>> Announcer: From around the globe, it's theCUBE presenting Enterprise Digital Resilience on Hybrid and multicloud brought to you by io/tahoe >> Hello everyone, and welcome to our continuing series covering data automation brought to you by io/tahoe. Today we're going to look at how to ensure enterprise resilience for hybrid and multicloud, let's welcome in Ajay Vohora who's the CEO of io/tahoe Ajay, always good to see you again, thanks for coming on. >> Great to be back David, pleasure. >> And he's joined by Fadzi Ushewokunze, who is a global principal architect for financial services, the vertical of financial services at Red Hat. He's got deep experiences in that sector. Welcome Fadzi, good to see you. >> Thank you very much. Happy to be here. >> Fadzi, let's start with you. Look, there are a lot of views on cloud and what it is. I wonder if you could explain to us how you think about what is a hybrid cloud and how it works. >> Sure, Yeah. So, a hybrid cloud is an IT architecture that incorporates some degree of workload portability, orchestration and management across multiple clouds. Those clouds could be private clouds or public clouds or even your own data centers. And how does it all work? It's all about secure interconnectivity and on demand allocation of resources across clouds. And separate clouds can become hybrid when you're seamlessly interconnected. And it is that interconnectivity that allows the workloads to be moved and how management can be unified and orchestration can work. And how well you have these interconnections has a direct impact of how well your hybrid cloud will work. >> Okay, so well Fadzi, staying with you for a minute. So, in the early days of cloud that term private cloud was thrown around a lot. But it often just meant virtualization of an on-prem system and a network connection to the public cloud. Let's bring it forward. What, in your view does a modern hybrid cloud architecture look like? >> Sure, so, for modern hybrid clouds we see that teams or organizations need to focus on the portability of applications across clouds. That's very important, right. And when organizations build applications they need to build and deploy these applications as a small collections of independently loosely coupled services. And then have those things run on the same operating system, which means in other words, running it all Linux everywhere and building cloud native applications and being able to manage it and orchestrate these applications with platforms like Kubernetes or Red Hat OpenShift, for example. >> Okay, so, Fadzi that's definitely different from building a monolithic application that's fossilized and doesn't move. So, what are the challenges for customers, you know, to get to that modern cloud is as you've just described it as it skillsets, is it the ability to leverage things like containers? What's your View there? >> So, I mean, from what we've seen around the industry especially around financial services where I spend most of my time. We see that the first thing that we see is management, right. Now, because you have all these clouds, you know, all these applications. You have a massive array of connections, of interconnections. You also have massive array of integrations portability and resource allocation as well. And then orchestrating all those different moving pieces things like storage networks. Those are really difficult to manage, right? So, management is the first challenge. The second one is workload placement. Where do you place this cloud? How do you place these cloud native operations? Do you, what do you keep on site on prem and what do you put in the cloud? That is the other challenge. The major one, the third one is security. Security now becomes the key challenge and concern for most customers. And we're going to talk about how to address that. >> Yeah, we're definitely going to dig into that. Let's bring Ajay into the conversation. Ajay, you know, you and I have talked about this in the past. One of the big problems that virtually every company face is data fragmentation. Talk a little bit about how io/tahoe, unifies data across both traditional systems, legacy systems and it connects to these modern IT environments. >> Yeah, sure Dave. I mean, a Fadzi just nailed it there. It used to be about data, the volume of data and the different types of data, but as applications become more connected and interconnected the location of that data really matters. How we serve that data up to those apps. So, working with Red Hat and our partnership with Red Hat. Being able to inject our data discovery machine learning into these multiple different locations. whether it be an AWS or an IBM cloud or a GCP or on prem. Being able to automate that discovery and pulling that single view of where is all my data, then allows the CIO to manage cost. They can do things like, one, I keep the data where it is, on premise or in my Oracle cloud or in my IBM cloud and connect the application that needs to feed off that data. And the way in which we do that is machine learning that learns over time as it recognizes different types of data, applies policies to classify that data and brings it all together with automation. >> Right, and one of the big themes that we've talked about this on earlier episodes is really simplification, really abstracting a lot of that heavy lifting away. So, we can focus on things Ajay, as you just mentioned. I mean, Fadzi, one of the big challenges that of course we all talk about is governance across these disparate data sets. I'm curious as your thoughts how does Red Hat really think about helping customers adhere to corporate edicts and compliance regulations? Which of course are particularly acute within financial services. >> Oh yeah, yes. So, for banks and payment providers like you've just mentioned there. Insurers and many other financial services firms, you know they have to adhere to a standard such as say a PCI DSS. And in Europe you've got the GDPR, which requires stringent tracking, reporting, documentation and, you know for them to, to remain in compliance. And the way we recommend our customers to address these challenges is by having an automation strategy, right. And that type of strategy can help you to improve the security on compliance of of your organization and reduce the risk out of the business, right. And we help organizations build security and compliance from the start with our consulting services, residencies. We also offer courses that help customers to understand how to address some of these challenges. And there's also, we help organizations build security into their applications with our open source middleware offerings and even using a platform like OpenShift, because it allows you to run legacy applications and also containerized applications in a unified platform. Right, and also that provides you with, you know with the automation and the tooling that you need to continuously monitor, manage and automate the systems for security and compliance purposes. >> Ajay, anything, any color you could add to this conversation? >> Yeah, I'm pleased Fadzi brought up OpenShift. I mean we're using OpenShift to be able to take that security application of controls to the data level and it's all about context. So, understanding what data is there, being able to assess it to say, who should have access to it, which application permission should be applied to it. That's a great combination of Red Hat and io/tahoe. >> Fadzi, what about