>> Well, thank you, Gary. Well, you know, reasonable people could debate when the so-called big data era started. But for me it was in the fall of 2010 when I was sleepwalking through this conference in Dallas. And the conference was focused on data being a liability. And the whole conversation was about, how do you mitigate the risks of things like work in process and smoking-gun emails. I got a call from my business partner, John Fard, he said to me, "get to New York and come and see the future of data. We're doing theCUBE at Hadoop World tomorrow." I subsequently I canceled about a dozen meetings that I had scheduled for the week. And with only one exception, every one of the folks I was scheduled to meet said, "what's a Hadoop?" Well, I flew through an ice storm across country. I got to the New York Hilton around 3:00 AM, and I met John in the Dark Bar. If any of you remember that little facility. And I caught a little shut eye. And then the next day I met some of the most interesting people in tech during that time. They were thinking a lot differently than we were used to. They looked at data through a prism of value. And they were finding new ways to do things like deal with fraud, they were building out social networks, they were finding novel marketing vectors and identifying new investment strategies. The other thing they were doing is, they were taking these little tiny bits of code and bring it to really large sets of data. And they were doing things that I hadn't really heard of like no schema-on-write. And they were transforming their organizations by looking at data not as a liability, but as a monetization opportunity. And that opened my eyes and theCUBE, like a lot of others bet its business on data. Now over the past decade, customers have built up infrastructure and have been accommodating a lot of different use cases. Things like offloading ETL, data protection, mining data, analyzing data, visualizing. And as you know, you no doubt realize this was at a time when the cloud was, you know, really kind of nascent. And it was really about startups and experimentation. But today, we've evolved from the wild west of 2010, and many of these customers they're leveraging the cloud for of course, ease of use and flexibility it brings, but also they're finding out it brings complexity and risk. I want to tell you a quick story. Recently it was interviewing a CIO in theCUBE and he said to me, "if you just shove all your workloads into the cloud, you might get some benefit, but you're also going to miss the forest to the trees. You have to change your operating model and expand your mind as to what is cloud and create a cloud light experience that spans your on premises, workloads, multiple public clouds, and even the edge. And you have to re-imagine your business and the possibilities that this new architecture this new platform can bring." So we're going to talk about some of this today in a little bit more detail and specifically how we can better navigate the data storm. And what's the role of hybrid cloud. I'm really excited to have two great guests. Manish Dasaur is the managing director in the North America lead for analytics and artificial intelligence at Accenture. Anupam Singh is the chief customer officer for Cloudera. Gentlemen, welcome to theCUBE, great to see you. >> Hi Dave good to see you again. >> All right, guys, Anupam and Manish, you heard my little monologue upfront Anupam we'll start with you. What would you? Anything you'd add, amend, emphasize? You know, share a quick story. >> Yeah, Dave thank you for that introduction. It takes me back to the days when I was an article employee and went to this 14 people meet up. Just a couple of pizza talking about this thing called Hadoop. And I'm just amazed to see that today we are now at 2000 customers, who are using petabytes of data to make extremely critical decisions. Reminds me of the fact that this week, a lot of our customers are busy thinking about elections and what effect it would have on their data pipeline. Will it be more data? Will it be more stressful? So, totally agree with you. And also agree that cloud, is almost still in early days in times of the culture of IT on how to use the cloud. And I'm sure we'll talk about that today in greater detail. >> Yeah most definitely Manish I wonder if we could get your perspective on this. I mean, back when Anupam was at Oracle you'd shove a bunch of, you know, data, maybe you could attach a big honking disc drive, you'd buy some Oracle licenses, you know, it was a Unix box. Everything went into this, you know, this God box and then things changed quite dramatically, which was awesome, but also complex. And you guys have been there from the beginning. What's your perspective on all this? >> Yeah, it's been fascinating just to watch the market and the technology evolve. And I think the urgency to innovate is really just getting started. We're seeing companies drive growth from 20% in cloud today, to 80% cloud in the next few years. And I think the emergence of capabilities like hybrid cloud, we really get upfront a lot of flexibility for companies who need the ability to keep some data in a private setting, but be able to share the rest of the data in a public setting. I think we're just starting to scratch the surface of it. >> So let's talk a little bit about what is a hybrid cloud Anupam I wonder if you could take this one let's start with you and then Manish we come back to you and to get the customer perspective as well. I mean, it is a lot of things to a lot of people, but what is it? Why do we need it? And you know, what's the value? >> Yeah, I could speak poetic about Kubernetes and containers et cetera. But given that, you know, we talk to customers a lot, all three of us from the customer's perspective, hybrid cloud is a lot about collaboration and ease of procurement. A lot of our customers, whether they're in healthcare, banking or telco, are being asked to make the data available to regulatory authority, to subsidiaries outside of their geography. When you need that data to be available in other settings, taking a from on-prem and making it available in public cloud, enables extreme collaboration, extreme shared data experience if you will, inside the company. So we think about hybrid like that. >> Manish anything you'd add? How are your customers thinking about it? >> I mean, in a very simple way, it's a structure that where we are allowing mixed computing storage and service environments that's made of on-prem structures, private cloud structures, and public cloud structures. We're often calling it multicloud or mixcloud. And I think the really big advantage is, this model of cloud computing is enabling our clients to gain the benefits of public cloud setting, while maintaining your own private cloud for sensitive and mission critical and highly regulated computing services. That's also allowing our clients