>> From theCUBE Studios in Palo Alto and Boston, bringing you data-driven insights from theCUBE and ETR, this is Breaking Analysis with Dave Vellante. >> This past week we saw two of the Big 3 cloud providers present the latest update on their respective cloud visions, their business progress, their announcements and innovations. The content at these events had many overlapping themes, including modern cloud infrastructure at global scale, applying advanced machine intelligence, AKA AI, end-to-end data platforms, collaboration software. They talked a lot about the future of work automation. And they gave us a little taste, each company of the Metaverse Web 3.0 and much more. Despite these striking similarities, the differences between these two cloud platforms and that of AWS remains significant. With Microsoft leveraging its massive application software footprint to dominate virtually all markets and Google doing everything in its power to keep up with the frenetic pace of today's cloud innovation, which was set into motion a decade and a half ago by AWS. Hello and welcome to this week's Wikibon CUBE Insights, powered by ETR. In this Breaking Analysis, we unpack the immense amount of content presented by the CEOs of Microsoft and Google Cloud at Microsoft Ignite and Google Cloud Next. We'll also quantify with ETR survey data the relative position of these two cloud giants in four key sectors: cloud IaaS, BI analytics, data platforms and collaboration software. Now one thing was clear this past week, hybrid events are the thing. Google Cloud Next took place live over a 24-hour period in six cities around the world, with the main gathering in New York City. Microsoft Ignite, which normally is attended by 30,000 people, had a smaller event in Seattle, in person with a virtual audience around the world. AWS re:Invent, of course, is much different. Yes, there's a virtual component at re:Invent, but it's all about a big live audience gathering the week after Thanksgiving, in the first week of December in Las Vegas. Regardless, Satya Nadella keynote address was prerecorded. It was highly produced and substantive. It was visionary, energetic with a strong message that Azure was a platform to allow customers to build their digital businesses. Doing more with less, which was a key theme of his. Nadella covered a lot of ground, starting with infrastructure from the compute, highlighting a collaboration with Arm-based, Ampere processors. New block storage, 60 regions, 175,000 miles of fiber cables around the world. He presented a meaningful multi-cloud message with Azure Arc to support on-prem and edge workloads, as well as of course the public cloud. And talked about confidential computing at the infrastructure level, a theme we hear from all cloud vendors. He then went deeper into the end-to-end data platform that Microsoft is building from the core data stores to analytics, to governance and the myriad tooling Microsoft offers. AI was next with a big focus on automation, AI, training models. He showed demos of machines coding and fixing code and machines automatically creating designs for creative workers and how Power Automate, Microsoft's RPA tooling, would combine with Microsoft Syntex to understand documents and provide standard ways for organizations to communicate with those documents. There was of course a big focus on Azure as developer cloud platform with GitHub Copilot as a linchpin using AI to assist coders in low-code and no-code innovations that are coming down the pipe. And another giant theme was a workforce transformation and how Microsoft is using its heritage and collaboration and productivity software to move beyond what Nadella called productivity paranoia, i.e., are remote workers doing their jobs? In a world where collaboration is built into intelligent workflows, and he even showed a glimpse of the future with AI-powered avatars and partnerships with Meta and Cisco with Teams of all firms. And finally, security with a bevy of tools from identity, endpoint, governance, et cetera, stressing a suite of tools from a single provider, i.e., Microsoft. So a couple points here. One, Microsoft is following in the footsteps of AWS with silicon advancements and didn't really emphasize that trend much except for the Ampere announcement. But it's building out cloud infrastructure at a massive scale, there is no debate about that. Its plan on data is to try and provide a somewhat more abstracted and simplified solutions, which differs a little bit from AWS's approach of the right database tool, for example, for the right job. Microsoft's automation play appears to provide simple individual productivity tools, kind of a ground up approach and make it really easy for users to drive these bottoms up initiatives. We heard from UiPath that forward five last month, a little bit of a different approach of horizontal automation, end-to-end across platforms. So quite a different play there. Microsoft's angle on workforce transformation is visionary and will continue to solidify in our view its dominant position with Teams and Microsoft 365, and it will drive cloud infrastructure consumption by default. On security as well as a cloud player, it has to have world-class security, and Azure does. There's not a lot of debate about that, but the knock on Microsoft is Patch Tuesday becomes Hack Wednesday because Microsoft releases so many patches, it's got so much Swiss cheese in its legacy estate and patching frequently, it becomes a roadmap and a trigger for hackers. Hey, patch Tuesday, these are all the exploits that you can go after so you can act before the patches are implemented. And so it's really become a problem for users. As well Microsoft is competing with many of the best-of-breed platforms like CrowdStrike and Okta, which have market momentum and appear to be more attractive horizontal plays for customers outside of just the Microsoft cloud. But again, it's Microsoft. They make it easy and very inexpensive to adopt. Now, despite the outstanding presentation by Satya Nadella, there are a couple of statements that should raise eyebrows. Here are two of them. First, as he said, Azure is the only cloud that supports all organizations and all workloads from enterprises to startups, to highly regulated industries. I had a conversation with Sarbjeet Johal about this, to make sure I wasn't just missing something and we were both surprised, somewhat, by this claim. I mean most certainly AWS supports more certifications for example, and we would think it has a reasonable case to dispute that claim. And the other statement, Nadella made, Azure is the only cloud provider enabling highly regulated industries to bring their most sensitive applications to the cloud. Now, reasonable people can debate whether AWS is there yet, but very clearly Oracle and IBM would have something to say about that statement. Now maybe it's not just, would say, "Oh, they're not real clouds, you know, they're just going to hosting in the cloud if you will." But still, when it comes to mission-critical applications, you would think Oracle is really the the leader there. Oh, and Satya also mentioned the claim that the Edge browser, the Microsoft Edge browser, no questions asked, he said, is the best browser for business. And we could see some people having some questions about that. Like isn't Edge based on Chrome? Anyway, so we just had to question these statements and challenge Microsoft to defend them because to us it's a little bit of BS and makes one wonder what else in such as awesome keynote and it was awesome, it was hyperbole. Okay, moving on to Google Cloud Next. The keynote started with Sundar Pichai doing a virtual session, he was remote, stressing the importance of Google Cloud. He mentioned that Google Cloud from its Q2 earnings was on a $25-billion annual run rate. What he didn't mention is that it's also on a 3.6 billion annual operating loss run rate based on its first half performance. Just saying. And we'll dig into that issue a little bit more later in this episode. He also stressed