Michael Bird (00:09):
Hello and welcome back to Technology Now, a weekly show from Hewlett Packard Enterprise, where we take what's happening in the world and explore how it's changing the way organizations are using technology. We are your hosts, Michael Bird...

Aubrey Lovell (00:23):
And Aubrey Lovell, and in this episode, we are looking at how technology is allowing us to bring together the potentially dozens or even hundreds of different IT services and systems, from hardware to software and cloud in use throughout our organizations. It's an idea that's been years in the making, but with the rise of AI and edge computing, it's finally becoming a reality. We'll be asking how to bring together hundreds of data sources from different systems and vendors. We'll be asking why you'd want to, and we'll be exploring what it means for our organizations.

Michael Bird (00:55):
Yes, thank you, Aubrey. And if you are the kind of person who needs to know why what's going on in the world matters to your organization, then this podcast is, of course, just for you. Act, if you haven't yet. Do make sure you subscribe on your podcast app of choice so you don't miss out. Aubrey, let's get into it.

Aubrey Lovell (01:12):
Let's do it.

Michael Bird (01:16):
Building an IT stack for an organization is a daunting prospect. Not only do you have to pick the best products and providers, you somehow have to mate or migrate all your new software and hardware with your legacy systems. It's something entire departments built around, and it's often not the smoothest process. Then, even once you've got everything running, there are countless dashboards to monitor, to make sure everything is running smoothly and to cross compare when it comes to troubleshooting.

Aubrey Lovell (01:47):
So wouldn't it be nice if there was one dashboard that had it all? It presented you with everything you need to run your IT, whether you're in IT ops, running the systems, DevOps, running the software or SRE and making sure everything runs smoothly together. That is known as convergence and it's a potentially massive business opportunity. According to research by Deloitte, improving IT efficiency, especially with more automation, can save between 25 and 40%.

Michael Bird (02:16):
So why has it taken so long to happen? And are we there yet? Well, to find out, I recently met with Taruna Gandhi, she's head of product marketing at OpsRamp, a data insights and dashboard provider who recently joined the HPE family. Taruna, welcome to the show. Can you just explain what OpsRamp is, just really, really briefly?

Taruna Gandhi (02:37):
Oh, yeah, sure, sure, sure, sure. So OpsRamp mission is to simplify and integrate operations management for our customers. If you think about our customers, they have a diverse stack of infrastructure. It could be HPE infrastructure or it could be third party, it could be a public cloud. On top of that, they have multiple run times. It could be VMs, containers, bare metal, and then on top of that you have the applications, which could again be traditional applications, they could be cloud native applications, and lately AI native applications.

(03:09):
So OpsRamp's goal is to give our customers an operations framework that they can use no matter how they instrument their applications, how they develop those applications. So it gives unified visibility across the entire stack for a multi-vendor, multi-cloud environment, all the way from apps to infrastructure. And then with that observability, it layers on predictive analytics and machine learning and AI so that we can make sense of all of that observability data and surface up actionable insights so that our customers can automate and simplify as much as possible. So they get simplified operations management across their whole application through infrastructure, but they are still in control. They're still in the driver's seat.

Michael Bird (03:55):
Got it, got it. So why are we talking about this and why are we talking about this now?

Taruna Gandhi (03:59):
We've had a number of tools and that's what I think has gotten a lot of people into trouble. Think about it, if you can't see it, if you can't measure it, how are you going to optimize or fix it? And so we ended up in this situation because customers went on and they acquired one tool after another. The answer is not more tools. The answer is integrated data, so you get a holistic view of your environment and you are actually able to take actions quicker, you are able to service the business units better. If you have these broken up, then you end up in this big firefight and finger pointing exercise and nobody wants to do that.

Michael Bird (04:40):
Now, we talked in this podcast about convergence being a long-term aim. What is convergence?

Taruna Gandhi (04:46):
I have a slightly different point of view on it.

Michael Bird (04:46):
Okay, good, good, good.