and organizations to leverage the pay-as-you-go model, which is really quite impressive and attractive to them because then they can scale their investments accordingly. Clients can combine one or more public cloud providers together in a private cloud, multicloud platform. The cloud can operate independently of each other, communicate over an encrypted connection. This dynamic solution offers a lot of flexibility and scalability which I think is really important to our clients. >> So Manish I wonder if we would stay there. How do they, how do your customers decide? How do you help them decide, you know, what the right mix is? What the equilibrium is? How much should it be in on-prem? How much should be in public or across clouds? Or, you know, eventually, well the edge will I guess decide for us. But, how do you go through, what are the decision points there? >> Yeah, I think that's a great question Dave. I would say there's several factors to consider when developing a cloud strategy that's the right strategy for you. Some of the factors that come to my mind when contemplating it, one would be security. Are there data sets that are highly sensitive that you don't want leaving the premise, versus data sets that need to be in a more shareable solution. Another factor I'd consider is speed and flexibility. Is there a need to stand up and stand down capabilities based on the seasonality of the business or some short-term demands? Is there a need to add and remove scale from the infrastructure and that quick pivot and that quick reaction is another factor they should consider. The third one I'd probably put out there is cost. Large data sets and large computing capacities often much more scalable and cost effective than a cloud infrastructure so there's lots of advantages to think through there. And maybe lastly I'd share is the native services. A lot of the cloud providers enable a set of native services for ingestion, for processing, of modeling, for machine learning, that organizations can really take advantage of. I would say if you're contemplating your strategy right now, my coaching would be, get help. It's a team sport. So definitely leverage your partners and think through the pros and cons of the strategy. Establish a primary hyperscaler, I think that's going to be super key and maximize your value through optimizing the workload, the data placement and really scaling the running operations. And lastly, maybe Dave move quickly right? Each day that you wait, you're incurring technical debt in your legacy environment, that's going to increase the cost and barrier to entry when moving to the new cloud hybrid driver. >> Thank you for that. Anupam I wonder if we could talk a little bit about the business impact. I mean, in the early days of big data, yes, it was a heavy lift, but it was really transformative. When you go to hybrid cloud, is it really about governance and compliance and security and getting the right mix in terms of latency? Are there other, you know, business impacts that are potentially as transformative as we saw in the early days? What are your thoughts on that? >> Absolutely. It's the other business impacts that are interesting. And you know, Dave, let's say you're in the line of business and I come to you and say, oh, there's cost, there's all these other security governance benefits. It doesn't ring the bell for you. But if I say, Dave used to wait 32 weeks, 32 weeks to procure hardware and install software, but I can give you the same thing in 30 minutes. It's literally that transformative, right? Even on-prem, if I use cloud native technology, I can give something today within days versus weeks. So we have banks, we have a bank in Ohio that would take 32 weeks to rack up a 42 node server. Yes, it's very powerful, you have 42 nodes on it, 42 things stacked on it, but still it's taking too much time. So when you get cloud native technologies in your data center, you start behaving like the cloud and you're responsive to the business. The responsiveness is very important. >> That's a great point. I mean, in fact, you know, there's always this debate about is the cloud public cloud probably cost more expensive? Is it more expensive to rent than it is to own? And you get debates back and forth based on your perspective. But I think at the end of the day, what, Anupam you just talked about, it may oftentimes could dwarf, you know, any cost factors, if you can actually, you know, move that fast. Now cost is always a consideration. But I want to talk about the migration path if we can Manish. Where do, how should customers think about migrating to the cloud migration's a, an evil word. How should they think about migrating to the cloud? What's the strategy there? Where should they start? >> No I think you should start with kind of a use case in mind. I think you should start with a particular data set in mind as well. I think starting with what you're really seeking to achieve from a business value perspective is always the right lens in my mind. This is the decade of time technology and cloud to the fitness value, right? So if you start with, I'm seeking to make a dramatic upsell or dramatic change to my top line or bottom line, start with the use case in mind and migrate the data sets and elements that are relevant to that use case, relevant to that value, relevant to that unlock that you're trying to create, that I think is the way to prioritize it. Most of our clients are going to have tons and tons of data in their legacy environment. I don't think the right way to start is to start with a strategy that's going to be focused on migrating all of that. I think the strategy is start with the prioritized items that are tied to the specific value or the use case you're seeking to drive and focus your transformation and your migration on that. >> So guys I've been around a long time in this business and been an observer for awhile. And back in the mainframe days, we used to have a joke called CTAM. When we talk about moving data, it was called the Chevy truck access method. So I want to ask you Anupam, how do you move the data? Do you, it's like an Einstein saying, right? Move as much data as you need to, but no more. So what's going on in that front? what's happening with data movement, and, you know, do you have to make changes to the applications when you move data to the cloud? >> So there's two design patterns, but I love your service story because you know, when you have a 30 petabyte system and you tell the customer, hey, just make a copy of the data and everything will be fine. That will take you one and a half years to make the copies aligned with each other. Instead, what we are seeing is the biggest magic is workload analysis. You analyze the workload, you analyze the behavior of the users, and say so let's say Dave runs dashboards that are very complicated and Manish waits for compute when Dave is running his