that the investments that Google has made to support its core business and search, like its global network of 22 subsea cables to support things like, YouTube video, great performance obviously that we all rely on, those innovations there. Innovations in BigQuery to support its search business and its threat analysis that it's always had and its AI, it's always been an AI-first company, he's stressed, that they're all leveraged by the Google Cloud Platform, GCP. This is all true by the way. Google has absolutely awesome tech and the talk, as well as his talk, Pichai, but also Kurian's was forward thinking and laid out a vision of the future. But it didn't address in our view, and I talked to Sarbjeet Johal about this as well, today's challenges to the degree that Microsoft did and we expect AWS will at re:Invent this year, it was more out there, more forward thinking, what's possible in the future, somewhat less about today's problem, so I think it's resonates less with today's enterprise players. Thomas Kurian then took over from Sundar Pichai and did a really good job of highlighting customers, and I think he has to, right? He has to say, "Look, we are in this game. We have customers, 9 out of the top 10 media firms use Google Cloud. 8 out of the top 10 manufacturers. 9 out of the top 10 retailers. Same for telecom, same for healthcare. 8 out of the top 10 retail banks." He and Sundar specifically referenced a number of companies, customers, including Avery Dennison, Groupe Renault, H&M, John Hopkins, Prudential, Minna Bank out of Japan, ANZ bank and many, many others during the session. So you know, they had some proof points and you got to give 'em props for that. Now like Microsoft, Google talked about infrastructure, they referenced training processors and regions and compute optionality and storage and how new workloads were emerging, particularly data-driven workloads in AI that required new infrastructure. He explicitly highlighted partnerships within Nvidia and Intel. I didn't see anything on Arm, which somewhat surprised me 'cause I believe Google's working on that or at least has come following in AWS's suit if you will, but maybe that's why they're not mentioning it or maybe I got to do more research there, but let's park that for a minute. But again, as we've extensively discussed in Breaking Analysis in our view when it comes to compute, AWS via its Annapurna acquisition is well ahead of the pack in this area. Arm is making its way into the enterprise, but all three companies are heavily investing in infrastructure, which is great news for customers and the ecosystem. We'll come back to that. Data and AI go hand in hand, and there was no shortage of data talk. Google didn't mention Snowflake or Databricks specifically, but it did mention, by the way, it mentioned Mongo a couple of times, but it did mention Google's, quote, Open Data cloud. Now maybe Google has used that term before, but Snowflake has been marketing the data cloud concept for a couple of years now. So that struck as a shot across the bow to one of its partners and obviously competitor, Snowflake. At BigQuery is a main centerpiece of Google's data strategy. Kurian talked about how they can take any data from any source in any format from any cloud provider with BigQuery Omni and aggregate and understand it. And with the support of Apache Iceberg and Delta and Hudi coming in the future and its open Data Cloud Alliance, they talked a lot about that. So without specifically mentioning Snowflake or Databricks, Kurian co-opted a lot of messaging from these two players, such as life and tech. Kurian also talked about Google Workspace and how it's now at 8 million users up from 6 million just two years ago. There's a lot of discussion on developer optionality and several details on tools supported and the open mantra of Google. And finally on security, Google brought out Kevin Mandian, he's a CUBE alum, extremely impressive individual who's CEO of Mandiant, a leading security service provider and consultancy that Google recently acquired for around 5.3 billion. They talked about moving from a shared responsibility model to a shared fate model, which is again, it's kind of a shot across AWS's bow, kind of shared responsibility model. It's unclear that Google will pay the same penalty if a customer doesn't live up to its portion of the shared responsibility, but we can probably assume that the customer is still going to bear the brunt of the pain, nonetheless. Mandiant is really interesting because it's a services play and Google has stated that it is not a services company, it's going to give partners in the channel plenty of room to play. So we'll see what it does with Mandiant. But Mandiant is a very strong enterprise capability and in the single most important area security. So interesting acquisition by Google. Now as well, unlike Microsoft, Google is not competing with security leaders like Okta and CrowdStrike. Rather, it's partnering aggressively with those firms and prominently putting them forth. All right. Let's get into the ETR survey data and see how Microsoft and Google are positioned in four key markets that we've mentioned before, IaaS, BI analytics, database data platforms and collaboration software. First, let's look at the IaaS cloud. ETR is just about to release its October survey, so I cannot share the that data yet. I can only show July data, but we're going to give you some directional hints throughout this conversation. This chart shows net score or spending momentum on the vertical axis and overlap or presence in the data, i.e., how pervasive the platform is. That's on the horizontal axis. And we've inserted the Wikibon estimates of IaaS revenue for the companies, the Big 3. Actually the Big 4, we included Alibaba. So a couple of points in this somewhat busy data chart. First, Microsoft and AWS as always are dominant on both axes. The red dotted line there at 40% on the vertical axis. That represents a highly elevated spending velocity and all of the Big 3 are above the line. Now at the same time, GCP is well behind the two leaders on the horizontal axis and you can see that in the table insert as well in our revenue estimates. Now why is Azure bigger in the ETR survey when AWS is larger according to the Wikibon revenue estimates? And the answer is because Microsoft with products like 365 and Teams will often be considered by respondents in the survey as cloud by customers, so they fit into that ETR category. But in the insert data we're stripping out applications and SaaS from Microsoft and Google and we're only isolating on IaaS. The other point is when you take a look at the early October returns, you see downward pressure as signified by those dotted arrows on every name. The only exception was Dell, or Dell and IBM, which showing slightly improved momentum. So the survey data generally confirms what we know that AWS and Azure have a massive lead and strong momentum in the marketplace. But the real story is below the line. Unlike Google Cloud, which is on pace to lose well over 3 billion on an operating basis this year, AWS's operating profit is around $20 billion annually. Microsoft's Intelligent Cloud generated more than $30 billion in operating income last fiscal year. Let that sink in for a moment. Now again, that's not to say Google doesn't have traction, it does and Kurian gave some nice proof points and customer examples in his keynote presentation, but the data underscores the lead that Microsoft and AWS have on Google in cloud. And here's a breakdown of ETR's proprietary net score methodology, that vertical axis that we showed you in the previous chart. It asks customers, are you adopting the platform new? That's that lime green. Are you spending 6% or more? That's the forest green. Is you're spending flat? That's the gray. Is you're spending down 6% or worse? That's the pinkest color. Or are you replacing the platform, defecting? That's the bright red. You subtract the reds from the greens and you get a net score. Now one caveat here, which actually is