Thursday, May 10, 2018

Panel explores new ways to solve the complexity of hybrid cloud monitoring

The next BriefingsDirect panel discussion focuses on improving performance and cost monitoring of various IT workloads in a multi-cloud world.

We will now explore how multi-cloud adoption is forcing cloud monitoring and cost management to work in new ways for enterprises.

Our panel of Micro Focus experts will unpack new Dimensional Research survey findings gleaned from more than 500 enterprise cloud specifiers. You will learn about their concerns, requirements and demands for improving the monitoring, management and cost control over hybrid and multi-cloud deployments.

We will also hear about new solutions and explore examples of how automation leverages machine learning (ML) and rapidly improves cloud management at a large Barcelona bank.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy.
To share more about interesting new cloud trends, we are joined by Harald Burose, Director of Product Management at Micro Focus, and he is based in Stuttgart; Ian Bromehead, Direct of Product Marketing at Micro Focus, and he is based in Grenoble, France, and Gary Brandt, Product Manager at Micro Focus, based in Sacramento. The discussion is moderated by Dana Gardner, Principal Analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: Let's begin with setting the stage for how cloud computing complexity is rapidly advancing to include multi-cloud computing -- and how traditional monitoring and management approaches are falling short in this new hybrid IT environment.

Enterprise IT leaders tasked with the management of apps, data, and business processes amid this new level of complexity are primarily grounded in the IT management and monitoring models from their on-premises data centers.

They are used to being able to gain agent-based data sets and generate analysis on their own, using their own IT assets that they control, that they own, and that they can impose their will over.

Yet virtually overnight, a majority of companies share infrastructure for their workloads across public clouds and on-premises systems. The ability to manage these disparate environments is often all or nothing.

The cart is in front of the horse. IT managers do not own the performance data generated from their cloud infrastructure.
In many ways, the ability to manage in a hybrid fashion has been overtaken by the actual hybrid deployment models. The cart is in front of the horse. IT managers do not own the performance data generated from their cloud infrastructure. Their management agents can’t go there. They have insights from their own systems, but far less from their clouds, and they can’t join these. They therefore have hybrid computing -- but without commensurate hybrid management and monitoring.

They can’t assure security or compliance and they cannot determine true and comparative costs -- never mind gain optimization for efficiency across the cloud computing spectrum.

Old management into the cloud

But there’s more to fixing the equation of multi-cloud complexity than extending yesterday’s management means into the cloud. IT executives today recognize that IT operations’ divisions and adjustments must be handled in a much different way.

Even with the best data assets and access and analysis, manual methods will not do for making the right performance adjustments and adequately reacting to security and compliance needs.
Automation, in synergy with big data analytics, is absolutely the key to effective and ongoing multi-cloud management and optimization.

Fortunately, just as the need for automation across hybrid IT management has become critical, the means to provide ML-enabled analysis and remediation have matured -- and at compelling prices.

Great strides have been made in big data analysis of such vast data sets as IT infrastructure logs from a variety of sources, including from across the hybrid IT continuum.

Many analysts, in addition to myself, are now envisioning how automated bots leveraging IT systems and cloud performance data can begin to deliver more value to IT operations, management, and optimization. Whether you call it BotOps, or AIOps, the idea is the same: The rapid concurrent use of multiple data sources, data collection methods and real-time top-line analytic technologies to make IT operations work the best at the least cost.

We are on the cusp of being able to take advantage of ML to tackle the complexity of multi-cloud deployments and keep business services safe. 
IT leaders are seeking the next generation of monitoring, management and optimizing solutions. We are now on the cusp of being able to take advantage of advanced ML to tackle the complexity of multi-cloud deployments and to keep business services safe, performant, and highly cost efficient.

Similar in concept to self-driving cars, wouldn’t you rather have self-driving IT operations? So far, a majority of you surveyed say yes; and we are going to soon learn more about that survey information. 
 