dashboard. If you're able to gather that information, you can actually take some of the noise out of the system. So you take selected sets of hot data, and you move it to public cloud, process it in public cloud maybe even bring it back. Sounds like science fiction, but the good news is you don't need a Chevy to take all that data into public cloud. It's a small amount of data. That's one reason the other pattern that we have seen is, let's say Manish needs something as a data scientist. And he needs some really specific type of GPUs that are only available in the cloud. So you pull the data sets out that Manish needs so that he can get the new silicone, the new library in the cloud. Those are the two patterns that if you have a new type of compute requirement, you go to public cloud, or if you have a really noisy tenant, you take the hot data out into public cloud and process it there. Does that make sense? >> Yeah it does and it sort of sets up this notion I was sort of describing upfront that the cloud is not just, you know, the public cloud, it's the spans on-prem and multicloud and even the edge. And it seems to me that you've got a metadata opportunity I'll call it and a challenge as well. I mean, there's got to be a lot of R and D going on right now. You hear people talking about cloud native and I wonder on Anupam if you could stay on that, I mean, what's your sense as to how, what the journey is going to look like? I mean, we're not going to get there overnight. People have laid out a vision of this sort of expanding cloud and I'm saying it's a metadata opportunity, but I, you know, how do you, the system has to know what workload to put where based on a lot of those factors that you guys were talking about. The governance, the laws of the land, the latency issues, the cost issues is, you know, how is the industry Anupam sort of approaching this problem and solving this problem? >> I think the biggest thing is to reflect all your security governance across every cloud, as well as on-prem. So let's say, you know, a particular user named Manish cannot access financial data, revenue data. It's important that that data as it goes around the cloud, if it gets copied from on-prem to the cloud, it should carry that quality with it. A big danger is you copy it into some optic storage, and you're absolutely right Dave metadata is the goal there. If you copy the data into an object storage and you lose all metadata, you lose all security, you lose all authorization. So we have invested heavily in something called shared data experience. Which reflects policies from on-prem all the way to the cloud and back. We've seen customers needing to invest in that, but some customers went all hog on the cloud and they realize that putting data just in these buckets of optic storage, you lose all the metadata, and then you're exposing yourself to some breach and security issues. >> Manish I wonder if we could talk about, thank you for that Anupam. Manish I wonder if we could talk about, you know, I've imagined a project, okay? Wherever I am in my journey, maybe you can pick your sort of sweet spot in the market today. You know, what's the fat middle if you will. What does a project look like when I'm migrating to the cloud? I mean, what are some of the, who are the stakeholders? What are some of the outer scope maybe expectations that I better be thinking about? What kind of timeframe? How should I tackle this and so it's not like a, you know, a big, giant expensive? Can I take it in pieces? What's the state-of-the-art of a project look like today? >> Yeah, lots of thoughts come to mind, Dave, when you ask that question. So there's lots to pack. As far as who the buyer is or what the project is for, this is out of migration is directly relevant to every officer in the C-suite in my mind. It's very relevant for the CIO and CTO obviously it's going to be their infrastructure of the future, and certainly something that they're going to need to migrate to. It's very important for the CFO as well. These things require a significant migration and a significant investment from enterprises, different kind of position there. And it's very relevant all the way up to the CEO. Because if you get it right, the truly the power it unlocks is illuminates parts of your business that allow you to capture more value, capture a higher share of wallet, allows you to pivot. A lot of our clients right now are making a pivot from going from a products organization to an as a service organization and really using the capabilities of the cloud to make that pivot happen. So it's really relevant kind of across the C-suite. As far as what a typical program looks like, I always coach my clients just like I said, to start with the value case in mind. So typically, what I'll ask them to do is kind of prioritize their top three or five use cases that they really want to drive, and then we'll land a project team that will help them make that migration and really scale out data and analytics on the cloud that are focused on those use cases. >> Great, thank you for that. I'm glad you mentioned the shift in the mindset from product to as a service. We're seeing that across the board now, even infrastructure players are jumping on the bandwagon and borrowing some sort of best practices from the SaaS vendors. And I wanted to ask you guys about, I mean, as you move to the cloud, one of the other things that strikes me is that you actually get greater scale, but there's a broader ecosystem as well. So we're kind of moving from a product centric world and with SaaS we've got this sort of platform centric, and now it seems like ecosystems are really where the innovation is coming from. I wonder if you guys could comment on that, maybe Anupam you could start. >> Yeah, many of our customers as I said right? Are all about sharing data with more and more lines of businesses. So whenever we talk to our CXO partners, our CRO partners, they are being asked to open up the big data system to more tenants. The fear is, of course, if you add more tenants to a system, it could get, you know, the operational actually might get violated. So I think that's a very important part as more and more collaboration across the company, more and more collaboration across industries. So we have customers who create sandboxes. These are healthcare customers who create sandbox environments for other pharma companies to come in and look at clinical trial data. In that case, you need to be able to create these fenced environments that can be run in public cloud, but with the same security that you expect up. >> Yeah thank you. So Manish this is your wheelhouse as Accenture. You guys are one of the top, you know, two or three or four organizations in the world in terms of dealing with complexity, you've got deep industry expertise, and it seems like some of these ecosystems as Anupam was just sort of describing it in a form are