really favorable from Microsoft, the Microsoft data that we're showing here is across the entire Microsoft portfolio. The other point is, this is July data, we'll have an update for you once ETR releases its October results. But we're talking about meaningful samples here, the ends. 620 for AWS over a thousand from Microsoft in more than 450 respondents in the survey for Google. So the real tell is replacements, that bright red. There is virtually no churn for AWS and Microsoft, but Google's churn is 5x, those two in the survey. Now 5% churn is not high, but you'd like to see three things for Google given it's smaller size. One is less churn, two is much, much higher adoption rates in the lime green. Three is a higher percentage of those spending more, the forest green. And four is a lower percentage of those spending less. And none of these conditions really applies here for Google. GCP is still not growing fast enough in our opinion, and doesn't have nearly the traction of the two leaders and that shows up in the survey data. All right, let's look at the next sector, BI analytics. Here we have that same XY dimension. Again, Microsoft dominating the picture. AWS very strong also in both axes. Tableau, very popular and respectable of course acquired by Salesforce on the vertical axis, still looking pretty good there. And again on the horizontal axis, big presence there for Tableau. And Google with Looker and its other platforms is also respectable, but it again, has some work to do. Now notice Streamlit, that's a recent Snowflake acquisition. It's strong in the vertical axis and because of Snowflake's go-to-market (indistinct), it's likely going to move to the right overtime. Grafana is also prominent in the Y axis, but a glimpse at the most recent survey data shows them slightly declining while Looker actually improves a bit. As does Cloudera, which we'll move up slightly. Again, Microsoft just blows you away, doesn't it? All right, now let's get into database and data platform. Same X Y dimensions, but now database and data warehouse. Snowflake as usual takes the top spot on the vertical axis and it is actually keeps moving to the right as well with again, Microsoft and AWS is dominant in the market, as is Oracle on the X axis, albeit it's got less spending velocity, but of course it's the database king. Google is well behind on the X axis but solidly above the 40% line on the vertical axis. Note that virtually all platforms will see pressure in the next survey due to the macro environment. Microsoft might even dip below the 40% line for the first time in a while. Lastly, let's look at the collaboration and productivity software market. This is such an important area for both Microsoft and Google. And just look at Microsoft with 365 and Teams up into the right. I mean just so impressive in ubiquitous. And we've highlighted Google. It's in the pack. It certainly is a nice base with 174 N, which I can tell you that N will rise in the next survey, which is an indication that more people are adopting. But given the investment and the tech behind it and all the AI and Google's resources, you'd really like to see Google in this space above the 40% line, given the importance of this market, of this collaboration area to Google's success and the degree to which they emphasize it in their pitch. And look, this brings up something that we've talked about before on Breaking Analysis. Google doesn't have a tech problem. This is a go-to-market and marketing challenge that Google faces and it's up against two go-to-market champs and Microsoft and AWS. And Google doesn't have the enterprise sales culture. It's trying, it's making progress, but it's like that racehorse that has all the potential in the world, but it's just missing some kind of key ingredient to put it over at the top. It's always coming in third, (chuckles) but we're watching and Google's obviously, making some investments as we shared with earlier. All right. Some final thoughts on what we learned this week and in this research: customers and partners should be thrilled that both Microsoft and Google along with AWS are spending so much money on innovation and building out global platforms. This is a gift to the industry and we should be thankful frankly because it's good for business, it's good for competitiveness and future innovation as a platform that can be built upon. Now we didn't talk much about multi-cloud, we haven't even mentioned supercloud, but both Microsoft and Google have a story that resonates with customers in cross cloud capabilities, unlike AWS at this time. But we never say never when it comes to AWS. They sometimes and oftentimes surprise you. One of the other things that Sarbjeet Johal and John Furrier and I have discussed is that each of the Big 3 is positioning to their respective strengths. AWS is the best IaaS. Microsoft is building out the kind of, quote, we-make-it-easy-for-you cloud, and Google is trying to be the open data cloud with its open-source chops and excellent tech. And that puts added pressure on Snowflake, doesn't it? You know, Thomas Kurian made some comments according to CRN, something to the effect that, we are the only company that can do the data cloud thing across clouds, which again, if I'm being honest is not really accurate. Now I haven't clarified these statements with Google and often things get misquoted, but there's little question that, as AWS has done in the past with Redshift, Google is taking a page out of Snowflake, Databricks as well. A big difference in the Big 3 is that AWS doesn't have this big emphasis on the up-the-stack collaboration software that both Microsoft and Google have, and that for Microsoft and Google will drive captive IaaS consumption. AWS obviously does some of that in database, a lot of that in database, but ISVs that compete with Microsoft and Google should have a greater affinity, one would think, to AWS for competitive reasons. and the same thing could be said in security, we would think because, as I mentioned before, Microsoft competes very directly with CrowdStrike and Okta and others. One of the big thing that Sarbjeet mentioned that I want to call out here, I'd love to have your opinion. AWS specifically, but also Microsoft with Azure have successfully created what Sarbjeet calls brand distance. AWS from the Amazon Retail, and even though AWS all the time talks about Amazon X and Amazon Y is in their product portfolio, but you don't really consider it part of the retail organization 'cause it's not. Azure, same thing, has created its own identity. And it seems that Google still struggles to do that. It's still very highly linked to the sort of core of Google. Now, maybe that's by design, but for enterprise customers, there's still some potential confusion with Google, what's its intentions? How long will they continue to lose money and invest? Are they going to pull the plug like they do on so many other tools? So you know, maybe some rethinking of the marketing there and the positioning. Now we didn't talk much about ecosystem, but it's vital for any cloud player, and Google again has some work to do relative to the leaders. Which brings us to supercloud. The ecosystem and end customers are now in a position this decade to digitally transform. And we're talking here about building out their own clouds, not by putting in and building data centers and installing racks of servers and storage devices, no. Rather to build value on top of the hyperscaler gift that has been presented. And that is a mega trend that we're watching closely in theCUBE community. While there's debate about the supercloud name and so forth, there little question in our minds that the next decade of cloud will not be like the last. All right, we're going to leave it there today. Many thanks to Sarbjeet Johal, and my business partner, John Furrier, for their input to today's episode. Thanks to Alex Myerson who's on production and manages the podcast and Ken Schiffman as well. Kristen Martin and Cheryl Knight helped get the word out on social media and in our newsletters. And Rob Hof is our editor in chief over at SiliconANGLE, who does some wonderful editing. And check out SiliconANGLE, a lot of coverage on Google Cloud Next and Microsoft Ignite. Remember, all these episodes are available as podcast wherever you listen. Just search Breaking Analysis podcast. I publish each week on wikibon.com and siliconangle.com. And you can always get in touch with me via email, david.vellante@siliconangle.com or you can DM me at dvellante or comment on my LinkedIn posts. And please do check out etr.ai, the best survey data in the enterprise tech business. This is Dave Vellante for the CUBE Insights, powered by ETR. Thanks for watching and we'll see you next time on Breaking Analysis. (gentle music)

