Vijoy Pandey, vice president of emerging technologies and Incubation for Cisco, explains why automation has become an absolute IT necessity. The video is below followed by a transcript of the conversation.
Michael Vizard: Hey, guys, thanks for the throw. We’re here with Vijoy Pandey, who’s vice president of emerging technology and incubation for Cisco. We’re gonna be talking about all things related to automation. Vijoy, welcome to the show.
Vijoy Pandey: Thank you, Mike, pleasure to be here.
Michael Vizard: Right now, everybody is struggling, looking to find people, hire people, retain people, and this was an issue before COVID came, but it seems like it’s much worse these days, and there seems to be no end in sight. So, what is your best advice to folks about how to think about managing talent these days?
Vijoy Pandey: Yeah, I think that’s a pretty important point you raise there, Mike. Just like everybody else, we’ve been seeing not just news articles around the great resignation, but also we’re feeling that inside of Cisco as well. We know that our partners, our customers, all of us are feeling that pinch, where it’s incredibly important to retain top talent, but it’s also very hard to find talent, given the trends that we’re seeing around us.
Anything about cloud computing, anything about AI, all of those things. So, we think of the problem in a very different way. We think – and we’ve done a bunch of surveys inside of Cisco – what we realized was given the global nature of events – we know some events unfolding right now – and all of the geopolitical events happening, all the pandemic, people really are realizing that life is too short.
It’s not a pithy statement here, it’s actually people believe that life is just too short, and they actually want to do meaningful work. They want to make an impact, not just to the team that they are with, nor the company that they’re with, but even a global impact with the work that they do.
But they also want to grow and learn, and make sure that they are on a path themselves towards meaningfully improving their own lives. So, I think those are pretty important characteristics that we have gathered, and as organizations and as teams we need to harness that desire to make both local impact as well as global impact as well as figure out how to drive meaning into everybody’s personal lives – yours, mine, our teams’, and so on and so forth.
So, there’s a bunch of things that we are doing inside of Cisco to make sure that this meaning, or meaningful impact, is nurtured. One of the things that we keep on saying is that yes, there is a business to run, but there’s also an avenue we need to give our employees and our teams to innovate, to look at impact beyond the run-of-the-mill business that any corporation needs to do.
So, typically what we end up doing is we end up taking problem statements that we face, let’s say, as a team or an organization, and we start splitting it into buckets. So, think about buckets that deal with run-of-the-mill business, because that, you need to absolutely take care of.
But also, there are buckets that you need to innovate around or do meaningful work around. So, we have a portfolio management system inside, at least on my team, that says let’s take 60 percent of your time and make sure that that’s allocated towards run-of-the-mill business as usual projects, and then maybe 30 percent of the time which is future-looking and adding new features or looking at new markets and so on and so forth, and maybe 10 percent of your time is actually towards growing yourself, nurturing yourself, or making some meaningful impact on the global stage. So, that’s actually how we’ve been viewing the problem.
Michael Vizard: Early on, I think a lot of people were intimidated by automation, and there was concerns that people might lose their jobs. Now, I wonder if we’ve flipped that entirely, where people are saying hey, I don’t really wanna work for organizations that don’t have automated IT process in place because of your points – there’s just things that I don’t wanna spend my day doing anymore. So, has the whole conversation flipped, as far as automation is concerned?
Vijoy Pandey: I would say the conversation is flipping as we speak, again, yeah, going back to the previous comment, yes, people don’t want to spend time on repeatable tasks, on things which a computer can do better than you and I can do. I have this constant struggle with my kid nowadays as to why do I need to learn grammar when there’s Grammarly? But that’s a different matter.
But I think it’s a similar mindset going through every individual in the workforce, as to am I really adding value in the workplace, and am I being more productive, which in turn translates is the organization being more productive, which in turn translates to is the economy and the country being more productive.
So, I think the bump towards productivity is definitely a goal that people are more concerned about, and you hear the other side of this, which is, as you pointed out, is the digitization of the workplace is the digitization of all economy. That’s in progress.