Ian, please tell us more about the survey findings.

IT leaders respond to their needs 

Ian Bromehead: Thanks, Dana. The first element of the survey that we wanted to share describes the extent to which cloud is so prevalent today.
More than 92 percent of the 500 or so executives are indicating that we are already in a world of significant multi-cloud adoption.
Bromehead

The lion’s share, or nearly two-thirds, of this population that we surveyed are using between two to five different cloud vendors. But more than 12 percent of respondents are using more than 10 vendors. So, the world is becoming increasingly complex. Of course, this strains a lot of the different aspects [of management].

What are people doing with those multiple cloud instances? As to be expected, people are using them to extend their IT landscape, interconnecting application logic and their own corporate data sources with the infrastructure and the apps in their cloud-based deployments -- whether they’re Infrastructure as a Service (IaaS) or Platform as a Service (PaaS). Some 88 percent of the respondents are indeed connecting their corporate logic and data sources to those cloud instances.

What’s more interesting is that a good two-thirds of the respondents are sharing data and integrating that logic across heterogeneous cloud instances, which may or may not be a surprise to you. It’s nevertheless a facet of many people’s architectures today. It’s a result of the need for agility and cost reduction, but it’s obviously creating a pretty high degree of complexity as people share data across multiple cloud instances.

The next aspect that we saw in the survey is that 96 percent of the respondents indicate that these public cloud application issues are resolved too slowly, and they are impacting the business in many cases.

Some of the business impacts range from resources tied up by collaborating with the cloud vendor to trying to solve these issues, and the extra time required to resolve issues impacting service level agreements (SLAs) and contractual agreements, and prolonged down time.
What we regularly see is that the adoption of cloud often translates into a loss in transparency of what’s deployed and the health of what’s being deployed, and how that’s capable of impacting the business. This insight is a strong bias on our investment and some of the solutions we will talk to you about. Their primary concern is on the visibility of what’s being deployed -- and what depends on the internal, on-premise as well as private and public cloud instances.

People need to see what is impacting the delivery of services as a provider, and if that’s due to issues with local or remote resources, or the connectivity between them. It’s just compounded by the fact that people are interconnecting services, as we just saw in the survey, from multiple cloud providers. So the weak part could be anywhere, could be anyone of those links. The ability for people to know where those issues are is not happening fast enough for many people, with some 96 percent indicating that the issues are being resolved too slowly.

How to gain better visibility?

What are the key changes that need to be addressed when monitoring hybrid IT absent environments? People have challenges with discovery, understanding, and visualizing what has actually been deployed, and how it is impacting the end-to-end business.

They have limited access to the cloud infrastructure, and things like inadequate security monitoring or traditional monitoring agent difficulties, as well as monitoring lack of real-time metrics to be able to properly understand what’s happening.

It shows some of the real challenges that people are facing. And as the world shifts to being more dependent on the services that they consume, then traditional methods are not going to be properly adapted to the new environment. Newer solutions are needed. New ways of gaining visibility – and the measuring availability and performance are going to be needed.

I think what’s interesting in this part of the survey is the indication that the cloud vendors themselves are not providing this visibility. They are not providing enough information for people to be able to properly understand how service delivery might be impacting their own businesses. For instance, you might think that IT is actually flying blind in the clouds as it were.

The cloud vendors are not providing the visibility. They are not providing enough information for people to be able to understand service delivery impacts.
So, one of my next questions was, Across the different monitoring ideas or types, what’s needed for the hybrid IT environment? What should people be focusing on? Security infrastructure, getting better visibility, and end-user experience monitoring, service delivery monitoring and cloud costs – all had high ranking on what people believe they need to be able to monitor. Whether you are a provider or a consumer, most people end up being both. Monitoring is really key.
 