around industries, whether it's healthcare, government, financial services and the like. Maybe your thoughts on the power of ecosystems versus the, you know, the power of many versus the resources of one. >> Yeah, listen, I always talk about this is a team sport right? And it's not about doing it alone. It's about developing as ecosystem partners and really leveraging the power of that collective group. And I've been for as my clients to start thinking about, you know, the key thing you want to think about is how you migrate to becoming a data driven enterprise. And in order for you to get there, you're going to need ecosystem partners to go along the journey with you, to help you drive that innovation. You're going to need to adopt a pervasive mindset to data and democratization of that data everywhere in your enterprise. And you're going to need to refocus your decision-making based on that data, right? So I think partner ecosystem partnerships are here to stay. I think what we're going to see Dave is, you know, at the beginning of the maturity cycle, you're going to see the ecosystem expand with lots of different players and technologies kind of focused on industry. And then I think you'll get to a point where it starts to mature and starts to consolidate as ecosystem partners start to join together through acquisitions and mergers and things like that. So I think ecosystem is just starting to change. I think the key message that I would give to our clients is take advantage of that. There's too much complexity for any one person to kind of navigate through on your own. It's a team sport, so take advantage of all the partnerships you can create. >> Well, Manish one of the things you just said that it kind of reminds me, you said data data-driven, you know, organizations and, you know, if you look at the pre-COVID narrative around digital transformation, certainly there was a lot of digital transformation going on, but there was a lot of complacency too. I talked to a lot of folks, companies that say, "you know, we're doing pretty well, our banks kicking butt right now, we're making a ton of money." Or you know, all that stuff that's kind of not on my watch. I'll be retired before then. And then it was the old, "if it ain't broke, don't fix it." And then COVID breaks everything. And now if you're not digital, you're out of business. And so Anupam I'll start with you. I mean, to build a data-driven culture, what does that mean? That means putting data at the center of your organization, as opposed to around in stove pipes. And this, again, we talked about this, it sort of started in there before even the early parts of last decade. And so it seems that there's cultural aspects there's obviously technology, but there's skillsets, there's processes, you've got a data lifecycle and a data, what I sometimes call a data pipeline, meaning an end to end cycle. And organizations are having to rethink really putting data at the core. What are you seeing? And specifically as it relates to this notion of data-driven organization and data culture, what's working? >> Yeah three favorite stories, and you're a 100% right. Digital transformation has been hyperaccelerated with COVID right? So our telco customers for example, you know, Manish had some technical problems with bandwidth just 10 minutes ago. Most likely is going to call his ISP. The ISP will most likely load up a dashboard in his zip code and the reason it gives me stress, this entire story is because most likely it's starting on a big data system that has to collect data every 15 minutes, and make it available. Because you'll have a very angry Manish on the other end, if you can't explain when is the internet coming back, right? So, as you said this is accelerated. Our telco providers, our telco customers ability to ingest data, because they have to get it in 15 minute increments, not in 24 hour increments. So that's one. On the banking sector what we have seen is uncertainty has created more needs for data. So next week is going to be very uncertain all of us know elections are upcoming. We have customers who are preparing for that additional variable capacity, elastic capacity, so that if investment bankers start running hundreds and thousands of reports, they better be ready. So it's changing the culture at a very fundamental level, right? And my last story is healthcare. You're running clinical trials, but everybody wants access to the data. Your partners, the government wants access to the data, manufacturers wants access to the data. So again, you have to actualize digital transformation on how do you share very sensitive, private healthcare data without violating any policy. But you have to do it quick. That's what COVID has started. >> Thank you for that. So I want to come back to hybrid cloud. I know a lot of people in the audience are, want to learn more about that. And they have a mandate really to go to cloud generally but hybrid specifically. So Manish I wonder if you could share with us, maybe there's some challenges, I mean what's the dark side of hybrid. What should people be thinking about that they, you know, they don't want to venture into, you know, this way, they want to go that way. What are some of the challenges that you're seeing with customers? And how are they mitigating them? >> Yeah, Dave it's a great question. I think there's a few items that I would coach my clients to prioritize and really get right when thinking about making the migration happen. First of all, I would say integration. Between your private and public components that can be complex, it can be challenging. It can be complicated based on the data itself, the organizational structure of the company, the number of touches and authors we have on that data and several other factors. So I think it's really important to get this integration right, with some clear accountabilities build automation where you can and really establish some consistent governance that allows you to maintain these assets. The second one I would say is security. When it comes to hybrid cloud management, any transfers of data you need to handle the strict policies and procedures, especially in industries where that's really relevant like healthcare and financial services. So using these policies in a way that's consistent across your environment and really well understood with anyone who's touching your environment is really important. And the third I would say is cost management. All the executives that I talk about have to have a cost management angle to it. Cloud migration provides ample opportunities for cost reduction. However many migration projects can go over budget when all the costs aren't factored in, right? So your cloud vendors. You've got to be mindful of kind of the charges on accessing on premise applications and scaling costs that maybe need to be budgeted for and where if possible anticipated and really plan