pizza, you are front-ended by software. And therefore the user experience is of paramount importance. Just to give you some factoids. Eighty-three percent of U.S. consumers say that the brand that, the frontal software portal is more important than the product itself. And the companies are reciprocating by putting a lot of emphasis on user experience, as you see in the second factoid. The third factoid, it's even more interesting that 53% of the users of a mobile app actually abandon the app if the app doesn't load within a specified time. So we all understand now the importance of user experience in today's business. So what's happening to the infrastructure underneath that's hosting these applications? The infrastructure itself is evolving, right? How? First of all, as we all know there is a huge movement, a huge shift towards cloud. Customers are adopting cloud for reasons of economy, agility and efficiency. And whether you are running on cloud or on prem, the architecture itself is getting more and more dynamic. On the server side we hear about server-less computing. More and more enterprises are adopting containers, could be Dockers or other containers. And on the networking side we see an adoption of software-defined networking. The logical overlay on top of the physical underlay is abstracting the network. While we see a huge shift, a movement towards cloud, it is also true that customers are also retaining some of their assets on prem, and that's why we talk about hybrid cloud. Hybrid cloud is a reality, and it's going to be a reality for the foreseeable future. Take for example a bank that has its systems of engagement on public cloud, and systems of records on prem deeply nested within their DNC. So the transaction, the end-to-end transaction has to traverse multiple clouds. Similarly we talk to customers who run their production tier one application on prem, while tier two and tier three desktop applications run on public cloud. So that's the reality. Multi-cloud dynamic environment is a reality of today. While that's a reality, they pose a serious challenge for IT operations. What are the challenges? Because of multiple clouds, because of assets spanning multiple data centers, multiple clouds, there are blind spots getting created. IT ops is often blindsided on things that are happening on the other side of the firewall. And as a result what's happening is they're late to react, and often they react to problems much later than their customers find it, and that's an embarrassment. The other thing that's happening is because of the dynamic nature of the cloud, things are ephemeral, things are dynamic, things come and go, assets come and go, IT ops is often in the business of keeping pace with these changes. They are reacting to these changes. They are trying to keep pace with these changes, and silo'd tools are not the way to go. They are trying to keep up with these changes, but they are failing in doing so. And as a result we see poor user experience, low productivity, capacity problems and delayed time to market. Now what's the solution? What is the solution to all these problems? So what we are recommending is a four-pronged solution, what we represent as four pillars. The first pillar is about dynamic policy-based configuration and discovery. The second one is unification of the monitoring and analytics. The third one is contextual intelligence, and the fourth one is integration and collaboration. Let's go through them one by one. First of all, in terms of dynamic policy-based configuration, why is it important? I was talking to a VP of IT last week, and he commented that the time to deploy the monitoring for an application is longer than the time to deploy the application itself, and that's a shame. That's a real shame because in today's world application needs to be monitored straight out of the box. This is compounded by the fact that once you deploy the application, the application today is dynamic, as I said, the cloud assets are dynamic. The topology changes, and monitoring tools need to keep pace with that changing topology. So we need automated discovery. We need API driven discovery, and we need policy-based monitoring for large scale standardization. And last but not the least, the policies need to be based on dynamic baselines. The age, the era of static thresholds is long over because static thresholds lead to false alerts, resulting in higher opics for IT, and IT personnel absolutely, absolutely want to move away from it. Unified monitoring and analytics. This morning I stumbled upon a Lincoln white paper which said 20 tools you need for your hybrid monitoring, and I was absolutely dumbfounded. Twenty tools? I mean, that's a conversation non-starter. So how do we rationalize the tools, minimize the silos, and bring them under single pane of glass, or at least minimal panes for glass for monitoring? So IT admins can have a coherent view of servers, storage, network and applications through a single pane of glass? And why is that important? It's important because it results in lesser blame game. Because of silo'd tools what happens is admins are often fighting with each other, blaming each other. Server admins think that it's a storage problem. The storage admin thinks it's a database problem, and they are pointing to each other, right? So the tools, the management tools should be a point of collaboration, not a point of contention. Talking about blame game, one area that often gets ignored is the area of fault management and monitoring. Why is it important? And I will give a specific example. Let's say you have 100 VMs, and all those VMs become unreachable as a result of router being down. The root cause of the problem therefore are not the VMs, but the router. So instead of generating 101 alarms, the management tool needs to be smart enough to generate one single alarm. And that's why fault management and root cause analysis is of paramount importance. It suppresses unnecessary noise and results in lesser blaming. Contextual intelligence. Now when we talk about the cloud administrator, the cloud admin, the cloud admin in the past were living in the cocoon of their hybrid infrastructure. They were managing the hybrid infrastructure, but in today's world to have an end-to-end visibility of the digital chain, they need to integrate with application performance management tools, APM, as well as what lies underneath, which is the network, so that they have an end-to-end visibility of what's happening in the whole digital chain. But that's not all. They also need what we call is the