We’ve called that using various phrases – software eating of the world, or the API economy – whatever term that you want to use. But we are moving towards a world where software is critical in driving everything that we do. Software in terms of automation, or even beyond that, is definitely key to whatever we do.
Michael Vizard: Not too long ago we all thought we’d be running around by flying cars by now, and that IT would be easy. We’ve seen neither, and it looks like IT is getting more complex than ever. So, my question to you is is IT getting to the point where it is just too complex to manually deal with and we need automation, because we are seeing all these microservices, serverless frameworks.
There’s all our existing monolithic applications, it’s distributed all the way out to the edge now. Have we reached some sort of inflection point?
Vijoy Pandey: Yeah, I think to your point IT is definitely way more complex than it was even a decade ago, and I think the crux of the matter is that the way you are building applications and all of the digitization that we talked about is actually taking place in a very, very distributed manner.
So, as an application developer, first and foremost, we at Cisco like to say that the application is your brand. So, if I am a bank, how my customers interact with the apps that I build defines me, my company, my bank, as the brand. Because if bank A has more capabilities in their software, their mobile app, versus bank B, I will migrate towards bank A.
So, I think the application is becoming the front end to everything customer experience is all about. So, if you take that notion and play it out, that means the application developer that is developing those applications is under extreme pressure to deliver velocity behind features, do deliver trust with the data of the customers, to deliver uptime and security and so on and so forth.
So, which means that they are picking and choosing all of these APIs that exist anywhere to make their job faster, easier more secure, more trustworthy. So, if you think about that kind of an environment, as a developer, I’m picking APIs from cloud providers, SaaS providers, I have legacy systems, I have transaction systems, I have edge devices, in the case of a bank. It might be sitting at a branch office.
I have all of these APIs and systems that I need to interface with just to build one particular app or feature. So, in this kind of a distributed environment, think about the IT – more IT people, right? It’s like I’m trying to build a platform that caters to these kind of demands, and so it is definitely getting more complex, it’s getting more distributed, and every provider in the distributed environment has their own semantics, their own lifecycle management behind their APIs and their infrastructures.
So, automation – I mean, it’s just humanly impossible to not just deploy but even manage and observe such a highly distributed – and secure, by the way – such a highly distributed system. So, automation is key to doing all of this, a direction automation, to me, is discoverability.
It’s intent-based, it’s security, which is there’s no longer a perimeter of security, and it’s observability across all of these end points, API to mainframe. That is key to moving forward.
Michael Vizard: Do you think as we go along that organizations – at least some of them I talked to, it’s almost like a chicken and an egg kind of issue. They have so much legacy stuff that can’t be automated that they can’t invest in automation, and they can’t necessarily buy all new platforms tomorrow. So, how do we get over the automation hump to kind of get from point A to point B without necessarily breaking the IT budget?
Vijoy Pandey: Yeah, that’s a great point. I think some of that, I’ve dealt with in my previous lives as well. The way to do that is – and there’s no questions about it, that for some period of time, there is going to be more chaos and more money spent than before that time or after that time.
So, we just have to acknowledge that as vendors, as customers, as organizations, that for some period of time, there’s going to be turmoil. That’s the way, at least, I’ve handled it in the past, where you say let’s put milestones, where we say maybe we look after a pocket of the organization, and say we’re going to build this out in a highly automated, distributed, cloud-first, API-first manner.
This part of the application, this part of the infrastructure goes out and does that. To do that, we’re going to do a clean slate process here. So, we’ll think about – we won’t get ourselves bound to organizational boundaries, skill set boundaries – that is very hard to do. Most people’s jobs, peoples’ skill sets, organizational structures, all of that.
But we have to try in some pockets, and then give ourselves strict guidelines and metrics, and try and meet those metrics. If we meet those metrics, the resulting outcome is that I will be spending less moving forward than I’m spending today.
So, I might spend a little bit more in getting maybe SREs or software engineers, and marrying them up with IT folks or architects, and getting something going. I’ll give myself a timeline of let’s say a year or 18 months; it cannot be longer than that, otherwise it’s a science project.