for. >> Excellent. So Anupam I wonder if we could go a little deeper on, we talked a little bit about this, but kind of what you put where, which workloads. What are you seeing? I mean, how are people making the choice? Are they saying, okay, this cloud is good for analytics. This cloud is good. Well, I'm a customer of their software so I'm going to use this cloud or this one is the best infrastructure and they got, you know, the most features. How are people deciding really what to put where? Or is it, "hey, I don't want to be locked in to one cloud. I want to spread my risk around. What are you seeing specifically? >> I think the biggest thing is just to echo what Manish said. Is business comes in and as a complaint. So most projects that we see on digital transformation and on public cloud adoption is because businesses complaining about something. It's not architectural goodness, it is not for just innovation for innovation's sake. So, the biggest thing that we see is what we call noisy neighbors. A lot of dashboards, you know, because business has become so intense, click, click, click, click, you're actually putting a lot of load on the system. So isolating noisy neighbors into a cloud is one of the biggest patterns that you've seen. It takes the noisiest tenant on your cluster, noisiest workload and you take them to public cloud. The other one is data scientists. They want new libraries, they want to work with GPU's. And to your point Dave, that's where you select a particular cloud. Let's say there's a particular type silicone that is available only in that cloud. That GPU is available only in that cloud or that particular artificial intelligence library is available only in a particular cloud. That's when customers say, Hey miss, they decided, why don't you go to this cloud while the main workload might still be running on them, right? That's the two patterns that we are seeing. >> Right thank you. And I wonder if we can end on a little bit of looking to the future. Maybe how this is all going to evolve over the next several years. I mean, I like to look at it at a spectrum at a journey. It's not going to all come at once. I do think the edge is part of that. But it feels like today we've got, you know, multi clouds are loosely coupled and hybrid is also loosely coupled, but we're moving very quickly to a much more integrated, I think we Manish you talked about integration. Where you've got state, you've got the control plane, you've got the data plane. And all this stuff is really becoming native to the respective clouds and even bring that on-prem and you've got now hybrid applications and much much tighter integration and build this, build out of this massively distributed, maybe going from it's a hyper-converged to hyper-distributed again including the edge. So I wonder Manish we could start with you. How are your customers thinking about the future? How are they thinking about, you know, making sure that they're not going down a path where that's going to, they're going to incur a lot of technical debt? I know there's sort of infrastructure is code and containers and that seems it seems necessary, but insufficient there's a lot of talk about, well maybe we start with a functions based or a serverless architecture. There's some bets that have to be made to make sure that you can future proof yourself. What are you recommending there Manish? >> Yeah, I, listen I think we're just getting started in this journey. And like I said, it's really exciting time and I think there's a lot of evolution in front of us that we're going to see. I, you know, I think for example, I think we're going to see hybrid technologies evolve from public and private thinking to dedicated and shared thinking instead. And I think we're going to see advances in capabilities around automation and computer federation and evolution of consumption models of that data. But I think we've got a lot of kind of technology modifications and enhancements ahead of us. As far as companies and how they future proof themselves. I would offer the following. First of all, I think it's a time for action, right? So I would encourage all my class to take action now. Every day spent in legacy adds to the technical debt that you're going to incur, and it increases your barrier to entry. The second one would be move with agility and flexibility. That's the underlying value of hybrid cloud structures. So organizations really need to learn how to operate in that way and take advantage of that agility and that flexibility. We've talked about creating partnerships in ecosystems I think that's going to be really important. Gathering partners and thought leaders to help you navigate through that complexity. And lastly I would say monetizing your data. Making a value led approach to how you viewed your data assets and force a function where each decision in your enterprise is tied to the value that it creates and is backed by the data that supports it. And I think if you get those things right, the technology and the infrastructure will serve. >> Excellent and Anupam why don't you bring us home, I mean you've got a unique combination of technical acumen and business knowledge. How do you see this evolving over the next three to five years? >> Oh, thank you Dave. So technically speaking, adoption of containers is going to steadily make sure that you're not aware even of what cloud you're running on that day. So the multicloud will not be a requirement even, it will just be obviated when you have that abstraction there. Contrarily, it's going to be a bigger challenge. I would echo what Manish said start today, especially on the cultural side. It is great that you don't have to procure hardware anymore, but that also means that many of us don't know what our cloud bill is going to be next month. It is a very scary feeling for your CIO and your CFO that you don't know how much you're going to to spend next month forget next year, right? So you have to be agile in your financial planning as much you have to be agile in your technical planning. And finally I think you hit on it. Ecosystems are what makes data great. And so you have to start from day one that if I am going on this cloud solution, is the data shareable? Am I able to create an ecosystem around that data? Because without that, it's just somebody running a report may or may not have value to the business. >> That's awesome, guys. Thanks so much for a great conversation. We're at a time and I want to wish everybody a terrific event. Let me now hand it back to Vanita. She's going to take you through the rest of the day. This is Dave Vellante for theCUBE, thanks. (smooth calm music)