>> Hello, everyone. I'm Khalil Ahmad, Senior Director, Architecture at S&P Global. I have been working with S&P Global for six years now. Previously, I worked for Citigroup and Prudential. Overall, I have been part of IT industry for 30 years, and most of my professional career has been within financial sector in New York City metro area. I live in New Jersey with my wife and son, Daniel Khalil. I have a Master degree in software engineering from the University of Scranton, and Master in mathematics University of Punjab, Lahore. And currently I am pursuing TRIUM global Executive MBA. A joint program from the NYU Stern, LSE and HEC Paris. So today, I'm going to talk about building multi-cluster scalable container platform, supporting on-prem hybrid and multicloud use cases, how we leverage that with an S&P Global and what was our best story. As far as the agenda is concerned, I will go over, quickly the problem statement. Then I will mention the work of our core requirements, how we get solutioning, how Docker Enterprise helped us. And at the end, I will go over the pilot deployment for a proof of concept which we leverage. So, as far as the problem statement is concerned. Containers, as you all know, in the enterprise are becoming mainstream but expertise remains limited and challenges are mounting as containers enter production. Some companies are building skills internally and someone looking for partners that can help catalyze success, and choosing more integrated solutions that accelerate deployments and simplify the container environment. To overcome the challenges, we at S&P Global started our journey a few years back, taking advantage of both options. So, first of all, we met with all the stakeholder, application team, Product Manager and we define our core requirements. What we want out of this container platform, which supports multicloud and hybrid supporting on-prem as well. So, as you see my core requirements, we decided that we need first of all a roadmap or container strategy, providing guidelines on standards and specification. Secondly, with an S&P Global, we decided to introduce Platform as a Service approach, where we bring the container platform and provide that as a service internally to our all application team and all the Product Managers. Hosting multiple application on-prem as well as in multicloud. Third requirement was that we need Linux and Windows container support. In addition to that, we would also require hosted secure image registry with role based access control and image security scanning. In addition to that, we also started DevOps journey, so we want to have a full support of CI/CD pipeline. Whatever the solution we recommend from the architecture group, it should be easily integrated to the developer workstation. And developer workstation could be Windows, Mac or Linux. Orchestration, performance and control were few other parameter which we'll want to keep in mind. And the most important, dynamic scaling of container clusters. That was something we were also want to achieve, when we introduce this Platform as a Service. So, as far as the standard specification are concerned, we turn to the Open Container Initiative, the OCI. OCI was established in June 2015 by Docker and other leaders in the technology industry. And OCI operates under Linux Foundation, and currently contains two specification, runtime specification and image specification. So, at that time, it was a no brainer, other than to just stick with OCI. So, we are following the industry standard and specifications. Now the next step was, okay, the container platform. But what would be our runtime engine? What would be orchestration? And how we support, in our on-prem as well as in the multicloud infrastructure? So, when it comes to runtime engine, we decided to go with the Docker. Which is by default, runtime engine and Kubernetes. And if I may mention, DataDog in one of their public report, they say Docker is probably the most talked about infrastructure technology for the past few years. So, sticking to Docker runtime engine was another win-win game and we saw in future not bringing any challenge or issues. When it comes to orchestration. We prefer Kubernetes but that time there was a challenge, Kubernetes did not support Windows container. So, we wanted something which worked with a Linux container, and also has the ability or to orchestrate Windows containers. So, even though long term we want to stick to Kubernetes, but we also wanted to have a Docker swarm. When it comes to on-prem and multicloud, technically you could only support as of now, technology may change in future, but as of now, you can only support if you bring your own orchestration too. So, in our case, if we have control over orchestration control and not locked in with one cloud provider, that was the ideal situation. So, with all that, research, R&D and finding, we found Docker Enterprise. Which is securely built, share and run modern applications anywhere. So, when we come across Docker Enterprise, we were pleased to see that it meets our most of the core requirements. Whether it is coming on the developer machine, to integrating their workstation, building the application. Whether it comes to sharing those application, in a secure way and collaborating with our pipeline. And the lastly, when it comes to the running. If we run in hybrid or multicloud or edge, in Kubernetes, Docker Enterprise have the support all the way. So, three area one I just call up all the Docker Enterprise, choice, flexibility and security. I'm sure there's a lot more features in Docker Enterprise as a suite. But, when we looked at these three words very quickly, simplified hybrid orchestration. Define application centric policies and boundaries. Once you define, you're all set. Then you just maintain those policies. Manage diverse application across mixed infrastructure, with secure segmentation. Then it comes to secure software supply chain. Provenance across the entire lifecycle of apps and infrastructure through enforceable policy. Consistently manage all apps and infrastructure. And lastly, when it comes to infrastructure independence. It was easily forever lift and shift, because same time, our cloud journey was in the flight. We were moving from on-prem to the cloud. So, support for lift and shift application was one of our wishlist. And Docker Enterprise did not disappoint us. It also supported both traditional and micro services apps on any infrastructure. So, here we are, Docker Enterprise. Why Docker Enterprise? Some of the items in previous slides I mentioned. But in addition to those industry-leading platform, simplifying the IT operations, for running modern application at scale, anywhere. Docker Enterprise also has developer tools. So, the integration, as I mentioned earlier was smooth. In addition to all these tools, the main two components, the Universal Control Plane and the Docker Trusted Registry, solve lot of our problems. When it comes to the orchestration, we have our own Universal Control Plane. Which under the hood, manages Kubernetes and Docker swarm both clusters. So, guess what? We have a Windows support, through Docker swarm and we have a Linux support through Kubernetes. Now that paradigm has changed, as of today, Kubernetes support Windows container. So, guess