multi-cloud? Doesn't that complicate the situation even further, maybe you could talk about some of the best practices to apply automation across not only hybrid cloud, but multi-cloud as well. >> Yeah, sure, yeah. So, the right automation solution, you know can be the difference between, you know cultivating an automated enterprise or automation carries. And some of the recommendations we give our clients is to look for an automation platform that can offer the first thing is complete support. So, that means have an automation solution that provides, you know, promotes IT availability and reliability with your platform so that, you can provide enterprise grade support, including security and testing integration and clear roadmaps. The second thing is vendor interoperability in that, you are going to be integrating multiple clouds. So, you're going to need a solution that can connect to multiple clouds seamlessly, right? And with that comes the challenge of maintainability. So, you're going to need to look into a automation solution that is easy to learn or has an easy learning curve. And then, the fourth idea that we tell our customers is scalability. In the hybrid cloud space, scale is the big, big deal here. And you need to deploy an automation solution that can span across the whole enterprise in a consistent manner, right. And then also that allows you finally to integrate the multiple data centers that you have. >> So, Ajay, I mean, this is a complicated situation for if a customer has to make sure things work on AWS or Azure or Google. They're going to spend all their time doing that. What can you add to really just simplify that multi-cloud and hybrid cloud equation. >> Yeah, I can give a few customer examples here. One being a manufacturer that we've worked with to drive that simplification. And the real bonuses for them has been a reduction in cost. We worked with them late last year to bring the cost spend down by $10 million in 2021. So, they could hit that reduced budget. And, what we brought to that was the ability to deploy using OpenShift templates into their different environments, whether it was on premise or in, as you mentioned, AWS. They had GCP as well for their marketing team and across those different platforms, being able to use a template, use prebuilt scripts to get up and running and catalog and discover that data within minutes. It takes away the legacy of having teams of people having to jump on workshop calls. And I know we're all on a lot of teams zoom calls. And in these current times. They're just simply using enough hours of the day to manually perform all of this. So, yeah, working with Red Hat, applying machine learning into those templates, those little recipes that we can put that automation to work regardless which location the data's in allows us to pull that unified view together. >> Great, thank you. Fadzi, I want to come back to you. So, the early days of cloud you're in the Big Apple, you know financial services really well. Cloud was like an evil word and within financial services, and obviously that's changed, it's evolved. We talk about the pandemic has even accelerated that. And when you really dug into it, when you talk to customers about their experiences with security in the cloud, it was not that it wasn't good, it was great, whatever, but it was different. And there's always this issue of skill, lack of skills and multiple tools, set up teams. are really overburdened. But in the cloud requires, you know, new thinking you've got the shared responsibility model. You've got to obviously have specific corporate, you know requirements and compliance. So, this is even more complicated when you introduce multiple clouds. So, what are the differences that you can share from your experiences running on a sort of either on prem or on a mono cloud or, you know, versus across clouds? What, do you suggest there? >> Sure, you know, because of these complexities that you have explained here mixed configurations and the inadequate change control are the top security threats. So, human error is what we want to avoid, because as you know, as your clouds grow with complexity then you put humans in the mix. Then the rate of errors is going to increase and that is going to expose you to security threats. So, this is where automation comes in, because automation will streamline and increase the consistency of your infrastructure management also application development and even security operations to improve in your protection compliance and change control. So, you want to consistently configure resources according to a pre-approved, you know, pre-approved policies and you want to proactively maintain them in a repeatable fashion over the whole life cycle. And then, you also want to rapidly the identify system that require patches and reconfiguration and automate that process of patching and reconfiguring. So that, you don't have humans doing this type of thing, And you want to be able to easily apply patches and change assistance settings according to a pre-defined base like I explained before, you know with the pre-approved policies. And also you want ease of auditing and troubleshooting, right. And from a Red Hat perspective we provide tools that enable you to do this. We have, for example a tool called Ansible that enables you to automate data center operations and security and also deployment of applications. And also OpenShift itself, it automates most of these things and obstruct the human beings from putting their fingers and causing, you know potentially introducing errors, right. Now, in looking into the new world of multiple clouds and so forth. The differences that we're seeing here between running a single cloud or on prem is three main areas, which is control, security and compliance, right. Control here, it means if you're on premise or you have one cloud you know, in most cases you have control over your data and your applications, especially if you're on prem. However, if you're in the public cloud, there is a difference that the ownership it is still yours, but your resources are running on somebody else's or the public clouds, EWS and so forth infrastructure. So, people that are going to do these need to really, especially banks and governments need to be aware of the regulatory constraints of running those applications in the public cloud. And we also help customers rationalize some of these choices. And also on security, you will see that if you're running on premises or in a single cloud you have more control, especially if you're on prem. You can control the sensitive information that you have. However, in the cloud, that's a different situation especially from personal information of employees and things like that. You need to be really careful with that. And also again, we help you rationalize some of those choices. And then, the last one is compliance. As well, you see that if you're running on prem on single cloud, regulations come into play again, right? And if you're running on prem, you have control over that. You can document everything, you have access to everything that you need, but if you're going to go to the public cloud again, you need to think about that. We have automation and we have standards that can help you you know, address some of these challenges. >> So, that's really strong insights, Fadzi. I mean, first of all Ansible has a lot of market momentum, you know, Red Hat's done a really good job with that acquisition. Your point about