People say they really need to span infrastructure monitoring, metric that monitoring, and gain end-user security and compliance. But even that’s not enough because to properly govern the service delivery, you are going to have to have an eye on the costs -- the cost of what’s being deployed -- and how can you optimize the resources according to those costs. You need that analysis whether you are a consumer or the provider.

The last of our survey results shows the need for comprehensive enterprise monitoring. Now, people need things such as high-availability, automation, the ability to cover all types of data to find issues like root causes and issues, even from a predictive perspective. Clearly, here people expect scalability, they expect to be able to use a big data platform.

For consumers of cloud services, they should be measuring what they are receiving, and capable of seeing what’s impacting the service delivery. No one is really so naive as to say that infrastructure is somebody else’s problem. When it’s part of this service, equally impacting the service that you are paying for, and that you are delivering to your business users -- then you better have the means to be able to see where the weak links are. It should be the minimum to seek, but there’s still happenings to prove to your providers that they’re underperforming and renegotiate what you pay for.

Ultimately, when you are sticking such composite services together, IT needs to become more of a service broker. We should be able to govern the aspects of detecting when the service is degrading. 

So when their service is more PaaS, then workers’ productivity is going to suffer and the business will expect IT to have the means to reverse that quickly.

So that, Dana, is the set of the different results that we got out of this survey.

A new need for analytics 

Gardner: Thank you, Ian. We’ll now go to Gary Brandt to learn about the need for analytics and how cloud monitoring solutions can be cobbled together anew to address these challenges.

Gary Brandt: Thanks, Dana. As the survey results were outlined and as Ian described, there are many challenges and numerous types of monitoring for enterprise hybrid IT environments. With such variety and volume of data from these different types of environments that gets generated in the complex hybrid environments, humans simply can’t look at dashboards or use traditional tools and make sense of the data efficiently. Nor can they take necessary actions required in a timely manner, given the volume and the complexity of these environments.

Brandt
So how do we deal with all of this? It’s where analytics, advanced analytics via ML, really brings in value. What’s needed is a set of automated capabilities such as those described in Gartner’s definition of AIOps and these include traditional and streaming data management, log and wire metrics, and document ingestion from many different types of sources in these complex hybrid environments.

Dealing with all this, trying to, when you are not quite sure where to look, when you have all this information coming in, it requires some advanced analytics and some clever artificial intelligence (AI)-driven algorithms just to make sense of it. This is what Gartner is really trying to guide the market toward and show where the industry is moving. The key capabilities that they speak about are analytics that allow for predictive capabilities and the capability to find anomalies in vast amounts of data, and then try to pinpoint where your root cause is, or at least eliminate the noise and get to focus on those areas.

We are making this Gartner report available for a limited time. What we have found also is that people don’t have the time or often the skill set to deal with activities and they focus on -- they need to focus on the business user and the target and the different issues that come up in these hybrid environments and these AIOps capabilities that Gartner speaks about are great.

But, without the automation to drive out the activities or the response that needs to occur, it becomes a missing piece. So, we look at a survey -- some of our survey results and what our respondents said, it was clear that upward of the high-90 percent are clearly telling us that automation is considered highly critical. You need to see which event or metric trend so clearly impacts on a business service and whether that service pertains to a local, on-prem type of solution, or a remote solution in a cloud at some place.

Automation is key, and that requires a degree of that service definition, dependency mapping, which really should be automated. And to be declared more – just more easily or more importantly to be kept up to date, you don’t need complex environments, things are changing so rapidly and so quickly.

Sense and significance of all that data? 

Micro Focus’ approach uses analytics to make sense of this vast amount of data that’s coming in from these hybrid environments to drive automation. The automation of discovery, monitoring, service analytics, they are really critical -- and must be applied across hybrid IT against your resources and map them to your services that you define.

Those are the vast amounts of data that we just described. They come in the form of logs and events and metrics, generated from lots of different sources in a hybrid environment across cloud and on-prem. You have to begin to use analytics as Gartner describes to make sense of that, and we do that in a variety of ways, where we use ML to learn behavior, basically of your environment, in this hybrid world.