what? We are well after the UCP, because we have our own orchestration tool, and we start managing Kubernetes cluster in Linux and introduce now, Windows as well. Then comes to the Docker Trusted Registry. Integrated Security and role based access control, made a very smooth transition from our RT storage to DTR. In addition to that, binary level scanning was another good feature from the security point of view. So that, these all options and our R&D landed the Docker Enterprise is the way to go. And if we go over the Docker Enterprise, we can spin up multiple clusters on-prem and in the cloud. And we have a one centralized location to manage those clusters. >> Khalil: So, with all that, now let's talk about how what was our pilot deployment, for proof of concept. In this diagram, you can see we, on the left side is our on-prem Data Center, on the right side is AWS, US East Coast. We picked up one region three zones. And on-prem, we picked up our Data Center, one of the Data Center in the United States of America, and we started the POC. So, our Universal Control Plane had a five nodes cluster. Docker Trusted Registry, also has a five node cluster. And the both, but in our on-prem Data Center. When it comes to the worker nodes, we have started with 18 node cluster, on the Linux side and the four node cluster on the Windows side. Because the major footprint which we have was on the Linux side, and the Windows use cases were pretty small. Also, this is just a proof of concept. And in AWS, we mimic the same web worker nodes, virtual to what we have on-prem. We have a 13 nodes cluster on Linux. And we started with four node cluster of Windows container. And having the direct connect from our Data Center to AWS, which was previously existing, so we did not have any connectivity or latency issue. Now, if you see in this diagram, you have a centralized, Universal Control Plane and your trusted registry. And we were able to spin up a cluster, on-prem as well as in the cloud. And we made this happen, end to end in record time. So later, when we deploy this in production, we also added another cloud provider. So, what you see the box on the right side, we just duplicate test that box in another cloud platform. So, now other orchestration tool, managing on-prem and multicloud clusters. Now, in your use case, you may find this little, you know, more in favor of on-prem. But that fit in our use case. Later, we did have expanded the cluster of Universal Control Plane and DTR in the cloud as well. And the clusters have gone and hundreds and thousands of worker nodes span over two cloud providers, third being discussed. And this solution has been working so far, very good. We did not see any downtime, not a single instance. And we were able to provide multicloud platform, container Platform as a Service for our S&P Global. Thank you for your time. If any questions, I have put my LinkedIn and Twitter account holder, you're welcome to ask any question

>>Live from Las Vegas. It's the cube covering UI path forward Americas 2019 brought to you by UI path. >>Welcome back to Las Vegas. Everybody, you watching the cube, the leader in live tech coverage. We go out to the events, we extract the signal from the noise. Ahmed Zion, he is here, he's the chief automation officer at accelerate a specialist service provider in this area of RPA in Armando Lambert is the vice president of enterprise optimization governance and risk guys. Oh sorry. At Bayview asset management in Miami. Welcome to the cube criminal. Thank you for that. So Bayview, you've got a good view of the Bay and Miami, is that kinda where the name comes from or the beautiful place to work happening with UI path forward to was in Miami at the Fontainebleau back here in Vegas. But um, so let's get into it. I met um, chief automation officer. That's kind of a cool title. I don't see that a lot. What's that entail? And tell us about accelerate. >>So accelerate at accelerated where one of the largest nice providers is the only thing that we do a process automation and AI company. And our sole focus has been process automation since our inception and our past lives were generalists. We did well and wanted to do it again. Uh, so when we started accelerate, we wanted to make sure that we focused on a very specific vertical niche and process automation was just starting up the uptick about mid 2016 ish. >> So there's gonna be some interesting conversations around process automation is like had an analyst on yesterday, they predicted RPA is dead, you know, process automation lives. You know, it's kind of a tongue in cheek thing. So maybe we can talk about that a little bit, but Amando tell us about your role and a little bit about Bayview. So Bayview is an asset management company, primarily whole loans, mortgage back securities, mortgage servicing rights. >>We offer service advisory as well as investment vehicles. My role basically is to strategize, innovate, look at new technologies, new ways of streamlining the business. Um, and you know, about in 2016, you know, we were faced with the challenge and the challenge was we have a lot of road swiveled to chair type work, back office, operational work. Um, and I went in there just trying to look at people, processes and systems and trying to figure out a way to make things more efficient. And you know, RPA is one of those vehicles. Okay. So smart. You started with people in process, you didn't start with the technology. Yeah, absolutely. Right. So what did you learn? I mean, take us back to 2016 when you started to do the investigation, you started unpack the processes and the people. What did you see and then what led you to RPA? >>Yeah, I mean, I think inherently you're, you're, there's a lot of business processes that are just brought down through years of just being kind of entrepreneurial and doing a lot of business. So a, of these prices of processes early on we felt like we can just go in and automate and we realized that just needed a level of process optimization first. Um, so in doing that, it just kind of directs the vehicle right into what type of automation you need to do. It's not always RPA. RPA is big, a big component for us. Um, it works for us. Early on we wanted to put a strong governance structure. I strongly believe that, you know, and it's worked out so far for us. >> So you, you brought in accelerate, you brought in an outside firm to help you with that process automation, is that right? Absolutely. >>So tell us more about how that all went down. So that was, that was an interesting, um, interesting time, right? The, these products were coming up. Nobody really knew how well they work. And so we went in and we actually did proof of value, right? We said, Hey, this is all well and good. Let's do a proof of concept that a proof of value at that time, proof of concepts really were a thing. I don't, I don't think we should do them anymore. We should only do proof of values. But we went in, looked at the various systems they had, tried it out so he could demonstrate it to his management that this thing works. And as soon as that was over, I think I'd given to her, Armando, here we went all in, right? We said, all right, let's look at the highest value things. >>Let's deliver this. Um, let's figure out a governance model. Let's, let's not, let's not hold it back like we, like we have done in the past. It project spinning up. So let's get the infrastructure up and running very quickly. Let's get, let's get a few automations out there. Some of the business sees the value right away, right? Crawl, walk, run. We can do this. You know, what are we going to automate and what do we need from it and how are we going to govern this? These are the three pillars that I see that I suggest everybody look at it. And we did that in parallel parallel streams and all three of them. And within a few months he was able to return a significant value back to the business, which has led to adoption. I think, I think that has been a very big reason why he's been able to scale because he was