Taruna Gandhi (04:49):
So it isn't about convergence. It is about not converging the data, but let the data be created where it is, because data has gravity, it has personality, it has to be in sovereign regions, but converging the visibility into that data, and not just visibility for the sake of visibility, but visibility so that you can get insights out of it. We know there's an explosion of data happening, and we know data is created everywhere, whether it's at the edge or cloud or your data center, it's going to happen. The point is to get it together in one place so that we can make sense out of it.

Michael Bird (05:28):
That makes sense. So what do we miss by not having everything under one umbrella?

Taruna Gandhi (05:35):
Now, that is a loaded question. What do you miss if you don't know what's happening in your house or in your business or where your kids are? You suffer performance issues, you suffer inefficiencies. You don't know where you have free resources and where you should place your new resources at. You could be in a situation where your data center is running hot, but your public cloud is underutilized, but you're still paying for it. You could end up in a situation where you don't know if something breaks, whether the issue was in the application or whether it was in the database, or was it in the infrastructure? Was it in the networking? Oftentimes IT is the last to know that a problem has occurred, and it should be the exact opposite. We are here in the business to make sure that IT is the first to know, and they can take actions before the end user or the businesses are impacted.

Michael Bird (06:33):
But is that actually realistic? Will a tool actually do that? How does that actually practically look?

Taruna Gandhi (06:39):
So practically, it happens at a couple of different levels. So one of the things that has been going on for a long time is this idea of machine learning, where you're looking at time series data, which is you're looking at patterns. So let's say Valentine's Day, the sale of flowers goes up, so you know, next time Valentine's Day comes in, I'd better have enough infrastructure to support that spike in business. But what do you do where you've never seen that pattern before? This is where the latest techniques in AI are coming in to help us identify those areas where there is no pattern. And we're finally at a point where the AI technology and the horsepower behind it and the software and the models are mature enough that we can actually answer that problem.

(07:27):
So that's where a lot of investment is going on is the core basic level of machine learning that's already there. And a lot of vendors may offer it, but to actually get ahead of it and say, "What if I've never seen that problem?" That's where foundational models, the latest techniques in AI, neural networks, all of those things come into play. So we are finally at a point where we can actually get that data, but I would not stop there, because on top of that, we also have conversational assistants now, and that's what simplifies that human machine interface. So I can go to my generative AI conversational assistant and say, "Hey, how's my infrastructure doing today?" And it's not just a text-based answer that I get. I get a generative dashboard that says, "Here's your whole world and here's the problems that I've pinpointed." So we really needed these technologies to be mature enough so that we could move beyond statistical techniques to these AI advanced techniques and then have a human machine interface that makes it easy to utilize it.

Michael Bird (08:37):
Are there any challenges that systems such as OpsRamp are still yet to overcome?

Taruna Gandhi (08:41):
It's a journey, and like everything in life, we have to keep pace with the technology. So one of the investment areas is obviously the generative AI and neural network piece to get from that prompt level to answer level to that predictive level. The other piece of investment that's going into OpsRamp is this continuously expanding ecosystem. So we currently have 3,000 integrations and we continue to expand those integrations because we follow our mantra and say we're going to bring everything under a unified observability framework. And then the other piece is how do we bring the day zero provisioning and the day-to-day end operations so that we can help our customers take their applications and their workloads from cradle to grave? And if you have that closed loop integration between provisioning and operations, then you can think about that continuous optimization cycle where you're optimizing workload placement, workload sizing, workload performance, capacity, cost, all of those things. So there's a lot of work to do, and we'll continue investing in it. One of the things that's happened after joining HPE is I think our innovation curve has actually accelerated. That's very exciting.

Aubrey Lovell (10:02):
Thanks, Michael, for bringing us that chat with Taruna. That seems like a massive leap forward in tech, and I can't wait to hear more. So we'll rejoin the interview in a couple of minutes.

(10:14):
So it's time for Today I Learned... The part of the show where we take a look at something happening in the world we think you should know about. And Michael, I know you have one for us this week and involves dogs. And ironically, my dog is barking in the background, so if you hear her, she's participating in this story as well.