And we need to be able to suggest what the most significant data is, what the significant information is in your messages, to really try to help find the needle in a haystack. When you are trying to solve problems, we have capabilities through analytics to provide predictive learning to operators to give them the chance to anticipate and to remediate issues before they disrupt the services in a company’s environment.

When you are trying to solve problems, we have capabilities through analytics to provide predictive learning to operators to remediate issues before they disrupt.
And then we take this further because we have the analytics capability that’s described by Gartner and others. We couple that with the ability to execute different types of automation as a means to let the operator, the operations team, have more time to spend on what’s really impacting the business and getting to the issues quicker than trying to spend time searching and sorting through that vast amount of data.

And we built this on different platforms. One of the key things that’s critical when you have this hybrid environment is to have a common way, or an efficient way, to collect information and to store information, and then use that data to provide access to different functionality in your system. And we do that in the form of microservices in this complex environment.

We like to refer to this as autonomous operations and it’s part of our OpsBridge solution, which embodies a lot of different patented capabilities around AIOps. Harald is going to speak to our OpsBridge solution in more detail.

Operations Bridge in more detail  

Gardner: Thank you, Gary. Now that we know more about what users need and consider essential, let’s explore a high-level look at where the solutions are going, how to access and assemble the data, and what new analytics platforms can do.

We’ll now hear from Harald Burose, Director of Product Management at Micro Focus.

Harald Burose: When we listen carefully to the different problems that Ian was highlighting, we actually have a lot of those problems addressed in the Operations Bridge solution that we are currently bringing to market.

Burose
All core use cases for Operations Bridge tie it to the underpinning of the Vertica big data analytics platform. We’re consolidating all the different types of data that we are getting; whether business transactions, IT infrastructure, application infrastructure, or business services data -- all of that is actually moved into a single data repository and then reduced in order to basically understand what the original root cause is.

And from there, these tools like the analytics that Gary described, not only identify the root cause, but move to remediation, to fixing the problem using automation.

This all makes it easy for the stakeholders to understand what the status is and provide the right dashboarding, reporting via the right interface to the right user across the full hybrid cloud infrastructure.

As we saw, some 88 percent of our customers are connecting their cloud infrastructure to their on-premises infrastructure. We are providing the ability to understand that connectivity through a dynamically updated model, and to show how these services are interconnecting -- independent of the technology -- whether deployed in the public cloud, a private cloud, or even in a classical, non-cloud infrastructure. They can then understand how they are connecting, and they can use the toolset to navigate through it all, a modern HTML5-based interface, to look at all the data in one place.

They are able to consolidate more than 250 different technologies and information into a single place: their log files, the events, metrics, topology -- everything together to understand the health of their infrastructure. That is the key element that we drive with the Operations Bridge.
Now, we have extended the capabilities further, specifically for the cloud. We basically took the generic capability and made it work specifically for the different cloud stacks, whether private cloud, your own stack implementations, a hyperconverged (HCI) stack, like Nutanix, or a Docker container infrastructure that you bring up on a public cloud like Azure, Amazon, or Google Cloud.

We are now automatically discovering and placing that all into the context of your business service application by using the Automated Service Modeling part of the Operations Bridge.
Now, once we actually integrate those toolsets, we tightly integrate them for native tools on Amazon or for Docker tools, for example. You can include these tools, so you can then automate processes from within our console.

Customers vote a top choice

And, best of all, we have been getting positive feedback from the cloud monitoring community, by the customers. And the feedback has helped earn us a Readers’ Choice Award by the Cloud Computing Insider in 2017, by being ahead of the competition.

This success is not just about getting the data together, using ML to understand the problem, and using our capabilities to connect these things together. At the end of the day, you need to act on the activity.