repeatability is critical, because you can't scale otherwise. And then, that idea you're putting forth about control, security and compliance. It's so true, I called it the shared responsibility model. And there was a lot of misunderstanding in the early days of cloud. I mean, yeah, maybe AWS is going to physically secure the you know, the S3, but in the bucket but we saw so many misconfigurations early on. And so it's key to have partners that really understand this stuff and can share the experiences of other clients. So, this all sounds great. Ajay, you're sharp, financial background. What about the economics? You know, our survey data shows that security it's at the top of the spending priority list, but budgets are stretched thin. I mean, especially when you think about the work from home pivot and all the areas that they had to, the holes that they had to fill there, whether it was laptops, you know, new security models, et cetera. So, how to organizations pay for this? What's the business case look like in terms of maybe reducing infrastructure costs, so I can pay it forward or there's a there's a risk reduction angle. What can you share there? >> Yeah, I mean, that perspective I'd like to give here is not being multi-cloud as multi copies of an application or data. When I think back 20 years, a lot of the work in financial services I was looking at was managing copies of data that were feeding different pipelines, different applications. Now, what we're seeing at io/tahoe a lot of the work that we're doing is reducing the number of copies of that data. So that, if I've got a product lifecycle management set of data, if I'm a manufacturer I'm just going to keep that at one location. But across my different clouds, I'm going to have best of breed applications developed in-house, third parties in collaboration with my supply chain, connecting securely to that single version of the truth. What I'm not going to do is to copy that data. So, a lot of what we're seeing now is that interconnectivity using applications built on Kubernetes that are decoupled from the data source. That allows us to reduce those copies of data within that you're gaining from a security capability and resilience, because you're not leaving yourself open to those multiple copies of data. And with that come cost of storage and a cost to compute. So, what we're saying is using multi-cloud to leverage the best of what each cloud platform has to offer. And that goes all the way to Snowflake and Heroku on a cloud managed databases too. >> Well and the people cost too as well. When you think about, yes, the copy creep. But then, you know, when something goes wrong a human has to come in and figure it out. You know, you brought up Snowflake, I get this vision of the data cloud, which is, you know data. I think we're going to be rethinking Ajay, data architectures in the coming decade where data stays where it belongs, it's distributed and you're providing access. Like you said, you're separating the data from the applications. Applications as we talked about with Fadzi, much more portable. So, it's really the last 10 years it'd be different than the next 10 years ago Ajay. >> Definitely, I think the people cost reduction is used. Gone are the days where you needed to have a dozen people governing, managing byte policies to data. A lot of that repetitive work, those tasks can be in part automated. We're seen examples in insurance where reduced teams of 15 people working in the back office, trying to apply security controls, compliance down to just a couple of people who are looking at the exceptions that don't fit. And that's really important because maybe two years ago the emphasis was on regulatory compliance of data with policies such as GDPR and CCPA. Last year, very much the economic effect to reduce head counts and enterprises running lean looking to reduce that cost. This year, we can see that already some of the more proactive companies are looking at initiatives, such as net zero emissions. How they use data to understand how they can become more, have a better social impact and using data to drive that. And that's across all of their operations and supply chain. So, those regulatory compliance issues that might have been external. We see similar patterns emerging for internal initiatives that are benefiting that environment, social impact, and of course costs. >> Great perspectives. Jeff Hammerbacher once famously said, the best minds of my generation are trying to get people to click on ads and Ajay those examples that you just gave of, you know social good and moving things forward are really critical. And I think that's where data is going to have the biggest societal impact. Okay guys, great conversation. Thanks so much for coming to the program. Really appreciate your time. >> Thank you. >> Thank you so much, Dave. >> Keep it right there, for more insight and conversation around creating a resilient digital business model. You're watching theCube. (soft music)

>> Announcer: From around the globe, it's theCUBE presenting Enterprise Digital Resilience on Hybrid and multicloud brought to you by io/tahoe >> Hello everyone, and welcome to our continuing series covering data automation brought to you by io/tahoe. Today we're going to look at how to ensure enterprise resilience for hybrid and multicloud, let's welcome in Ajay Vohora who's the CEO of io/tahoe Ajay, always good to see you again, thanks for coming on. >> Great to be back David, pleasure. >> And he's joined by Fadzi Ushewokunze, who is a global principal architect for financial services, the vertical of financial services at Red Hat. He's got deep experiences in that sector. Welcome Fadzi, good to see you. >> Thank you very much. Happy to be here. >> Fadzi, let's start with you. Look, there are a lot of views on cloud and what it is. I wonder if you could explain to us how you think about what is a hybrid cloud and how it works. >> Sure, Yeah. So, a hybrid cloud is an IT architecture that incorporates some degree of workload portability, orchestration and management across multiple clouds. Those clouds could be private clouds or public clouds or even your own data centers. And how does it all work? It's all about secure interconnectivity and on demand allocation of resources across clouds. And separate clouds can become hybrid when you're seamlessly interconnected. And it is that interconnectivity that allows the workloads to be moved and how management can be unified and orchestration can work. And how well you have these interconnections has a direct impact of how well your hybrid cloud will work. >> Okay, so well Fadzi, staying with you for a minute. So, in the early days of cloud that term private cloud was thrown around a lot. But it often just meant virtualization of an on-prem system and a network connection to the public cloud. Let's bring it forward. What, in your view does a modern hybrid cloud architecture look like? >> Sure, so, for modern hybrid clouds we see that teams or organizations need to focus on the portability of applications across clouds. That's very important, right. And when organizations build applications they need to build and deploy these applications as a small collections of independently loosely coupled services. And then have those things run on the same operating system, which means in other words, running it all Linux everywhere and building cloud native applications and being able to manage it and orchestrate these applications with