able to show early value back to the business very quickly focusing on value rather than the technology or the underlying solution. >>Right? It's um, a lot of times we see folks going into RPA saying, what can RPA do for me? I think that is the wrong question. Um, the question really is what do you do? Let's classify what you do in manual mechanical work, intelligent work and wasteful work, right? And then look at your toolbox. I have RPA, I have AI, I have other technologies that within an enterprise folks are working on, and then apply those to it. RPA becomes the glue for most of these things. You have API as SDKs. You have AI technologies, be it cloud or on prem. RPA becomes the glue and it becomes easy to deploy once you figured out what all the different pieces are. But it's important to look at the process first and say, what? What do you do? So when the business comes back and say, what can you do for me with RPA? >>I said, no, I don't know. What can you do for, with the, I don't know. Tell me what you do and then I'll tell you what the solution is. So mono, given that you started with the value, did that ease some of those potential friction that you sometimes see with change management or change in general? Or did you still see that resistance? And I'm interested in where you started, what were some of those high value areas that you attack but, but the cultural piece first if you will. Yeah, I mean a lot of marketing, you know, it's really what it comes down to trying to prove to the Csuite and managing director areas. Like this is a value proposition. You know, early on, you know, we did a lot of presenting roundtables, luncheon learns with the business. You know, because there is some resistance early on. >>I think everybody has a misconception that it's going to take their jobs where I believe it's gonna create a lot more jobs in the future. Um, for me it was always a scalability play. You know, how can our business do more for less? And that's really what we really wanted to get to. Throughout that journey. We realized there's a lot of benefit, especially for companies that have a heavy back office operations. Um, and we just started, like I mentioned there, we started slow. I didn't want to boil the ocean. I knew I needed to prove to leadership that this works. And I think about three years ago, we all kind of felt, is this going to stick? You know, we've seen technology, I've been in technology for over 20 years and you know, some things fly, some things don't. Right? So we wanted to prove that it worked. >>And you know, the industry just kind of surrounded itself around that. And look where we are now. I think everybody's putting a lot of money in their budgets for, you know, intelligent automation, not just RPA. So the initiative was kind of middle up to the C suite and then top down. Is that how it, absolutely. I'm a firm believer the tone needs to come from the top. It has to come from the top. And you know, luckily for me, I have great leaders in our company. Um, they understood the vision, they understand what, what it could potentially mean for their business. They just needed someone to help execute it. So what kinds of things did you start with? There was a lot of sort of manual form filling out or some of that, uh, you know, data extraction from PDFs using, utilizing OCR, you know, RPAs great to gather and collect data so that they can put it in their models and make more informed decisions. >>Uh, claims processes, you know, dealing with different agencies. So, you know, early on in adopting UI path, there were some limitations. We worked around that. Now it's pretty much limitless and they could touch any system, any technology, any process. So yeah, it's growing tremendously. And in terms of just ensuring governance and compliance as you scale, you have robots doing that. Um, how do you tell me what we're working more and more. I mean, I think regulators now realize, okay, you're removing the human element, right? So, you know, that's a big value as well. Or sampling. Now you're not limited to what you can sample. You can sample 100%, you know, so those are big values and when you speak to regulators, they really understand that I would say five years ago, I'm not so sure. Um, but now they welcome it. And I think a lot of the government agencies now are, are adopting RPA. >>Uh, so it's, it's a good story. Well, automation kill sampling is that I think it is absolutely right. The point actually interesting point that you made, right? Uh, the regulators or the auditors or for that matter, the security and the compliance guys inside the enterprise have this. So this term of the bot, right has this connotation of Terminator and I keep telling him, no, this is that thing. You buy a target that does this. I press the right button, it goes right up, press the left button, mil goes left. It just doesn't think on its own. And I think that conversation is very important, right? Once you have that conversation with the security and the compliance guys to say, this is a bot, it only does what you ask it to do. You could put a social security number in front of this guy all day long in front of this user ID all day long. >>It just doesn't know what to do with it. Won't ever read it. And once they realize that they, the, the conversation changes, um, you know, especially when it in compliance and audit, right? Uh, the compliance officers would love this. Once you tell them there's a lot of decision making that happened in people's heads or Excel spreadsheets that never made it to systems and was never logged. So you'd get something in you massage that, you did that, and you put that in the system. That decision making is now auditable. So you can go back and say, here was the input, here was the massaging of it. Here's what went into the system of record after it came in. So that I think, I think those conversations early on really helped this scale in an age old problem and tribal knowledge. Exactly. You know, Joe has his spreadsheet and Fred knows the Joe has the spreadsheet. >>So when Joe leaves, he has to get the spreadsheet back. And that's kind of this perpetual thing. How much of what you guys did, Armando was processed re-engineering versus just applying automation at some low hanging fruit. Um, I think looking back now it's about a 50, 50 split. Um, you know, there are some areas that have robust processes and that makes our life easier. We can just kind of go in, map it out, look at the automation future state and deploy, develop and deployed. Uh, you know, some areas, you know, they inherit processes and they don't always just so busy doing their day jobs and they don't always realize there's, there's room for efficiency in their process. So, you know, early on when we priced out how much this would cost, how much development it would be, we didn't always factor in that it would be a 50, 50 split and doing a lot more process improvement in the beginning. >>Um, we've now counted for that. So absolutely. It's about a 50, 50 split. Craig LeClaire this morning said something that, you know, I was an analyst and he says, very, you know, very analyst's sort of savings. You've got to stop worrying about the ROI, you know, focus on the more strategic stuff. Every analyst sort of says that. But yeah, there weren't a lot of CFOs too. And they're like, where's the ROI? So you know, you're in the services business, you know, you have to have ROI dollars matter. Absolutely. So you obviously measure ROI. How do you look at it? You know what you said earlier, you're not cutting jobs, right? But so what do you tick? How do you measure kind of the, the value, the ROI? I mean, you know, giving the end user a little more to think about, right? Giving them the opportunity to, you know, do more, be more thoughtful in what their day to day job is rather than doing the swivel chair type work. >>So, you know, the measurement, the beauty around RPA is it's very quantifiable. You know, unlike some traditional it systems, you really can, the data doesn't always