Having a full-blown orchestration compatibility within OpsBridge provides more than 5,000 automated workflows, so you can automate different remediation tasks -- or potentially point to future provisioning tasks that solve the problems of whatever you can imagine. You can use this to not only identify the root cause, but you can automatically kick off a workflow to address the specific problems.

If you don’t want to address a problem through the workflow, or cannot automatically address it, you still have a rich set of integrated tools to manually address a problem.
Having a full-blown orchestration capability with OpsBridge provides more than 5,000 automated workflows to automate many different remediation tasks.

Last, but not least, you need to keep your stakeholders up to date. They need to know, anywhere that they go, that the services are working. Our real-time dashboard is very open and can integrate with any type of data -- not just the operational data that we collect and manage with the Operations Bridge, but also third-party data, such as business data, video feeds, and sentiment data. This gets presented on a single visual dashboard that quickly gives the stakeholders the information: Is my business service actually running? Is it okay? Can I feel good about the business services that I am offering to my internal as well as external customer-users?
 
And you can have this on a network operations center (NOC) wall, on your tablet, or your phone -- wherever you’d like to have that type of dashboard. You can easily you create those dashboards using Microsoft Office toolsets, and create graphical, very appealing dashboards for your different stakeholders.

Gardner: Thank you, Harald. We are now going to go beyond just the telling, we are going to do some showing. We have heard a lot about what’s possible. But now let’s hear from an example in the field.

Multicloud monitoring in action

Next up is David Herrera, Cloud Service Manager at Banco Sabadell in Barcelona. Let’s find out about this use case and their use of Micro Focus’s OpsBridge solution.

David Herrera: Banco Sabadell is fourth largest Spanish banking group. We had a big project to migrate several systems into the cloud and we realized that we didn’t have any kind of visibility about what was happening in the cloud.

Herrera
We are working with private and public clouds and it’s quite difficult to correlate the information in events and incidents. We need to aggregate this information in just one dashboard. And for that, OpsBridge is a perfect solution for us.

We started to develop new functionalities on OpsBridge, to customize for our needs. We had to cooperate with a project development team in order to achieve this.
The main benefit is that we have a detailed view about what is happening in the cloud. In the dashboard we are able to show availability, number of resources that we are using -- almost in real time. Also, we are able to show what the cost is in real time of every resource, and we can do even the projection of the cost of the items.
The main benefit is we have a detailed view about what is happening in the cloud. We are able to show what the cost is in real time of every resource.

[And that’s for] every single item that we have in the cloud now, even across the private and public cloud. The bank has invested a lot of money in this solution and we need to show them that it’s really a good choice in economical terms to migrate several systems to the cloud, and this tool will help us with this.
 
Our response time will be reduced dramatically because we are able to filter and find what is happening, and call the right people to fix the problem quickly. The business department will understand better what we are doing because they will be able to see all the information, and also select information that we haven’t gathered. They will be more aligned with our work and we can develop and deliver better solutions because also we will understand them.

We were able to build a new monitoring system from scratch that doesn’t exist on the market. Now, we are able to aggregate a lot of detailing information from different clouds.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy. Sponsor: Micro Focus.

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Monday, May 7, 2018

How HudsonAlpha transforms hybrid cloud complexity into an IT force multiplier

The next BriefingsDirect hybrid IT management success story examines how the nonprofit research institute HudsonAlpha improves how it harnesses and leverages a spectrum of IT deployment environments.

We’ll now learn how HudsonAlpha has been testing a new Hewlett Packard Enterprise (HPE) solution, OneSphere, to gain a common and simplified management interface to rule them all.

Listen to the podcast. Find it on iTunes. Get the mobile app. Read a full transcript or download a copy.

Here to help explore the benefits of improved levels of multi-cloud visibility and process automation is Katreena Mullican, Senior Architect and Cloud Whisperer at HudsonAlpha Institute for Biotechnology in Huntsville, Alabama. The discussion is moderated by Dana Gardner, principal analyst at Interarbor Solutions.