platforms like Kubernetes or Red Hat OpenShift, for example. >> Okay, so, Fadzi that's definitely different from building a monolithic application that's fossilized and doesn't move. So, what are the challenges for customers, you know, to get to that modern cloud is as you've just described it as it skillsets, is it the ability to leverage things like containers? What's your View there? >> So, I mean, from what we've seen around the industry especially around financial services where I spend most of my time. We see that the first thing that we see is management, right. Now, because you have all these clouds, you know, all these applications. You have a massive array of connections, of interconnections. You also have massive array of integrations portability and resource allocation as well. And then orchestrating all those different moving pieces things like storage networks. Those are really difficult to manage, right? So, management is the first challenge. The second one is workload placement. Where do you place this cloud? How do you place these cloud native operations? Do you, what do you keep on site on prem and what do you put in the cloud? That is the other challenge. The major one, the third one is security. Security now becomes the key challenge and concern for most customers. And we're going to talk about how to address that. >> Yeah, we're definitely going to dig into that. Let's bring Ajay into the conversation. Ajay, you know, you and I have talked about this in the past. One of the big problems that virtually every company face is data fragmentation. Talk a little bit about how io/tahoe, unifies data across both traditional systems, legacy systems and it connects to these modern IT environments. >> Yeah, sure Dave. I mean, a Fadzi just nailed it there. It used to be about data, the volume of data and the different types of data, but as applications become more connected and interconnected the location of that data really matters. How we serve that data up to those apps. So, working with Red Hat and our partnership with Red Hat. Being able to inject our data discovery machine learning into these multiple different locations. whether it be an AWS or an IBM cloud or a GCP or on prem. Being able to automate that discovery and pulling that single view of where is all my data, then allows the CIO to manage cost. They can do things like, one, I keep the data where it is, on premise or in my Oracle cloud or in my IBM cloud and connect the application that needs to feed off that data. And the way in which we do that is machine learning that learns over time as it recognizes different types of data, applies policies to classify that data and brings it all together with automation. >> Right, and one of the big themes that we've talked about this on earlier episodes is really simplification, really abstracting a lot of that heavy lifting away. So, we can focus on things Ajay, as you just mentioned. I mean, Fadzi, one of the big challenges that of course we all talk about is governance across these disparate data sets. I'm curious as your thoughts how does Red Hat really think about helping customers adhere to corporate edicts and compliance regulations? Which of course are particularly acute within financial services. >> Oh yeah, yes. So, for banks and payment providers like you've just mentioned there. Insurers and many other financial services firms, you know they have to adhere to a standard such as say a PCI DSS. And in Europe you've got the GDPR, which requires stringent tracking, reporting, documentation and, you know for them to, to remain in compliance. And the way we recommend our customers to address these challenges is by having an automation strategy, right. And that type of strategy can help you to improve the security on compliance of of your organization and reduce the risk out of the business, right. And we help organizations build security and compliance from the start with our consulting services, residencies. We also offer courses that help customers to understand how to address some of these challenges. And there's also, we help organizations build security into their applications with our open source middleware offerings and even using a platform like OpenShift, because it allows you to run legacy applications and also containerized applications in a unified platform. Right, and also that provides you with, you know with the automation and the tooling that you need to continuously monitor, manage and automate the systems for security and compliance purposes. >> Ajay, anything, any color you could add to this conversation? >> Yeah, I'm pleased Fadzi brought up OpenShift. I mean we're using OpenShift to be able to take that security application of controls to the data level and it's all about context. So, understanding what data is there, being able to assess it to say, who should have access to it, which application permission should be applied to it. That's a great combination of Red Hat and io/tahoe. >> Fadzi, what about multi-cloud? Doesn't that complicate the situation even further, maybe you could talk about some of the best practices to apply automation across not only hybrid cloud, but multi-cloud as well. >> Yeah, sure, yeah. So, the right automation solution, you know can be the difference between, you know cultivating an automated enterprise or automation carries. And some of the recommendations we give our clients is to look for an automation platform that can offer the first thing is complete support. So, that means have an automation solution that provides, you know, promotes IT availability and reliability with your platform so that, you can provide enterprise grade support, including security and testing integration and clear roadmaps. The second thing is vendor interoperability in that, you are going to be integrating multiple clouds. So, you're going to need a solution that can connect to multiple clouds seamlessly, right? And with that comes the challenge of maintainability. So, you're going to need to look into a automation solution that is easy to learn or has an easy learning curve. And then, the fourth idea that we tell our customers is scalability. In the hybrid cloud space, scale is the big, big deal here. And you need to deploy an automation solution that can span across the whole enterprise in a consistent manner, right. And then also that allows you finally to integrate the multiple data centers that you have. >> So, Ajay, I mean, this is a complicated situation for if a customer has to make sure things work on AWS or Azure or Google. They're going to spend all their time doing that. What can you add to really just simplify that multi-cloud and hybrid cloud equation. >> Yeah, I can give a few customer examples here. One being a manufacturer that we've worked with to drive that simplification. And the real bonuses for them has been a reduction in cost. We worked with them late last year to bring the cost spend down by $10 million in 2021. So, they could hit that reduced budget. And, what we brought to that was the ability to deploy using OpenShift templates into their different environments, whether it was on premise or in, as you mentioned, AWS. They had GCP as well for their marketing team and across those different platforms, being able to use a template, use prebuilt scripts to get up and running and catalog and discover that data within minutes. It takes away the legacy of having teams of people having to jump on workshop calls. And I know we're all on a lot of