from around the globe it's thecube with coverage of kubecon and cloudnativecon north america 2020 virtual brought to you by red hat the cloud native computing foundation and ecosystem partners hello and welcome back to the cube's coverage of kubecon plus cloud nativecon 2020 the virtual edition abinav joshi is here he's the senior product marketing manager for openshift at red hat and tom dean is the senior director of pro product management at cloudera gentlemen thanks for coming on thecube good to see you thank you very much for having us here hey guys i know you would be here it was great to have you and guys i know you're excited about the partnership and i definitely want to get in and talk about that but before we do i wonder if we could just set the tone you know what are you seeing in the market tom let's let's start with you i had a great deep dive a couple of weeks back with anupam singh and he brought me up to speed on what's new with cloudera but but one of the things we discussed was the accelerated importance of data putting data at the core of your digital business tom what are you seeing in the marketplace right now yeah absolutely so um overall we're still seeing a growing demand for uh storing and and processing massive massive amounts of data even in the past few months um where perhaps we see a little bit more variety is on by industry sector is on the propensity to adopt some of the latest and greatest uh technologies that are out there or that we we deliver to the market um so whether perhaps in the retail hospitality sector you may see a little bit more risk aversion around some of the latest tools then you you go to the healthcare industry as an example and you see we see a strong demand for our latest technologies uh with with everything that is that is going on um so overall um still a lot lots of demand around this space so abnormal i mean we just saw in ibm's earnings though the momentum of red hat you know growing in the mid teens and the explosion that we're seeing around containers and and obviously openshift is at the heart of that how the last nine months affected your customers priorities and what are you seeing yeah we've been a lot more busier like in the last few months because there's like a lot of use cases and if you look at the like a lot of the research and so on and we are seeing that from our customers as well that now the customers are actually speeding up the digital transformation right people say that okay kovac 19 has actually uh speeded up the digital transformation for a lot of our customers for the right reasons to be able to help the customers and so on so we are seeing a lot of attraction on like number of verticals and number of use cases beyond the traditional lab dev data analytics aiml messaging streaming edge and so on like lots of use cases in like a lot of different like industry verticals so there's a lot of momentum going on on openshift and the broader that portfolio as well yeah it's ironic the the timing of the pandemic but it sure underscores that this next 10 years is going to be a lot different than the last 10 years okay let's talk about some of the things that are new around data tom cloudera you guys have made a number of moves since acquiring hortonworks a little over two years ago what's new with uh with the cloudera data platform cdp sure so yes our latest therap uh platform is called cbp clara data platform last year we announced the public cloud version of cdp running on aws and then azure and what's new is just two months ago we announced the release of the version of this platform targeted at the data center and that's called cvp private cloud and really the focus of this platform this new version has been around solving some of the pain points that we see around agility or time to value and the ease of use of the platform and to give you some specific examples with our previous technology it could take a customer three months to provision a data warehouse if you include everything from obtaining the infrastructure to provisioning the warehouse loading the data setting security policies uh and fine-tuning the the software now with cbp private cloud we've been able to take those uh three months and turn it into three minutes so significant uh speed up in in that onboarding time and in time to valley and a key piece of this uh that enabled this this speed up was a revamping of the entire stack specifically the infrastructure and service services management layer and this is where the containerization of the platform comes in specifically kubernetes and red hat open shift that is a key piece of the puzzle that enables this uh order of magnitude uh improvement in time right uh now abner you think about uh red hat you think about cloudera of course hortonworks the stalwarts of of of open source you got kind of like birds of a feather how are red hat and cloudera partnering with each other you know what are the critical aspects of that relationship that people should be aware of yeah absolutely that's a very good question yeah so on the openshift side we've had a lot of momentum in the market and we have well over 2000 customers in terms of a lot of different verticals and the use cases that i talked about at the beginning of our conversation in terms of traditional and cloud native app dev databases data analytics like ai messaging and so on right and the value that you have with openshift and the containers kubernetes and devops like part of the solution being able to provide the agility flexibility scalability the cross cloud consistency like so all that that you see in a typical app dev world is directly applicable to fast track the data analytics and the ai projects as well and we've seen like a lot of customers and some of the ones that we can talk about in a public way like iix rbc bank hca healthcare boston children's bmw exxon mobil so all these organizations are being are able to leverage openshift to kind of speed up the ai projects and and help with the needs of the data engineers data scientists and uh and the app dev folks now from our perspective providing the best in class uh you say like experience for the customers at the platform level is key and we have to make sure that the tooling that the customers run on top of it uh gets the best in class the experience in terms of the day zero to day two uh management right and it's uh and and it's an ecosystem play for us and and and that's the way cloudera is the top isv in the space right when it comes to data analytics and ai and that was our key motivation to partner with cloudera in terms of bringing this joint solution to market and making sure that our customers are successful so the partnership is at all the different levels in the organization say both up and down as well as in the the engineering level the product management level the marketing level the sales level and at the support and services level as well so that way if you look at the customer journey in terms of selecting a solution uh putting it in place and then getting the value out of it so the partnership it actually spans across the entire spectrum yeah and tom you know i wonder if you could add