Here are some excerpts:

Gardner: What’s driving the need to solve hybrid IT complexity at HudsonAlpha?

Mullican: The big drivers at HudsonAlpha are the requirements for data locality and ease-of-adoption. We produce about 6 petabytes of new data every year, and that rate is increasing with every project that we do.

Mullican
We support hundreds of researchprograms with data and trend analysis. Our infrastructure requires quickly iterating to identify the approaches that are both cost-effective and the best fit for the needs of our users.

Gardner: Do you find that having multiple types of IT platforms, environments, and architectures creates a level of complexity that’s increasingly difficult to manage?

Mullican: Gaining a competitive edge requires adopting new approaches to hybrid IT. Even carefully contained shadow IT is a great way to develop new approaches and attain breakthroughs.

Gardner: You want to give people enough leash where they can go and roam and experiment, but perhaps not so much that you don’t know where they are, what they are doing.

Software-defined everything  

Mullican: Right. “Software-defined everything” is our mantra. That’s what we aim to do at HudsonAlpha for gaining rapid innovation.

Gardner: How do you gain balance from too hard-to-manage complexity, with a potential of chaos, to the point where you can harness and optimize -- yet allow for experimentation, too?

Mullican: IT is ultimately responsible for the security and the up-time of the infrastructure. So it’s important to have a good framework on which the developers and the researchers can compute. It’s about finding a balance between letting them have provisioning access to those resources versus being able to keep an eye on what they are doing. And not only from a usage perspective, but from a cost perspective, too.
Simplified 
Gardner: Tell us about HudsonAlpha and its fairly extreme IT requirements.

Mullican: HudsonAlpha is a nonprofit organization of entrepreneurs, scientists, and educators who apply the benefits of genomics to everyday life. We also provide IT services and support for about 40 affiliate companies on our 150-acre campus in Huntsville, Alabama.

Gardner: What about the IT requirements? How you fulfill that mandate using technology?

Mullican: We produce 6 petabytes of new data every year. We have millions of hours of compute processing time running on our infrastructure. We have hardware acceleration. We have direct connections to clouds. We have collaboration for our researchers that extends throughout the world to external organizations. We use containers, and we use multiple cloud providers. 

Gardner: So you have been doing multi-cloud before there was even a word for multi-cloud?

Mullican: We are the hybrid-scale and hybrid IT organization that no one has ever heard of.

Gardner: Let’s unpack some of the hurdles you need to overcome to keep all of your scientists and researchers happy. How do you avoid lock-in? How do you keep it so that you can remain open and competitive?

Agnostic arrangements of clouds

Mullican: It’s important for us to keep our local datacenters agnostic, as well as our private and public clouds. So we strive to communicate with all of our resources through application programming interfaces (APIs), and we use open-source technologies at HudsonAlpha. We are proud of that. Yet there are a lot of possibilities for arranging all of those pieces.

There are a lot [of services] that you can combine with the right toolsets, not only in your local datacenter but also in the clouds. If you put in the effort to write the code with that in mind -- so you don’t lock into any one solution necessarily -- then you can optimize and put everything together.

Gardner: Because you are a nonprofit institute, you often seek grants. But those grants can come with unique requirements, even IT use benefits and cloud choice considerations.

Cloud cost control, granted

Mullican: Right. Researchers are applying for grants throughout the year, and now with the National Institutes of Health (NIH), when grants are awarded, they come with community cloud credits, which is an exciting idea for the researchers. It means they can immediately begin consuming resources in the cloud -- from storage to compute -- and that cost is covered by the grant.

So they are anxious to get started on that, which brings challenges to IT. We certainly don’t want to be the holdup for that innovation. We want the projects to progress as rapidly as possible. At the same time, we need to be aware of what is happening in a cloud and not lose control over usage and cost.
Simplified 
Gardner: Certainly HudsonAlpha is an extreme test bed for multi-cloud management, with lots of different systems, changing requirements, and the need to provide the flexibility to innovate to your clientele. When you wanted a better management capability, to gain an overview into that full hybrid IT environment, how did you come together with HPE and test what they are doing?