Michael Bird (10:29):
I was hoping for a dog cameo on this bit. Anyway, so I've got a story from this side of the pond, and as you said, Aubrey, you have dogs. You love your dogs.

Aubrey Lovell (10:38):
I do.

Michael Bird (10:38):
Because the UK has just become the first country in Europe to start selling cultivated, lab grown meat, and it's beginning with a dog treat.

Aubrey Lovell (10:50):
That'd be nice.

Michael Bird (10:51):
Perfect timing.

Aubrey Lovell (10:52):
She wants one.

Michael Bird (10:54):
Now, as the first week of February, a chicken based dog food has gone on sale in the UK using a fully lab grown chicken meat. It uses cells taken from a chicken egg, which are then cultivated in a lab and combined with the rest of the ingredients that usually go into dog biscuits. Now, there are only a few countries in the world where lab grown meat is certified, and in most cases it's still a niche industry. There's very little commercial demand because it can't be sold as food, so the production capacity is limited. But with that in mind, it's hoped that this first step in the UK will lead to a massive expansion in the market and human grade food in the near future.

Aubrey Lovell (11:32):
Great story. Thanks, Michael. And thank you, Emma, to your cameo dog bark appearance.

Michael Bird (11:36):
Thank you, Emma.

(11:40):
Well now it is time to return to our guest, Taruna Gandhi, to talk about the bringing together of data systems and dashboards.

(11:48):
What are the big challenges when it comes to accurately presenting the right data and the right insights to the right people at the right time?

Taruna Gandhi (11:55):
Well, that's, I don't know, a trillion-dollar question. But it goes back to solving that human machine interface problem. One of the things in OpsRamp is that the architecture from the beginning is set up assuming that IT will become a service provider to the business. So it's multi-tenant, and so we can provide visibility from a tenant perspective or a business unit perspective or a business application, or we can do that whole service level maps to it. But we continue to evolve the user interface as we are assimilating more and more of the latest AI techniques.

(12:32):
So the goal of that is to understand what the role of that person is. Is it an executive who just wants a high level view? Is it an admin who wants to roll up their sleeves and dig in? So that's the work that needs to continue. It is there in the product. You can build different dashboards. It comes out of the box, but you can build your custom dashboards and provide that high level view. But more and more, as we get our generative AI and our conversational assistant online, that will help accelerate how we interface with the product.

Michael Bird (13:06):
So what's next for OpsRamp? What do you think the technology will look like in say, five or 10 years?

Taruna Gandhi (13:13):
Oh, wow. Five or 10 years, wow, that's thinking really ahead. I envision a product that really does get to that third level of human machine interface where it is becoming predictive. So right now, a lot of products can solve a known-known problem, which is, it's a known issue with a known answer, and I can automate that script and make it work. The next thing is, it's an unknown problem with a known resolution to it, and that's where the next level is, where AI can actually say, "Hey, by the way, this is something you could try." It's not based on an existing pattern, so it's not that it knows this is going to happen, but it knows what the resolution is.

(13:57):
Then the third, the final ultimate is to solve that unknown-unknown problem and actually solve it before anybody becomes aware of it. So that's what I envision. I think we are living in some fascinating times. On one hand, the infrastructure is growing, it's becoming faster, the deployments are getting larger, the data is exploding. But then so is the technology getting more and more mature that we can make sense of our world?

Michael Bird (14:24):
So final question, why should our listeners be paying attention to the evolution of operations and dashboards and services?

Taruna Gandhi (14:31):
Like I said, it's a journey. Like everything in life, as they are growing, they should be paying attention to how they are managing their IT estates. We've gone from monitoring, which was a very passive activity to observability, where we are taking all the telemetry information and what we are moving our customers to is autonomous IT operations, where the operations tool is able to sense the world that it lives in, it's able to continuously learn so that it gives actionable insights that can be automated. So that's what the IT department should be paying attention to is how can they move IT, especially IT operations from a cost center to a value center? And that requires alignment with the business unit, understanding what the business goals are and being ready and ahead of the business demands. And I think that's where we are leading our customers to.