teams zoom calls. And in these current times. They're just simply using enough hours of the day to manually perform all of this. So, yeah, working with Red Hat, applying machine learning into those templates, those little recipes that we can put that automation to work regardless which location the data's in allows us to pull that unified view together. >> Great, thank you. Fadzi, I want to come back to you. So, the early days of cloud you're in the Big Apple, you know financial services really well. Cloud was like an evil word and within financial services, and obviously that's changed, it's evolved. We talk about the pandemic has even accelerated that. And when you really dug into it, when you talk to customers about their experiences with security in the cloud, it was not that it wasn't good, it was great, whatever, but it was different. And there's always this issue of skill, lack of skills and multiple tools, set up teams. are really overburdened. But in the cloud requires, you know, new thinking you've got the shared responsibility model. You've got to obviously have specific corporate, you know requirements and compliance. So, this is even more complicated when you introduce multiple clouds. So, what are the differences that you can share from your experiences running on a sort of either on prem or on a mono cloud or, you know, versus across clouds? What, do you suggest there? >> Sure, you know, because of these complexities that you have explained here mixed configurations and the inadequate change control are the top security threats. So, human error is what we want to avoid, because as you know, as your clouds grow with complexity then you put humans in the mix. Then the rate of errors is going to increase and that is going to expose you to security threats. So, this is where automation comes in, because automation will streamline and increase the consistency of your infrastructure management also application development and even security operations to improve in your protection compliance and change control. So, you want to consistently configure resources according to a pre-approved, you know, pre-approved policies and you want to proactively maintain them in a repeatable fashion over the whole life cycle. And then, you also want to rapidly the identify system that require patches and reconfiguration and automate that process of patching and reconfiguring. So that, you don't have humans doing this type of thing, And you want to be able to easily apply patches and change assistance settings according to a pre-defined base like I explained before, you know with the pre-approved policies. And also you want ease of auditing and troubleshooting, right. And from a Red Hat perspective we provide tools that enable you to do this. We have, for example a tool called Ansible that enables you to automate data center operations and security and also deployment of applications. And also OpenShift itself, it automates most of these things and obstruct the human beings from putting their fingers and causing, you know potentially introducing errors, right. Now, in looking into the new world of multiple clouds and so forth. The differences that we're seeing here between running a single cloud or on prem is three main areas, which is control, security and compliance, right. Control here, it means if you're on premise or you have one cloud you know, in most cases you have control over your data and your applications, especially if you're on prem. However, if you're in the public cloud, there is a difference that the ownership it is still yours, but your resources are running on somebody else's or the public clouds, EWS and so forth infrastructure. So, people that are going to do these need to really, especially banks and governments need to be aware of the regulatory constraints of running those applications in the public cloud. And we also help customers rationalize some of these choices. And also on security, you will see that if you're running on premises or in a single cloud you have more control, especially if you're on prem. You can control the sensitive information that you have. However, in the cloud, that's a different situation especially from personal information of employees and things like that. You need to be really careful with that. And also again, we help you rationalize some of those choices. And then, the last one is compliance. As well, you see that if you're running on prem on single cloud, regulations come into play again, right? And if you're running on prem, you have control over that. You can document everything, you have access to everything that you need, but if you're going to go to the public cloud again, you need to think about that. We have automation and we have standards that can help you you know, address some of these challenges. >> So, that's really strong insights, Fadzi. I mean, first of all Ansible has a lot of market momentum, you know, Red Hat's done a really good job with that acquisition. Your point about repeatability is critical, because you can't scale otherwise. And then, that idea you're putting forth about control, security and compliance. It's so true, I called it the shared responsibility model. And there was a lot of misunderstanding in the early days of cloud. I mean, yeah, maybe AWS is going to physically secure the you know, the S3, but in the bucket but we saw so many misconfigurations early on. And so it's key to have partners that really understand this stuff and can share the experiences of other clients. So, this all sounds great. Ajay, you're sharp, financial background. What about the economics? You know, our survey data shows that security it's at the top of the spending priority list, but budgets are stretched thin. I mean, especially when you think about the work from home pivot and all the areas that they had to, the holes that they had to fill there, whether it was laptops, you know, new security models, et cetera. So, how to organizations pay for this? What's the business case look like in terms of maybe reducing infrastructure costs, so I can pay it forward or there's a there's a risk reduction angle. What can you share there? >> Yeah, I mean, that perspective I'd like to give here is not being multi-cloud as multi copies of an application or data. When I think back 20 years, a lot of the work in financial services I was looking at was managing copies of data that were feeding different pipelines, different applications. Now, what we're seeing at io/tahoe a lot of the work that we're doing is reducing the number of copies of that data. So that, if I've got a product lifecycle management set of data, if I'm a manufacturer I'm just going to keep that at one location. But across my different clouds, I'm going to have best of breed applications developed in-house, third parties in collaboration with my supply chain, connecting securely to that single version of the truth. What I'm not going to do is to copy that data. So, a lot of what we're seeing now is that interconnectivity using applications built on Kubernetes that are decoupled from the data source. That allows us to reduce those copies of data within that you're gaining from a security capability and resilience, because you're not leaving yourself open to those multiple copies of data. And with that come cost of storage and a cost to compute. So, what we're saying is using multi-cloud to leverage the best of what each cloud platform has to offer. And that goes all the way to Snowflake and Heroku