Variety is the spice of IT

Mullican: We’ve invested in composable infrastructure and hyperconverged infrastructure (HCI) in our datacenter, as well as blade server technology. We have a wide variety of compute, networking, and storage resources available to us.

The key is: How do we rapidly provision those resources in an automated fashion? I think the key there is not only for IT to be aware of those resources, but for developers to be as well. We have groups of developers dealing with bioinformatics at HudsonAlpha. They can benefit from all of the different types of infrastructure in our datacenter. What HPE OneSphere does is enable them to access -- through a common API -- that infrastructure. So it’s very exciting.

Gardner: What did HPE OneSphere bring to the table for you in order to be able to rationalize, visualize, and even prioritize this very large mixture of hybrid IT assets?

Mullican: We have been beta testing HPE OneSphere since October 2017, and we have tied it into our VMware ESX Server environment, as well as our Amazon Web Services (AWS) environment successfully -- and that’s at an IT level. So our next step is to give that to researchers as a single pane of glass where they can go and provision the resources themselves.

Gardner: What this might capability bring to you and your organization?

Cross-training the clouds

Mullican: We want to do more with cross-cloud. Right now we are very adept at provisioning within our datacenters, provisioning within each individual cloud. HudsonAlpha has a presence in all the major public clouds -- AWS, Google, Microsoft Azure. But the next step would be to go cross-cloud, to provision applications across them all.

For example, you might have an application that runs as a series of microservices. So you can have one microservice take advantage of your on-premises datacenter, such as for local storage. And then another piece could take advantage of object storage in the cloud. And even another piece could be in another separate public cloud.

But the key here is that our developer and researchers -- the end users of OneSphere – they don’t need to know all of the specifics of provisioning in each of those environments. That is not a level of expertise in their wheelhouse. In this new OneSphere way, all they know is that they are provisioning the application in the pipeline -- and that’s what the researchers will use. Then it’s up to us in IT to come along and keep an eye on what they are doing through the analytics that HPE OneSphere provides.

Gardner: Because OneSphere gives you the visibility to see what the end users are doing, potentially, for cost optimization and remaining competitive, you may be able to play one cloud off another. You may even be able to automate and orchestrate that.
Simplified 
Mullican: Right, and that will be an ongoing effort to always optimize cost -- but not at the risk of slowing the research. We want the research to happen, and to innovate as quickly as possible. We don’t want to be the holdup for that. But we definitely do need to loop back around and keep an eye on how the different clouds are being used and make decisions going forward based on the analytics.

Gardner: There may be other organizations that are going to be more cost-focused, and they will probably want to dial back to get the best deals. It’s nice that we have the flexibility to choose an algorithmic approach to business, if you will.

Mullican: Right. The research that we do at HudsonAlpha saves lives and the utmost importance is to be able to conduct that research at the fastest speed.

Gardner: HPE OneSphere seems geared toward being cloud-agnostic. They are beginning on AWS, yet they are going to be adding more clouds. And they are supporting more internal private cloud infrastructures, and using an API-driven approach to microservices and containers.

The research that we do at HudsonAlpha saves lives, and the utmost importance is to be able to conduct the research at the fastest speed.
As an early tester, and someone who has been a long-time user of HPE infrastructure, is there anything about the combination of HPE Synergy, HPE SimpliVity HCI, and HPE 3PAR intelligent storage -- in conjunction with OneSphere -- that’s given you a ‘whole greater than the sum of the parts’ effect?
 
Mullican: HPE Synergy and composable infrastructure is something that is very near and dear to me. I have a lot of hours invested with HPE Synergy Image Streamer and customizing open-source applications on Image Streamer – open-source operating systems and applications.