But after those 18 months, these are the metrics I’m going to come back to. I’ll get X percent improvement in productivity, and Y percent reduction in head count, let’s say. We shall measure ourselves to that objective, and I’ve seen that work.
If it works – and start with something simpler. But go all the way, don’t go 80 percent. Let’s not do 80 percent automation or 80 percent of the use cases. Hundred percent automation, 100 percent of the use cases for this pocket of your environment, and then grow that out over time.
Michael Vizard: We, of course, hear a lot about artificial intelligent and AI Ops. Are the machines gonna save us from ourselves? What’s the reality of AI?
Vijoy Pandey: To me, AI is a tool, just like all of the other tools that we’ve talked about, which is we’ve talked about automation or infrastructure as code, we’ve talked about cloud native and serverless and microservices. Each one of these tools, programming and scriptings tools.
So, all of these tools bring in something to the table, and infrastructure as code brings in consistency and intent-based infrastructures, and serverless and microservices, or cloud-native, bring in immutable architectures.
The fact that you can grow and scale out and do all of those things, and availability goes through the roof and velocity goes through the roof. Similarly, AI and ML bring in insights to the table where it was humanly, again, impossible to do that just by looking at the vast variety of data and the deluge of data coming our way.
If we could just take all of that – and it’s all unstructured. So, if I could take all of that and somehow put it in a structured database and somehow make sense of it as an individual, sure, we don’t need the AI or ML. But if I need to take all of that unstructured data and make some sense out of it, there’s no other way out, and I do need AI and ML.
I mean, I do need some statistical mechanism first, to figure out and make some sense out of it. I do need AI/ML, maybe deep-learning, to make some sense out of it. But then I need to marry that tool with subject matter expertise, I need to marry that tool with what I as an individual, or as humans, we’ve learned in the past, because AI doesn’t have that context.
Yes, we can do learning, all sorts of learning, but it doesn’t always work in all kinds of environments. We need to marry that with subject matter expertise, with some boundary conditions, and then we need to marry it with actions. Because AI/ML is gonna give us insights, but somebody needs to take actions on the insights.
So to me, it’s a tool in the toolbox, and we need to leverage it when it makes sense. We need to rely on subject matter expertise when it makes sense, and eventually things will get to a point where we need to go to the next level of abstraction.
So, it’s always a game of moving that level of abstraction higher and higher, and that’s what we are after. So, maybe someday there will be flying cars and robots that will take all our jobs, but not right now.
Michael Vizard: How do I bridge this divide in IT that maybe we don’t talk enough about, but there’s clearly a DevOps community that’s very programming-centric. The use APIs. Then there’s traditional IT administrators that use ITSM tools. They tend to be more graphical in nature. As we move forward with automation, do you think that those two camps are gonna converge, or how will this all play out?
Vijoy Pandey: In my opinion, I think they have to converge. I think each one of those pieces have their space in the hierarchy of things. One of the things I learned pretty early on in one of my previous lives is what good is a dashboard if you cannot take an action on it?
So, if you think about all dashboards that exist today, eventually, there is data being presented in a certain way about a certain problem, so that somebody can look at that and take an action. If you think about infrastructure as code, it’s exactly that.
It’s basically let’s remove the dashboard, and let’s figure out what goes – triggers that, that allow me to take those preset actions. Let’s try and remove the action of a human looking at a dashboard, thinking about it, and taking some action on it.
Now, again, I’m describing utopia, but I think that’s where, as engineers, as operations folks, we all need to move towards. To me, dashboards are a good start when the problem is less well understood. As we understand the problems better, we need to move towards code.
Dashboards will still have their place in helping us understand more and more complex problems, but as problems are better understood, they need to move towards code. And that’s the way at least I think through it.
Michael Vizard: All right, so automation needs to be our new North Star, as it were. Hey, Vijoy, thanks for being on the show.
Vijoy Pandey: Thank you so much, it was a pleasure, and I enjoyed our conversation.
Michael Vizard: All right, back to you guys in the studio.