anything there i mean it's not just about the public cloud with containers you're seeing obviously the acceleration of of cloud native principles on-prem in a hybrid you know across clouds it's sort of the linchpin containers really and kubernetes specifically linchpin to enable that what would you add to that discussion yeah as part of the partnership when we were looking for a vendor who could provide us that kubernetes layer we looked at our customer base and if you think about who clara is focused on we really go after that global the global 2000 firms out there these customers have very strict uh security requirements and they're often in these highly regulated uh industries and so when we looked at a customer's base uh we saw a lot of overlap and there was a natural good fit for us there but beyond that just our own technical evaluation of the solutions and also talking to uh to our own customers about who they do they see as a trusted platform that can provide enterprise grade uh features on on a kubernetes layer red hat had a clear leadership in in that front and that combined with our own uh long-standing relationship with our parent company ibm uh it made this partnership a natural good thing for us right and cloudera's always had a good relationship with ibm tom i want to stay with you if i can for a minute and talk about the specific joint solutions that you're providing with with red hat what are you guys bringing to customers in in terms of those solutions what's the business impact where's the value absolutely so the solution is called cbd or color data platform private cloud on red hat openshift and i'll describe three uh the three pillars that make up cbp uh first what we have is the five data analytic experiences and that is meant to cover the end to end data lifecycle in the first release we just came out two months ago we announced the availability of two of those five experiences we have data warehousing for bi analytics as well as machine learning and ai where we offer a collaborative data science data science tools for data scientists to come together do exploratory data analytics but also develop predictive models and push them to production going forward we'll be adding the remaining three uh experiences they include data engineering or transformations on uh on your data uh data flow for streaming analytics and ingest uh as well as operational database for uh real-time surveying of both structure and unstructured data so these five experiences have been re-banked right compared to our prior platform to target these specific use cases and simplify uh these data disciplines the second pillar that i'll talk about is the sdx or uh what what we call the shared data experience and what this is is the ability for these five experiences to have one global data set that they can all access with shared metadata security including fine grain permissions and a suite of governance tools that provide lineage provide auditing and business metadata so by having these shared data experiences our developers our users can build these multi-disciplinary workflows in a very straightforward way without having to create all this custom code and i can stitch you can stitch them together and the last pillar that i'll mention uh is the containerization of of the platform and because of containers because of kubernetes we're now able to offer that next level of agility isolation uh and infrastructure efficiency on the platform so give you a little bit more specific examples on the agility i mentioned going from three months to three minutes in terms of the speed up with i uh with uh containers we can now also give our users the ability to bring their own versions of their libraries and engines without colliding with another user who's sharing the platform that has been a big ask from our customers and last i'll mention infrastructure efficiency by re-architecting our services to running a microservices architecture we can now impact those servers in a much more efficient way we can also auto scale auto suspend bring all this as you mentioned bring all these cloud native concepts on premises and the end result of that is better infrastructure efficiency now our customers can do more with the same amount of hard work which overall uh reduces their their total spend on the solution so that's what we call cbp private cloud great thanks for that i mean wow we've seen really the evolution from the the wild west days of you know the early days of so-called big data ungoverned a lot of shadow data science uh maybe maybe not as efficient as as we'd like and but certainly today taking advantage of some of those capabilities dealing with the noisy neighbor problem enough i wonder if you could comment another question that i have is you know one of the things that jim whitehurst talked about when ibm acquired red hat was the scale that ibm could bring and what i always looked at in that context was ibm's deep expertise in vertical industries so i wonder what are some of the key industry verticals that you guys are targeting and succeeding in i mean yes there's the pandemic has some effects we talked about hospitality obviously airlines have to have to be careful and conserving cash but what are some of the interesting uh tailwinds that you're seeing by industry and some of the the more interesting and popular use cases yeah that's a very good question now in terms of the industry vertical so we are seeing the traction in like a number of verticals right and the top ones being the financial services like healthcare telco the automotive industry as well as the federal government are some of the key ones right and at the end of the day what what all the customers are looking at doing is be able to improve the experience of their customers with the digital services that they roll out right as part of the pandemic and so on as well and then being able to gain competitive edge right if you can have the services in your platform and make them kind of fresh and relevant and be able to update them on a regular basis that's kind of that's your differentiator these days right and then the next one is yeah if you do all this so you should be able to increase your revenue be able to save cost as well that's kind of a key one that you mentioned right that that a lot of the industries like the hospitality the airlines and so on are kind of working on saving cash right so if you can help them save the cost that's kind of key and then the last one is is being able to automate the business processes right because there's not like a lot of the manual processes so yeah if you can add in like a lot of automation that's all uh good for your business and then now if you look at the individual use cases in these different industry verticals what we're seeing that the use cases cannot vary from the industry to industry like if you look at the financial services the use cases like fraud