on a cloud managed databases too. >> Well and the people cost too as well. When you think about, yes, the copy creep. But then, you know, when something goes wrong a human has to come in and figure it out. You know, you brought up Snowflake, I get this vision of the data cloud, which is, you know data. I think we're going to be rethinking Ajay, data architectures in the coming decade where data stays where it belongs, it's distributed and you're providing access. Like you said, you're separating the data from the applications. Applications as we talked about with Fadzi, much more portable. So, it's really the last 10 years it'd be different than the next 10 years ago Ajay. >> Definitely, I think the people cost reduction is used. Gone are the days where you needed to have a dozen people governing, managing byte policies to data. A lot of that repetitive work, those tasks can be in part automated. We're seen examples in insurance where reduced teams of 15 people working in the back office, trying to apply security controls, compliance down to just a couple of people who are looking at the exceptions that don't fit. And that's really important because maybe two years ago the emphasis was on regulatory compliance of data with policies such as GDPR and CCPA. Last year, very much the economic effect to reduce head counts and enterprises running lean looking to reduce that cost. This year, we can see that already some of the more proactive companies are looking at initiatives, such as net zero emissions. How they use data to understand how they can become more, have a better social impact and using data to drive that. And that's across all of their operations and supply chain. So, those regulatory compliance issues that might have been external. We see similar patterns emerging for internal initiatives that are benefiting that environment, social impact, and of course costs. >> Great perspectives. Jeff Hammerbacher once famously said, the best minds of my generation are trying to get people to click on ads and Ajay those examples that you just gave of, you know social good and moving things forward are really critical. And I think that's where data is going to have the biggest societal impact. Okay guys, great conversation. Thanks so much for coming to the program. Really appreciate your time. >> Thank you. >> Thank you so much, Dave. >> Keep it right there, for more insight and conversation around creating a resilient digital business model. You're watching theCube. (soft music)

>> Announcer: From around the globe, it's theCUBE presenting Enterprise Digital Resilience on Hybrid and multicloud brought to you by io/tahoe >> Hello everyone, and welcome to our continuing series covering data automation brought to you by io/tahoe. Today we're going to look at how to ensure enterprise resilience for hybrid and multicloud, let's welcome in Ajay Vohora who's the CEO of io/tahoe Ajay, always good to see you again, thanks for coming on. >> Great to be back David, pleasure. >> And he's joined by Fadzi Ushewokunze, who is a global principal architect for financial services, the vertical of financial services at Red Hat. He's got deep experiences in that sector. Welcome Fadzi, good to see you. >> Thank you very much. Happy to be here. >> Fadzi, let's start with you. Look, there are a lot of views on cloud and what it is. I wonder if you could explain to us how you think about what is a hybrid cloud and how it works. >> Sure, Yeah. So, a hybrid cloud is an IT architecture that incorporates some degree of workload portability, orchestration and management across multiple clouds. Those clouds could be private clouds or public clouds or even your own data centers. And how does it all work? It's all about secure interconnectivity and on demand allocation of resources across clouds. And separate clouds can become hybrid when you're seamlessly interconnected. And it is that interconnectivity that allows the workloads to be moved and how management can be unified and orchestration can work. And how well you have these interconnections has a direct impact of how well your hybrid cloud will work. >> Okay, so well Fadzi, staying with you for a minute. So, in the early days of cloud that term private cloud was thrown around a lot. But it often just meant virtualization of an on-prem system and a network connection to the public cloud. Let's bring it forward. What, in your view does a modern hybrid cloud architecture look like? >> Sure, so, for modern hybrid clouds we see that teams or organizations need to focus on the portability of applications across clouds. That's very important, right. And when organizations build applications they need to build and deploy these applications as a small collections of independently loosely coupled services. And then have those things run on the same operating system, which means in other words, running it all Linux everywhere and building cloud native applications and being able to manage it and orchestrate these applications with platforms like Kubernetes or Red Hat OpenShift, for example. >> Okay, so, Fadzi that's definitely different from building a monolithic application that's fossilized and doesn't move. So, what are the challenges for customers, you know, to get to that modern cloud is as you've just described it as it skillsets, is it the ability to leverage things like containers? What's your View there? >> So, I mean, from what we've seen around the industry especially around financial services where I spend most of my time. We see that the first thing that we see is management, right. Now, because you have all these clouds, you know, all these applications. You have a massive array of connections, of interconnections. You also have massive array of integrations portability and resource allocation as well. And then orchestrating all those different moving pieces things like storage networks. Those are really difficult to manage, right? So, management is the first challenge. The second one is workload placement. Where do you place this cloud? How do you place these cloud native operations? Do you, what do you keep on site on prem and what do you put in the cloud? That is the other challenge. The major one, the third one is security. Security now becomes the key challenge and concern for most customers. And we're going to talk about how to address that. >> Yeah, we're definitely going to dig into that. Let's bring Ajay into the conversation. Ajay, you know, you and I have talked about this in the past. One of the big problems that virtually every company face is data fragmentation. Talk a little bit about how io/tahoe, unifies data across both traditional systems, legacy systems and it connects to these modern IT environments. >> Yeah, sure Dave. I mean, a Fadzi just nailed it there. It used to be about data, the volume of data and the different types of data, but as applications become more connected and interconnected the location of that data really matters. How we serve that data up to those apps. So, working with Red Hat and our partnership with Red Hat. Being able to inject our data discovery machine learning into these multiple different locations. whether it be an AWS or an IBM cloud or a GCP or on prem. Being able to automate that discovery and pulling that single view of where is all my data, then allows the CIO to manage cost. They can do things like, one, I keep the data where it is, on premise or in my Oracle cloud or in my IBM cloud and connect the application that needs to feed