In this DevOps Chat, we speak with Sinead Glynn of IBM about some coming trends in Cloud Service Management, ML/AI, ITSM, DevOps, ITIL and SRE. A lot of buzzwords in there, but there is also some good information here. Sinead is a great interview.
As usual, the streaming audio of our conversation is directly below, followed by the transcript of our conversation below that.
Alan Shimel: Hey, everyone. It’s Alan Shimel and you’re listening to another DevOps chat, and – here on DevOps dot com. Our guest for today’s chat is Sinead Glynn, Offering Manager, IBM Operations Analytics, IBM Hybrid Cloud. Sinead, did I – did I get that right?
Glynn: Yes, you did, Alan. Thank you. And thank you for having me.
Shimel: Thank you. It’s our pleasure to have you. So Sinead, you know, IBM titles are always kind of very descriptive but why don’t you give our audience a little bit more here. What exactly is your role with IBM? What do you work on? What do you do?
Glynn: Sure, yes. Yes, so I’m an offering manager here with IBM. Offering managers would be known as product managers in other companies. We focus on offering because it’s more – it’s more than just a technology discussion. We kind of go broader and look at the full solution.
In terms of my own area of specialty, it’s around the operations management and the broader management capabilities from an IT perspective, so it’s your centralized IT operations teams, your DevOps teams, and the management capabilities that they need.
In terms of the offerings I specialize in and the area I specialize in, I have a background myself in development and, in particular, the development of machine learning and cognitive technologies. So my own focus is in terms of bringing those capabilities to market and, you know, explaining how that – they benefit the IT operations teams and the DevOps teams.
Shimel: Great. So Sinead, you know, machine learning and its, you know, its Siamese twin, AI, seem to be on everyone’s lips these days whether we’re talking about Dev, DevOps, Ops, security, testing, or big data, or hybrid cloud, or cloud private or whatever, everyone has a story around ML, machine learning.
Shimel: But we’re really here today to really focus in on machine learning as it relates to cloud service management. Right? You know, I – my personal belief is that over the next five, ten years, machine learning and artificial intelligence, AI, is going to have a profound input – impact on a lot of different things that we do. But at a high level, Sinead, talk to us about, you know, what kind of impact machine learning is having on cloud service management specifically, and why it’s sort of become an essential piece of your cloud service management.
Glynn: Sure, yeah. So I suppose, you know, there’s two dimensions or two primary dimensions to cloud service management. There is the complexity of what you’re managing, you know, hybrid cloud was something we all talked about, you know, 12, 18 months ago that has morphed into multi-cloud. So, you know, management organizations, they’re handling their kind of traditional systems of record and they might have a number of public clouds and a number of private clouds that they’re using.
So there’s the – there’s the complexity dimension and certainly machine learning provides the ability to manage that complexity when you don’t have the ability to suddenly grow your teams. So you can’t add people.
But the other – the other dimension is how you manage. So it is that change in the process and the change in the culture that is required to be successful when you’re doing cloud service management. So, you know, it’s that move from, you know, months or even a year of preparation for a new application to be rolled out, it’s very much that agile versus traditional model and that, you know, DevOps stroke Lean versus your ITIL view of the world.
So it’s enabling at the roles and it’s enabling those roles to be successful in cloud service management in terms of how you manage, not just what you manage.
Shimel: Fair enough. So, you know, Sinead, I – I’ve – we both have been in this – in this business for more – a couple of years. Me longer than you, probably – you’re much younger. But, you know, we’ve seen sort of the rise of – of IT service management and things like ITIL, and, you know, traditional ITSM, and they’ve kind of ruled the roost here 15 years or more, 20 years or more. Right?
And now all of a sudden we’re seeing, you know, things like DevOps and Lean IT, and even sort of some of what we take from Agile. Right? From the Dev side of the house. You know, almost Agile for Ops if you will. And they – you know, and they’ve all been kind of chipping away at that ITSM model.
And then most recently, of course, we’ve introduced this term of SRE, site reliability engineering. And now this, along with things like machine learning, really seem to be changing, you know, traditional ITSM at – at its core. I mean, it’s really kind of rewriting the book or – I mean, really forcing us to reexamine some of our ITSM, you know, core values and principles, ways of doing it. What do you think about that?
Glynn: Oh, absolutely. You know, ITSM was very much focused on – or is, it’s not a was thing. Is very much focused on operational excellence about, you know, being that gatekeeper to ensure that only high quality applications are deployed and very, very process-centric and control-centric, typical kind of waterfall type methodologies, and that was very effective before the real transition in terms of how business is running.
So business – business must have digital engagement. Business must have agility in order to innovate, in order to keep your clients and grow your client base. And that, you know, operational excellence stroke, you know, very process-centric risk adverse way of managing just – just doesn’t work. So that’s where, in line with – in line with that digital transformation, the DevOps practices and the Agile Ops has to emerge with it.
And, you know, from an Agile Ops perspective, that’s much more about how can technology help me be agile while still managing the risk and delivering exemplary service? How can technology help me rather than how can I be very process-centric.