kick back. You know, all our, our, our own bots, all our processes kickback, they give us data that we can quantify, um, metrics on, on, on volume versus man hours. This is all information you capture early on. You need to do this at the discovery stage and we train. We have a robust training program for our business analysts and program managers and developers and they're always, that's the question they ask every time. It's not just about what is your process, your cute future, current state, future state, and it's like, how many limit? Let me look at your historical trending. What are their volumes look like? You know, our business is very cyclical. It goes up and down, and when I mentioned I want them to be scalable and have more capacity, that's really the play for me. >>For me, it's never been an FTE. I get it. It may come from the Csuite, but like I said, the tone from the top has been solid. Their vision is more about, Hey, when it's cyclical and it goes up and down, we need to be able to do more. We need to be able to scale. Have you been able to measure productivity improvement? Absolutely. Absolutely we have. If you had a Mulligan, what would you do differently? A good question. I mean, I think we factored early on, I mentioned this early on how much process improvement was needed. I think we undervalued that. And um, you know, every business faces the same challenges, right? They, you know, everyone feels like they're doing the right thing. These processes are inherited. You know, regulations change, investors change. There's new business rules every day, you know, and you kind of need to sit back as a business user every now and then and refresh that. >>And um, you know, we didn't account for that early on. We're helping the business do that. Our business is fantastic. They bought into the program and it's like having additional workforce working on your side. You know, Daniel Dienes in his keynote last night, basically sending them pick up on something you guys said is, is, um, he really appreciates those customers who took a chance early on. He goes, because frankly, our product wasn't, you know, fully, fully baked out. And I was like, wow, what an honest statement from a CEO. You don't usually hear that. My sense is that they got it right. You path. And I'd love your comments. In the sense that they attack, they went after simplicity and said, okay, make it easy to adopt and then we'll figure it out. And then, you know, bringing in the functionality is that, is that kind of what happened or picking up on Daniel? >>And by the way it was, it's amazing. Humility really comes through, right? So I saw him 2016 standing on stage and when my partner came to us for the idea of saying, Hey, we're going to do, we should do this RPA thing. Now I'm giving away my age. But 1998, my first job, I was sitting in front of the computer and Prudential and they put this software in front of me. It was called SQA robot. It was a test automation tool. It was called SQL robot. Uh, why that relates to Daniel is he's had a, came on the stage in the IRPA conference in 2016 if remember, I love this presentation just to blues black thing and few words on it. He goes, let's not kid ourselves. We have this very traditional, you know, QA automation technology that we think can do something really super. >>And I have built a product on top of that, but there's, there's not a lot of magic in here yet. Right. So that's, but, but I think the, the, the great thing about you I've had has been the vision, right? The vision has been, and if you saw yesterday they started with the core and unlike some of the other vendors, they said, we're just going to do RPA really well. We're not going to go into the OCR market. We're not going to try to build AI things. Let's make sure that our core RPA, so you know, you want to go, you're an enterprise, you want to do OCR, you're not going to buy it from an RPA company. You want to buy it from somebody who's been doing it for 30 years or we just has that sole focus. I think you'll have had had that sole focus. >>But as I've seen in the past three, four years, they've just done a great job with the, with the full vision, right. Starting from, they started with the middle of the core of the product and they said, okay, let's go towards the business and see what the business needs with, you know, planning of their, um, of their automations on and so forth and going further to the right to say, let us enable the technology guys who actually implement this to give them the tools and the integrations they need to, to actually make this routed to full product. Um, I think it's a very good question when people say, what can you do with RPA for me? So I said that answer was very different three years ago than it is today. Right? Some of the things are coming out of the box with these. So I, I, I predict that in the next few years, document understanding and natural language and all of that will just be built in today's still very sort of clunky in terms of how you do it. >>But I think those things are coming, coming together. So looking at processes that way is really important. It's a lot of runway for this. Margaret, Armando, I'll give you the last word. Where do you see are RPA or intelligent automation going in, in your organization? Is it still early days you had a lot more adoption or you're pretty much, you know, settled? No, definitely not settled. Um, I think it's, you know, RPA is just one of the tools in the spectrum of intelligent automation. So more integration, more API APIs, a lot of machine learning, uh, eventually some AI. Um, so yeah, we are not slowing down. There's a lot of opportunity. My mandate as I mentioned before, is just scale, scale, scale. So you know, the process is working. We have a good program in place. We'll continue marching forward. Great guys, thanks so much for coming. Thank you for sharing your story. Thank you for watching. From right back with the cube. Live from UI path forward three in Las Vegas. Right back.

>> Woman: From the heart of Silicon Valley, it's theCUBE; covering CloudNOW's Seventh Annual Top Women Entrepreneurs in Cloud Innovation Awards. (dramatic music) >> Hi, Lisa Martin with theCUBE on the ground at Facebook Headquarters. We're here for the Seventh Annual CloudNOW Top Women Entrepreneurs in Cloud Innovation event. Welcoming, one of the award-winners tonight, to the program, we've got Sce Pike, the founder and CEO of IOTAS. Sce, it's so great to have you here, and congratulations on your award. >> Thank you so much, Lisa. >> So IOTAS's cool software. >> Mm hmm. >> Tell us about that. This is for the Smart Apartments. These days we're so used to being able to talk to any device and have it control things. Smart cities are our big thing, smart everything. Tell us about IOTAS. What do you guys do when the impetus for the technology. >> Sure, I really believe that the future of smart home is actually something that is not just four walls and a roof, but actually something that is aware of you. So, aware of you and knows your preferences and settings, and actually knows everything about you and wants to actually be an ally to you, and actually can differentiate between you, and your family and friends, and potentially an intruder. And so, the only way you're going to get there is to actually work with early adopters of technology. This is when we start identifying the real estate industry with multi-family where all the early adopters were living, right, because only 30 percent of Millennials own homes. And so, we thought about this and said, "Okay, well, how are we going to actually get to those millennials?" And then a real estate developer actually approached us, saying, "Hey, I want technology differentiation for my building that I'm creating, 200 units in Portland Oregon," which is where I'm from, and said, "I want to have something different." And that's when I was like, "Oh, this is the opportunity to actually work with the real estate industry to put it into the fabric of the buildings." And that's