context of the application. I will give you a specific example. For example, if the server runs out of memory when a lot of end users log into the system, or run out of capacity when a particular marketing promotion is running, then the context really is the business that leads to a saturation in IT. So what you need is to capture all the data, whether they come from logs, whether they come from alarms, capacity events as well as business events, into a single analytics platform and perform analytics on top of it. And then augment it with machine learning and pattern recognition capabilities so that it will not only perform root cause analysis for what happened in the past, but you're also able to anticipate, predict and prevent future problems. The fourth pillar is collaboration and integration. IT ops in today's world doesn't and shouldn't run in a silo. IT ops need to interact with dev ops. Within dev ops developers need to interact with QA. Storage admins need to collaborate with server admins, database admins and various other admins. So the tools need to encourage and provide a platform for collaboration. Similarly IT tools, IT management tools should not run standalone. They need to integrate with other tools. For example, if you want monitoring straight out of the box, the monitoring needs to integrate with provisioning processes. The monitoring downstream needs to integrate with ticketing systems. So integration with other tools, whether third party or custom developed, whatever it is, it's very, very important. Having said that, having laid what the solution should be, what the prescription should be, how is CA Technologies gearing up for it? In CA we have the industry's most comprehensive, the richest portfolio of infrastructure management tools, which is capable of managing all forms of infrastructure, traditional, private cloud, public cloud. Just to give you an example, in private cloud we support the traditional VMs as well as hyper converged infrastructure like Nutanix. We support Docker and other forms of containers. In public cloud we support the monitoring of infrastructure as a service, platform as a service, software as a service. We support all the popular clouds, AWS, Azure, Office 365 on Azure, as well as Salesforce.com. In terms of network, out net ops tools manage the latest and greatest SDN and SD-WAN, the VMware SDN, the open stack SDN, in terms of SD-WAN Cisco, Viptella. If you are a hybrid cloud customer, then you are no longer blindsided on things that are happening on the cloud side because we integrate with tools like Ixia. And once we monitor all these tools, we provide value on top of it. First of all, we monitor not only performance, but also packet, flow, all the net ops attributes. Then on top of that we provide predictive insights and learning. And because of our presence in the application performance management space, we integrate with APM to provide application to infrastructure correlation. Finally our monitoring is integrally linked with our operational intelligence platform. So in CA we have an operational intelligence platform built around CA Jarvis technology, which is based on open source technology, Elastic Logstash and Kibana, supplemented by Hadoop and Spark. And what we are doing is we are ingesting data from our monitoring tools into this data lake to provide value added insights and intelligence. When we talk about big data we talk about the three Vs, the variety, the volume and the velocity of data. But there is a fourth V that we often ignore. That's the veracity of the data, the truthfulness of data. CA being a leader in monitoring space, we have been in the business of collecting and monitoring data for ages, and what we are doing is we are ingesting these data into the platform and provided value added analytics on top of it. If you can read the slide, it's also an open framework we have the APIs from for ingesting data from third-party sources as well. For example, if you have your business data, your business sentiment data, and if you want to correlate that with IT metrics, how your IT is keeping up with your business cycles, you can do that as well. Now some of the applications that we are building, and this product is in beta as you see, are correlation between the various events, IT events and business events, network events and server events. Contextual log analytics. The operative word is contextual. There are a plethora of tools in the market that perform log analytics, but log analytics in the context of a problem when you really need it is of paramount importance. Predictive capacity analytics. Again, capacity analytics is not only about trending, right? It's about what if analysis. What will happen to your infrastructure? Or can your infrastructure sustain the pressure if your business grows by 2X, for example? That kind of what if analysis we should be able to do. And finally machine learning, we are working on it. Out of box machine learning algorithm to make sure that problems are not only corrected after the fact, but we can predict problems. We can prevent the problems in future. So for those who may be listening to this might be wondering where do we start? If you are already a CA customer, you are familiar with CA tools, but if you're not, what's the starting point? So I would recommend the starting point is CA Unified Infrastructure Manager, which is the market leading tool for hybrid cloud management. And it's not a hollow claim that we are making, right? It has been testified, it has been blessed by customers and analysts alike. And you can see it was voted the cloud monitoring software of the year 2016 by a third party. And here are some of the customer experiences. NMSP, they were able to achieve 15% productivity improvement as a result of adopting UIM. A healthcare provider, their meantime to repair, MTTR, went down by 40% as a result of UIM. And a telecom provider, they had a faster adoption to cloud as a result of UIM, the reason being UIM gave them for the first time a single pane of glass to manage their on prem and cloud environments, which has been a detriment for them for adopting cloud. And once they were able to achieve that, they were able to switch onto cloud much, much faster. Finally, the infrastructure management capabilities that I talked about is now being delivered as a turnkey solution, as a SAS solution, which we call digital experience insights. And I strongly, strongly encourage you to try UIM via CA digital experience insights, and here is the URL. You can go and sign up for the trial. With that, thank you.