Shimel: Yep, and Sinead, though, I – you know, I almost feel compelled to caution the audience that I don’t think your saying, IBM’s saying it, I’m certainly not saying that ITSM is dead. You know, it’s more like ITSM is dead, long live ITSM. Right? And, you know, it’s just – it’s changing, it’s morphing, it’s evolving with – with, you know, new things like AI machine learning, but also with new frameworks like DevOps and Agile for Ops and Lean and so forth.
And this kind of gets at the heart or _____ of SRE. But another fundamental, I think anyway, another fundamental shift in this is – and I’ve heard you talk about it – we – we had the pleasure of doing a video at – I think it was IBM Think a couple months ago – is the kind of the – not the changing customer but the changing kind of world view that – that we need to have over in Ops, and that is the – the, you know, the changing into a skilled service organization rather than the center of the universe.
Glynn: Absolutely. So, you know, it’s – it’s moving the mindset from, I’m the center of the universe, I control everything, you know, with process and controls, et cetera, to, I have to support the required agility in the business. And in order to support the required agility in the business, I need to be much more about being a skilled services organization.
And just on the topic of, you know, is ITIL dead or, you know, it’s usually a coexistence. So, you know, we frequently see, particularly in larger organizations, you know, your traditional IT Ops remains and they need to have a – you know, they may need to have visibility and control across both the traditional and the cloud environments, whereas the software reliability engineer, they tend to service maybe a number of DevOps teams, supporting them in their agile work practices and they’re very much focused on automating rather than throwing people at it.
So it’s very much – maybe 50 percent of the time is worked on – or spent on kind of traditional operations and 50 percent is really looking at, you know, how I can scale this better. How can I automate this better and how can I support? So it’s really that services view.
And there is a transition, you know, there isn’t really clear lines. They might emerge over time but there is – there’s really kind of two types of organizations frequently emerging in the larger organizations and – and it’s because the larger organizations typically have been around for some time. So there’s already a tradition of that – that centralized IT operations.
From a technology provider perspective, there’s a challenge because everyone is trying to do the same job ultimately, you know, deliver exemplary service, but because of the cultural differences and because of the skill differences, they have slightly different views in the world.
So it’s the same thing – they’re managing but they need different views in the world. And I guess our challenge is to ensure that they – the right experience and the right insights are made available to the right types of users to do their job most effectively. But definitely there is that transition towards the site reliability engineer and their needs.
Shimel: Yeah, I’ve heard – I’ve heard people say that, you know, this whole SRE kind of role becomes the Ops in DevOps but, you know, in listening to the way you talk about it, Sinead, again it – it reinforces a continuing maturity sort of view of the world. You know, as a dad or as a parent, you know, every child is the center of the universe. Right? The child believes that they’re the center of the universe. And I think part of the maturation process and growing up is realizing perhaps you’re not the center of the universe. Right? But you are, you know, there’s a big world out there that you’re part of.
And I think that kind of really – when you think about it that way, that’s – that’s the journey for Ops. Understanding they’re not the center of the universe and they’re a part of this bigger world. And – and – but they still have a – a vital role to play, a very important role to play and – and I think that SRE role is in there.
Glynn: Absolutely, absolutely.
Shimel: So, you know, we have this webinar coming up on June 21, 2018, and it – it is, you know, along the lines of cloud service management and – but it really comes from, you know, I’ve seen anyway, a – a changing view of cloud from IBM itself. And, you know, IBM’s not a small company so when their – when their world view shifts, there’s usually good reason for it. Right? And it tends – and it tends to change a lot of others’ world view as well.
And you mentioned it rather casually earlier. You said something like, “Well, we’ve gone from an emphasis on hybrid cloud to a multi-cloud.” You know, dropped that in there. But, you know, that’s – that’s a profound – you know, that – there’s really something here.
Shimel: Talk with our audience a little bit. What do you mean by that?
Glynn: Absolutely. I suppose in the – in the early days, you know, there was a focus on, we have cloud. It’s fantastic. Come buy our cloud. Let me show you what our cloud can do. And I guess through many interactions and learning process, it’s obvious that, you know, no one cloud does all jobs. So it’s about picking the right tool for the right job.
So what we see is that the complexity in the environments that are actually being chosen. So it’s a multi-cloud strategy. It’s not a, I’m going to put everything into one particular vendor, or, you know, I’m going to move all of my workloads exclusively to cloud. You know, they – it’s much more granular decision. Certain parts of the business, you know, usually the systems of record, they may be kept on existing infrastructure and continue to be managed there, whereas the systems of engagement may go to public clouds, they may go to private clouds, depending on your security and data requirements.
What businesses are doing and what smart businesses are doing is, depending on the type of application modernization they’re driving, they’re selecting the right strategy. Which is great for business, it’s a heck of a challenge for your centralized IT operations because of that complexity. So they need machine learning and adaptive automation to help them manage that complexity, to do their more traditional roles in a much better way, particularly when there isn’t that long handover.