when I got really excited when we can actually make a true smart home that has all the lights, all the outlets, all the locks, voice as you mentioned, and everything that is an experience versus just on, off. >> That's so interesting. I looked at your Web site and saw the journal and how it's talking about something that you mentioned, this awareness and learning the individuals and being able to have the intelligence to distinguish. >> Is it called stories on the website? >> Those are stories, those are the automations, so that you can have a good night story, good morning, welcome home; so everything just works for people who are moving into our apartments. They download the app within 30 seconds. They can see everything that they can control, but they can see also, all the pre-programmed automation as well. But the other notion of what we are creating is something called a living profile. And this is really relevant from a CloudNOW perspective, is that the living profile travels with you from place to place to place. So we are not only doing smart apartments but we're also working in student housing, military housing, senior living, and starting to go into single family home as well. So for us, the notion is that these smart homes, all your settings preferences, your routines, your habits, travel with you from place to place to place, eventually to hotels, to cars, working spaces, hotels, short term vacation rentals and such. >> Wow! That's phenomenal. So this is an interesting kind of collaboration between the real estate industry and some technologists. >> Exactly. Exactly. >> I love that you were approached by a real estate developer who said, "I want to have a differentiation for my business." >> Exactly. Was that sort of a surprise to you thinking, you understand tech, you have a really cool background in anthropology as well as electronic arts, but there must have been sort of an interesting opportunity going, "Well, there's a huge opportunity in the market here >> Yeah. >> that we can help tech really kick the doors wide open on real estate. >> Yes. Exactly. My previous company, Citizen, which I sold to Ernst and Young, is known for connected technology. So we were developing connected technologies in cars, in healthcare and fintech, and we were looking at smart homes for single family home. And so, for us, when that real estate developer approached us, looked at the market, saw that the market is huge. It's $500 billion to a trillion dollars, just for multi-family home alone, it's an absolutely a large market, and then realized that this was truly an opportunity to scale smart home and IoT devices in a meaningful way because you're not just selling one device, one home, not even one building, but you're selling entire portfolios of companies like Prudential or JP Morgan. All the funds that you hear about, they're all real estate funds, right? And they're changing hands 40% of the ... A 40% of the fund is changing hands every year. That means they are buying and selling, and as they're buying and selling, they're adding technology into these buildings. >> Wow! That's so interesting. So, I want to kind of pivot a little bit into your background. I mentioned anthropology degree and electronic arts. And you have, I was asking you before we went live, I love stories like that where there's a ... I hear it wasn't a STEM kit, but you have some really cool influences that your anthropology background has delivered to, not just your career but also the technology that you guys are delivering. Tell us a little bit about that. Sure. So, anthropology is a study in human behavior, right? There's physical anthropology and cultural anthropology. Physical anthropology is now considered almost like evolutionary psychology. And so that actually allowed me because I've always been curious about human; human nature, why people do things, and that actually led my career into this interesting path of user experience design. And electronic arts actually taught me how to code as well as design on the computer. And when I graduated from college in the late '90s and moved to Silicon Valley, everybody's like, "I need somebody who could code and design all these Internet sites." So I ended up actually designing the first GM e-commerce site, the first HP's e-commerce sites, and that actually was not a direct path. I never thought I'd be making websites or working in an Internet, but it was an interesting path to get there. So you're right, it doesn't have to be this straight and like you got to be in computer science. There's so many different avenues to think about how technology needs a different point of view, right, from an art background or an anthropology background, and I think that's where there's an opportunity to bring in women or girls in a different way that still goes into STEM. So steam is a huge portion of what I support. >> Yes. And you talked about, it's just different points of view, it's thought diversity, even. >> Yes. >> Tell us a little bit about the culture that you're building at IOTAS and where, maybe even some of the softer skills >> Sure. >> are key to enabling you guys to do market expansion and accomplish some pretty big goals? >> Yeah. I mean, culturally, I love my team. I think one of the things that we always strive for, though, is the ability to always give back to the community as well. So we have like, events, as well as like, once a month, everyone has like, a give-back Wednesday, right? So they can go and volunteer and do other things that is outside of just their work life, right? And so that's just one of the things that we do and that allows them to just step away from their daily activity of being driven by just the startup mentality or the startup life and just go build something, and we do this a lot, Habitats for Humanities, right? We go build homes, real homes, and we always think we should offer these homes as smart home technology. But those are the things that I think really impact who we are. The other thought I had was I travel a lot. And I had this moment where I was getting on a plane. I was looking at the pilot, I was going, "Oh gosh! So much of my life is dependent on white men, and, unfortunately, like, my investors, my board members, all my executive staff, my husband, and I was thinking, "I need to change something. I'll keep the husband." (Lisa laughs) But we (chuckles) recently added a female board member who has a cybersecurity background. I'm recruiting for a female CFO and COO as well, and I'm trying to change up my executive staff, change up my investors, change up my board 'cause this is not something that you think about, coming from my generation which is a little bit older. You just need to do what you need to do to get it done, you don't think about yourself as a female entrepreneur. I thought of myself as an entrepreneur. I think of myself as a CEO. I don't have this like, "I'm a female entrepreneur." And so you sometimes forget to support other diversity in this environment, and that's kind of this moment of realization as I was getting on the plane, "I got to change something." Right? And so, our staff is more than 40% female. I'm trying to change that a little bit more. That's one of the key things that I think is a strength of having just representation. >> And maybe one of these days, you said your point: It won't matter, you will just be able to be a CEO, an entrepreneur. >> exactly. >> One more thing, since you're recruiting, where can people to go to find out more information about the opportunities? >> Sure, they can come to our site, reach out or contact at iotashome.com. That would be the best way to reach us. >> Excellent. Well, Sce, congratulations on the award. >> Thank you. >> And for what you're doing to help revolutionize the real estate tech industry. It's such interesting technology to make it aware and personal. Thanks for your time. >> Cool. >> Thank you so much, Lisa. We want to thank you for watching theCUBE. I'm Lisa Martin, at Facebook Headquarters. Thanks for watching. (dramatic music)