Michael Bird (15:28):
Amazing. Taruna, thank you so much for joining us on this episode of Technology Now.

Aubrey Lovell (15:33):
Thanks so much. It's been great to hear from Taruna, and thanks for bringing us that, Michael, as always. You can find more on the topics discussed in today's episode in the show notes.

Michael Bird (15:44):
Well, we are getting towards the end of the show, which means it is time for This Week in History, a look at monumental events in the world of business and technology, which has changed our lives. Aubrey, what was last week's clue?

Aubrey Lovell (15:56):
All right, readers are on. The clue last week was, it's 1949, and this global trip was a real high-flyer. Any ideas, Michael?

Michael Bird (16:05):
Yeah. I think last week I said something like the first circumnavigation of a jet or something. I think it's something to do with a jet bomber maybe or something. I don't know.

Aubrey Lovell (16:16):
Well, you're dead on. It was the first ever nonstop circumnavigation of the globe by air.

Michael Bird (16:23):
Ooh.

Aubrey Lovell (16:24):
Pretty big deal. So yes, this week, 76 years ago, a B-50A bomber... Nailed it, Michael... Called Lucky Lady II took off from the Carswell Air Force base in Texas and was in-flight refueling, circled the earth nonstop. It landed back at Carswell after 94 hours and one minute-

Michael Bird (16:43):
Wow.

Aubrey Lovell (16:43):
Having traveled 23,452 miles, which is 37,742 kilometers. That's pretty crazy if you think about that. 94 hours-

Michael Bird (16:54):
Wow.

Aubrey Lovell (16:54):
How do you keep yourself sane up there that long?

Michael Bird (16:57):
I guess multiple pilots, multiple pilots, lots of people sleeping.

Aubrey Lovell (17:01):
Definitely. Definitely.

Michael Bird (17:02):
That's [inaudible 00:17:03].

Aubrey Lovell (17:02):
Wow. It took four risky refueling missions to complete the flight, but proved that the feat was possible using standard military aircraft. The only modification to the B-50 was an extra fuel tank in the bomb bay. Very interesting.

Michael Bird (17:15):
And just to clarify, Aubrey, that B-50 isn't a jet bomber. It did have radial engines, propellers, so I was wrong in that sense, but I was right in that it was a long flight. I just-

Aubrey Lovell (17:27):
You were close.

Michael Bird (17:28):
I want to be pedantic about airplanes. Anyway, the clue for next week, Aubrey, it's 1953 and this twist revolutionized science. This twist, revolutionized science. What is it?

Aubrey Lovell (17:42):
Ooh.

Michael Bird (17:43):
Twist.

Aubrey Lovell (17:44):
Maybe it has something to do with DNA. I'm just throwing it out there. But I don't know.

Michael Bird (17:47):
Oh, yeah, like double helix.

Aubrey Lovell (17:48):
It's got to be.

Michael Bird (17:49):
Fifties. Fifties, that feels a bit too early for DNA. Anyway, we'll-

Aubrey Lovell (17:50):
Look at us go. We're getting really good with this.

Michael Bird (17:55):
We'll find out next week. And that, of course, brings us to the end of Technology Now for this week, and a huge thank you to our guest, Taruna Gandhi, head of product marketing at OpsRamp. And of course to you, thank you so much for joining us.

Aubrey Lovell (18:08):
Technology Now is hosted by Michael Bird and myself, Aubrey Lovell. This episode was produced by Sam Datta-Paulin and Lincoln Van der Westhuizen with production support from Harry Morton, Zoe Anderson, Alicia Kimson-Taylor, Alison Paisley, and Alyssa Petrie. Our social editorial team is Rebecca Wissinger, Judy Ann Goldman, Katie Guarino, and our social media designers are Alejandra Garcia and Ambar Maldonado

Michael Bird (18:30):
Technology Now is a Lower Street production for Hewlett Packard Enterprise. And we'll see you the same time, the same place next week. Cheers.