detection being able to do the risk analysis and compliance being able to improve the customer support and so on are some of the key use cases the cyber security is coming up a lot as well because uh yeah nobody wants to be hacked and so and and so on yeah especially like in these times right and then moving on to healthcare and the life sciences right what we're seeing the use cases on being able to do the data-driven diagnostics and care and being able to do the discovery of drugs being able to say track kobit 19 and be able to tell that okay uh which of my like hospital is going to be full when and what kind of ppe am i going to need at my uh the the sites and so on so that way i can yeah and mobilize like as needed are some of the key ones that we are seeing on the healthcare side uh and then in terms of the automotive industry right that's where being able to speed up the autonomous driving initiatives uh being able to do uh the auto warranty pricing based on the history of the drivers and so on and then being able to save on the insurance cost is a big one that we are seeing as well for the insurance industries and then but more like manufacturing right being able to do the quality assurance uh at the shop floor being able to do the predictive maintenance on machinery and also be able to do the robotics process automation so like lots of use cases that customers are prioritizing but it's very verticalized it kind of varies from the vertical to a vertical but at the end of the day yeah it's all about like improving the customer experience the revenue saving cost and and being able to automate the business processes yeah that's great thank you for that i mean we we heard a lot about automation we were covering ansible fest i mean just think about fraud how much you know fraud detection has changed in the last 10 years it used to be you know so slow you'd have to go go through your financial statements to find fraud and now it's instantaneous cyber security is critical because the adversaries are very capable healthcare is a space where you know it's ripe for change and now of course with the pandemic things are changing very rapidly automotive another one an industry that really hasn't hadn't seen much disruption and now you're seeing with a number of things autonomous vehicles and you know basically software on wheels and insurance great example even manufacturing you're seeing you know a real sea change there so thank you for that description you know very often in the cube we like to look at joint engineering solutions that's a gauge of the substance of a partnership you know sometimes you see these barney deals you know there's a press release i love you you love me okay see you but but so i wonder if you guys could talk about specific engineering that you're doing tom maybe you could start sure yeah so on the on the engineering and product side um we've um for cbp private cloud we've we've changed our uh internal development and testing to run all on uh openshift uh internally uh and as part of that we we have a direct line to red hat engineering to help us solve any issues that that uh we run into so in the initial release we start with support of openshift43 we're just wrapping up uh testing of and we'll begin with openshift46 very soon on another aspect of their partnership is on being able to update our images to account for any security vulnerabilities that are coming up so with the guidance and help from red hat we've been we've standardized our docker images on ubi or the universal based image and that allows us to automatically get many of these security fixes uh into our into our software um the last point that i mentioned here is that it's not just about providing kubernetes uh red hat helps us with the end to end uh solution so there is also the for example bringing a docker registry into the picture or providing a secure vault for storing uh all the secrets so all these uh all these pieces combined make up the uh a strong complete solution actually the last thing i'll mention is is a support aspect which is critical to our customers in this model our customers can bring support tickets to cluberra but as soon as we determine that it may be an issue that uh related to red hat or openshift where we can use their help we have that direct line of communication uh and automated systems in the back end to resolve those support tickets uh quickly for our customers so those are some of the examples of what we're doing on the technical side great thank you uh enough we're out of time but i wonder if we could just close here i mean when we look at our survey data with our data partner etr we see containers container orchestration container management generally and again kubernetes specifically is the the number one area of investment for companies that has the most momentum in terms of where they're putting their efforts it's it's it's right up there and even ahead of ai and machine learning and even ahead of cloud which is obviously larger maybe more mature but i wonder if you can add anything and bring us home with this segment yeah absolutely and i think uh so uh one thing i want to add is like in terms of the engineering level right we also have like between cloudera and red hat the partnership and the sales and the go to market levels as well because once you build the uh the integration it yeah it has to be built out in the customer environments as well right so that's where we have the alignment um at the marketing level as well as the sales level so that way we can like jointly go in and do the customer workshops and make sure the solutions are getting deployed the right way right uh and also we have a partnership at the professional services level as well right where um the experts from both the orgs are kind of hand in hand to help the customers right and then at the end of the day if you need help with support and that's what tom talked about that we have the experts on the support side as well yeah and then so to wrap things up right uh so all the industry research and the customer conversation that we are having are kind of indicating that the organizations are actually increasing the focus on digital uh transformation with the data and ai being a key part of it and that's where this strategic partnership between cloudera and and red hat is going to play a big role to help our mutual customers uh through that our transition and be able to achieve the key goals that they set for their business great well guys thanks so much for taking us through the partnership and the integration work that you guys are doing with customers a great discussion really appreciate your time yeah thanks a lot dave really appreciate it really enjoyed the conversation all right keep it right there everybody you're watching thecube's coverage of cubecon plus cloud nativecon north america the virtual edition keep it right there we'll be right back