off that data. And the way in which we do that is machine learning that learns over time as it recognizes different types of data, applies policies to classify that data and brings it all together with automation. >> Right, and one of the big themes that we've talked about this on earlier episodes is really simplification, really abstracting a lot of that heavy lifting away. So, we can focus on things Ajay, as you just mentioned. I mean, Fadzi, one of the big challenges that of course we all talk about is governance across these disparate data sets. I'm curious as your thoughts how does Red Hat really think about helping customers adhere to corporate edicts and compliance regulations? Which of course are particularly acute within financial services. >> Oh yeah, yes. So, for banks and payment providers like you've just mentioned there. Insurers and many other financial services firms, you know they have to adhere to a standard such as say a PCI DSS. And in Europe you've got the GDPR, which requires stringent tracking, reporting, documentation and, you know for them to, to remain in compliance. And the way we recommend our customers to address these challenges is by having an automation strategy, right. And that type of strategy can help you to improve the security on compliance of of your organization and reduce the risk out of the business, right. And we help organizations build security and compliance from the start with our consulting services, residencies. We also offer courses that help customers to understand how to address some of these challenges. And there's also, we help organizations build security into their applications with our open source middleware offerings and even using a platform like OpenShift, because it allows you to run legacy applications and also containerized applications in a unified platform. Right, and also that provides you with, you know with the automation and the tooling that you need to continuously monitor, manage and automate the systems for security and compliance purposes. >> Ajay, anything, any color you could add to this conversation? >> Yeah, I'm pleased Fadzi brought up OpenShift. I mean we're using OpenShift to be able to take that security application of controls to the data level and it's all about context. So, understanding what data is there, being able to assess it to say, who should have access to it, which application permission should be applied to it. That's a great combination of Red Hat and io/tahoe. >> Fadzi, what about multi-cloud? Doesn't that complicate the situation even further, maybe you could talk about some of the best practices to apply automation across not only hybrid cloud, but multi-cloud as well. >> Yeah, sure, yeah. So, the right automation solution, you know can be the difference between, you know cultivating an automated enterprise or automation carries. And some of the recommendations we give our clients is to look for an automation platform that can offer the first thing is complete support. So, that means have an automation solution that provides, you know, promotes IT availability and reliability with your platform so that, you can provide enterprise grade support, including security and testing integration and clear roadmaps. The second thing is vendor interoperability in that, you are going to be integrating multiple clouds. So, you're going to need a solution that can connect to multiple clouds seamlessly, right? And with that comes the challenge of maintainability. So, you're going to need to look into a automation solution that is easy to learn or has an easy learning curve. And then, the fourth idea that we tell our customers is scalability. In the hybrid cloud space, scale is the big, big deal here. And you need to deploy an automation solution that can span across the whole enterprise in a consistent manner, right. And then also that allows you finally to integrate the multiple data centers that you have. >> So, Ajay, I mean, this is a complicated situation for if a customer has to make sure things work on AWS or Azure or Google. They're going to spend all their time doing that. What can you add to really just simplify that multi-cloud and hybrid cloud equation. >> Yeah, I can give a few customer examples here. One being a manufacturer that we've worked with to drive that simplification. And the real bonuses for them has been a reduction in cost. We worked with them late last year to bring the cost spend down by $10 million in 2021. So, they could hit that reduced budget. And, what we brought to that was the ability to deploy using OpenShift templates into their different environments, whether it was on premise or in, as you mentioned, AWS. They had GCP as well for their marketing team and across those different platforms, being able to use a template, use prebuilt scripts to get up and running and catalog and discover that data within minutes. It takes away the legacy of having teams of people having to jump on workshop calls. And I know we're all on a lot of teams zoom calls. And in these current times. They're just simply using enough hours of the day to manually perform all of this. So, yeah, working with Red Hat, applying machine learning into those templates, those little recipes that we can put that automation to work regardless which location the data's in allows us to pull that unified view together. >> Great, thank you. Fadzi, I want to come back to you. So, the early days of cloud you're in the Big Apple, you know financial services really well. Cloud was like an evil word and within financial services, and obviously that's changed, it's evolved. We talk about the pandemic has even accelerated that. And when you really dug into it, when you talk to customers about their experiences with security in the cloud, it was not that it wasn't good, it was great, whatever, but it was different. And there's always this issue of skill, lack of skills and multiple tools, set up teams. are really overburdened. But in the cloud requires, you know, new thinking you've got the shared responsibility model. You've got to obviously have specific corporate, you know requirements and compliance. So, this is even more complicated when you introduce multiple clouds. So, what are the differences that you can share from your experiences running on a sort of either on prem or on a mono cloud or, you know, versus across clouds? What, do you suggest there? >> Sure, you know, because of these complexities that you have explained here mixed configurations and the inadequate change control are the top security threats. So, human error is what we want to avoid, because as you know, as your clouds grow with complexity then you put humans in the mix. Then the rate of errors is going to increase and that is going to expose you to security threats. So, this is where automation comes in, because automation will streamline and increase the consistency of your infrastructure management also application development and even security operations to improve in your protection compliance and change control. So, you want to consistently configure resources according to a pre-approved, you know, pre-approved policies and you want to proactively maintain them in a repeatable fashion over the whole life cycle. And then, you also want to rapidly the identify system that require patches and reconfiguration and automate that process of patching and reconfiguring. So that, you don't have humans doing this type of thing, And you want to be able to easily apply patches