The ability to utilize that in the mix that I have architected natively with OneSphere -- in addition to the public clouds -- is very powerful, and I am excited to see where that goes.

Gardner: Any words of wisdom to others who may be have not yet gone down this road? What do you advise others to consider as they are seeking to better compose, automate, and optimize their infrastructure?

Get adept at DevOps

Mullican: It needs to start with IT. IT needs to take on more of a DevOps approach.
As far as putting an emphasis on automation -- and being able to provision infrastructure in the datacenter and the cloud through automated APIs -- a lot of companies probably are still slow to adopt that. They are still provisioning in older methods, and I think it’s important that they do that. But then, once your IT department is adept with DevOps, your developers can begin feeding from that and using what IT has laid down as a foundation. So it needs to start with IT.

It involves a skill set change for some of the traditional system administrators and network administrators. But now, with software-defined networking (SDN) and with automated deployments and provisioning of resources -- that’s a skill set that IT really needs to step up and master. That’s because they are going to need to set the example for the developers who are going to come along and be able to then use those same tools.

That’s the partnership that companies really need to foster -- and it’s between IT and developers. And something like HPE OneSphere is a good fit for that, because it provides a unified API.

On one hand, your IT department can be busy mastering how to communicate with their infrastructure through that tool. And at the same time, they can be refactoring applications as microservices, and that’s up to the developer teams. So both can be working on all of this at the same time.

Then when it all comes together with a service catalog of options, in the end it’s just a simple interface. That’s what we want, to provide a simple interface for the researchers. They don’t have to think about all the work that went into the infrastructure, they are just choosing the proper workflow and pipeline for future projects.
We want to provide a simple interface to the researchers. They don't have to think about all the work that went into the infrastructure.


Gardner: It also sounds, Katreena, like you are able to elevate IT to a solutions-level abstraction, and that OneSphere is an accelerant to elevating IT. At the same time, OneSphere is an accelerant to the adoption of DevOps, which means it’s also elevating the developers. So are we really finally bringing people to that higher plane of business-focus and digital transformation?

HCI advances across the globe

Mullican: Yes. HPE OneSphere is an advantage to both of those departments, which in some companies can be still quite disparate. Now at HudsonAlpha, we are DevOps in IT. It’s not a distinguished department, but in some companies that’s not the case.

And I think we have a lot of advantages because we think in terms of automation, and we think in terms of APIs from the infrastructure standpoint. And the tools that we have invested in, the types of composable and hyperconverged infrastructure, are helping accomplish that.

Gardner: I speak with a number of organizations that are global, and they have some data sovereignty concerns. I’d like to explore, before we close out, how OneSphere also might be powerful in helping to decide where data sets reside in different clouds, private and public, for various regulatory reasons.

Is there something about having that visibility into hybrid IT that extends into hybrid data environments?

Mullican: Data locality is one of our driving factors in IT, and we do have on-premises storage as well as cloud storage. There is a time and a place for both of those, and they do not always mix, but we have requirements for our data to be available worldwide for collaboration.

So, the services that HPE OneSphere makes available are designed to use the appropriate data connections, whether that would be back to your object storage on-premises, or AWS Simple Storage Service (S3), for example, in the cloud.
Simplified 
Gardner: Now we can think of HPE OneSphere as also elevating data scientists -- and even the people in charge of governance, risk management, and compliance (GRC) around adhering to regulations. It seems like it’s a gift that keeps giving.

Hybrid hard work pays off

Mullican: It is a good fit for hybrid IT and what we do at HudsonAlpha. It’s a natural addition to all of the preparation work that we have done in IT around automated provisioning with HPE Synergy and Image Streamer.

HPE OneSphere is a way to showcase to the end user all of the efforts that have been, and are being, done by IT. That’s why it’s a satisfying tool to implement, because, in the end, you want what you have worked on so hard to be available to the researchers and be put to use easily and quickly.