and change assistance settings according to a pre-defined base like I explained before, you know with the pre-approved policies. And also you want ease of auditing and troubleshooting, right. And from a Red Hat perspective we provide tools that enable you to do this. We have, for example a tool called Ansible that enables you to automate data center operations and security and also deployment of applications. And also OpenShift itself, it automates most of these things and obstruct the human beings from putting their fingers and causing, you know potentially introducing errors, right. Now, in looking into the new world of multiple clouds and so forth. The differences that we're seeing here between running a single cloud or on prem is three main areas, which is control, security and compliance, right. Control here, it means if you're on premise or you have one cloud you know, in most cases you have control over your data and your applications, especially if you're on prem. However, if you're in the public cloud, there is a difference that the ownership it is still yours, but your resources are running on somebody else's or the public clouds, EWS and so forth infrastructure. So, people that are going to do these need to really, especially banks and governments need to be aware of the regulatory constraints of running those applications in the public cloud. And we also help customers rationalize some of these choices. And also on security, you will see that if you're running on premises or in a single cloud you have more control, especially if you're on prem. You can control the sensitive information that you have. However, in the cloud, that's a different situation especially from personal information of employees and things like that. You need to be really careful with that. And also again, we help you rationalize some of those choices. And then, the last one is compliance. As well, you see that if you're running on prem on single cloud, regulations come into play again, right? And if you're running on prem, you have control over that. You can document everything, you have access to everything that you need, but if you're going to go to the public cloud again, you need to think about that. We have automation and we have standards that can help you you know, address some of these challenges. >> So, that's really strong insights, Fadzi. I mean, first of all Ansible has a lot of market momentum, you know, Red Hat's done a really good job with that acquisition. Your point about repeatability is critical, because you can't scale otherwise. And then, that idea you're putting forth about control, security and compliance. It's so true, I called it the shared responsibility model. And there was a lot of misunderstanding in the early days of cloud. I mean, yeah, maybe AWS is going to physically secure the you know, the S3, but in the bucket but we saw so many misconfigurations early on. And so it's key to have partners that really understand this stuff and can share the experiences of other clients. So, this all sounds great. Ajay, you're sharp, financial background. What about the economics? You know, our survey data shows that security it's at the top of the spending priority list, but budgets are stretched thin. I mean, especially when you think about the work from home pivot and all the areas that they had to, the holes that they had to fill there, whether it was laptops, you know, new security models, et cetera. So, how to organizations pay for this? What's the business case look like in terms of maybe reducing infrastructure costs, so I can pay it forward or there's a there's a risk reduction angle. What can you share there? >> Yeah, I mean, that perspective I'd like to give here is not being multi-cloud as multi copies of an application or data. When I think back 20 years, a lot of the work in financial services I was looking at was managing copies of data that were feeding different pipelines, different applications. Now, what we're seeing at io/tahoe a lot of the work that we're doing is reducing the number of copies of that data. So that, if I've got a product lifecycle management set of data, if I'm a manufacturer I'm just going to keep that at one location. But across my different clouds, I'm going to have best of breed applications developed in-house, third parties in collaboration with my supply chain, connecting securely to that single version of the truth. What I'm not going to do is to copy that data. So, a lot of what we're seeing now is that interconnectivity using applications built on Kubernetes that are decoupled from the data source. That allows us to reduce those copies of data within that you're gaining from a security capability and resilience, because you're not leaving yourself open to those multiple copies of data. And with that come cost of storage and a cost to compute. So, what we're saying is using multi-cloud to leverage the best of what each cloud platform has to offer. And that goes all the way to Snowflake and Heroku on a cloud managed databases too. >> Well and the people cost too as well. When you think about, yes, the copy creep. But then, you know, when something goes wrong a human has to come in and figure it out. You know, you brought up Snowflake, I get this vision of the data cloud, which is, you know data. I think we're going to be rethinking Ajay, data architectures in the coming decade where data stays where it belongs, it's distributed and you're providing access. Like you said, you're separating the data from the applications. Applications as we talked about with Fadzi, much more portable. So, it's really the last 10 years it'd be different than the next 10 years ago Ajay. >> Definitely, I think the people cost reduction is used. Gone are the days where you needed to have a dozen people governing, managing byte policies to data. A lot of that repetitive work, those tasks can be in part automated. We're seen examples in insurance where reduced teams of 15 people working in the back office, trying to apply security controls, compliance down to just a couple of people who are looking at the exceptions that don't fit. And that's really important because maybe two years ago the emphasis was on regulatory compliance of data with policies such as GDPR and CCPA. Last year, very much the economic effect to reduce head counts and enterprises running lean looking to reduce that cost. This year, we can see that already some of the more proactive companies are looking at initiatives, such as net zero emissions. How they use data to understand how they can become more, have a better social impact and using data to drive that. And that's across all of their operations and supply chain. So, those regulatory compliance issues that might have been external. We see similar patterns emerging for internal initiatives that are benefiting that environment, social impact, and of course costs. >> Great perspectives. Jeff Hammerbacher once famously said, the best minds of my generation are trying to get people to click on ads and Ajay those examples that you just gave of, you know social good and moving things forward are really critical. And I think that's where data is going to have the biggest societal impact. Okay guys, great conversation. Thanks so much for coming to the program. Really appreciate your time. >> Thank you. >> Thank you so much, Dave. >> Keep it right there, for more insight and conversation around creating a resilient digital business model. You're watching theCube. (soft music)