You know, apps are pushed out, particularly in cloud, the scaling out of those apps on the infrastructure is, you know, highly dynamic and, you know, when you’re trying to troubleshoot things, you need to get insight. So you need to have insight and analytics and machine learning to help you understand because there hasn’t been – you know, there hasn’t been a communication that this has happened. So all of those technologies are required.
So that’s the – the multi-clouds _____ traditional IT Ops, they, you know, the infrastructure is – is agile, there are multiple clouds that they need to be able to see, and then you have some parts of the organization, maybe growing parts doing your DevOps type practices. And they have slightly different needs. You know, the – the DevOps persona just need to see their own project or the – the applications. The SRE engineer probably services more than one DevOps team.
So they – they have different views and we’re very much focused on ensuring that the management capabilities that we have, particularly around the machine learning and the analytics, that, you know, it’s providing those insights to help those groups do their jobs effectively. So it’s definitely multi-cloud, Alan. It’s not – it’s not hybrid. Not just hybrid. Yeah.
Shimel: I – I agree with you. I think that was a good explanation. While we’re doing definitions and glossary terms, let me break – throw another one at you and that’s IBM’s what you’re calling adaptive automation.
We’ve touched on it, we spoke a little bit about it, but let’s make sure we’re clear for our audience. What do you – what do you mean by that?
Glynn: Okay, well, I suppose traditional automation and, you know, obviously something that’s been around for 40 years, I don’t know, I think we need to go back – that’s about, you know, I know something, there’s a condition, I kick it off on and that condition happens again. Whatever you’re doing. So it’s very much a rule-based or a condition-based automation, absolutely very effective and very valuable.
But in – in the cloud world where things are dynamic, we need to think much more about adaptive automation and there are, I suppose, different types of adaptive automation. Does the type of adaptive automation, you know, if we think about, just as an example, the types of machine learning and analytics that would do things like event grouping. So that’s, you know, looking at real-time – real-time machine learning to reduce the number of events in your environment through machine learning, et cetera, et cetera. So that’s kind of a real-time adaptive automation.
You take it further and you can look at things like maybe proactive automation where you’re using, you know, machine learning to actually learn what is normal and – in your environment and proactively tell you when things have gone abnormal. So that’s more about being able to predict that things are going to happen rather than react elegantly to things that are happening in real time.
And then taking it further, Alan, I mean, there’s a big push – and obviously IBM is leading this in terms of cognitive capabilities, so not just looking at machine learning on the machine data in your environment, but going beyond that and using machine learning perhaps on your human data, your knowledge corpus, and really imbuing those workflows – workflows with, you know, cognitive – to help humans make those decisions even faster.
So there’s different levels of it. Practically, you know, folks tend to start off in that reactive way, using kind of, I suppose, automation in real time to reduce the number of events and to trigger maybe standard automations. And then it’s about moving beyond that to really start gaining the value from the machine learning.
Shimel: Got it. It’s a great time to be alive in Ops, isn’t it Sinead? Right? Think about – you know –
Glynn: I – I think so, yeah. I think so. And I know we – you know, I know some might fear things like automation and machine learning and analytics but I’m fully confident that the complexity of the environments we’re managing is rising much faster – you know, it’s getting so complicated you do need automation and machine learning to manage it.
Shimel: You need it. Right.
Glynn: Yeah, so, you know, I think it is. It’s an exciting time. Yeah, skill set changes, most definitely, but, like, if you – if you look at even, say, something simple like microservices, so, you know, everything is moving to microservice architectures, as far as can tell at least, and yes, that makes the job of development much easier and much more reuse, et cetera. But the – you know, the job of Ops gets a lot harder because it’s a lot less predictable, there’s a lot more data, you know, there’s – how do you see the wood for the trees? How do you pinpoint the, you know, there’s these obscure names on things, et cetera.
So you need insights, you need help to do the job you did, to do it much better. So, and again, it’s always about supporting that digital transformation.
Shimel: Sure. I mean, and it’s really necessity is the mother of invention. Right?
Shimel: No one – no one does things as much as we’d like to think, you know, no-one does things because they’re cool or, you know, just – you don’t do new for new’s sake. You do new because there’s an advantage to it and so much of what we’re seeing around machine learning and automation and these new frameworks and so forth is a response to the complexity, to the changing nature of the way we’re doing business in IT.
Glynn: I wholeheartedly agree. And I have personal experience of this because I’ve been doing this particular role for some time, particularly on the development side, and you know, I would say hand-on-heart, we were probably to market too early with some of this.
Glynn: You know, and – you know, a few years ago it used to be an experience of, wow, that’s really cool, but I don’t need it. It really was, you know.
Shimel: Exactly. Right.
Glynn: And it was, you know, quite surprising, particularly because I – myself, at the time, I was in development so I was very, why – why do you not see this? It’s like, what’s wrong – but you’re right.
Shimel: Well, and it is so cool. Right?
Glynn: Exactly. It’s very cool, but not needed.
Shimel: So that was, like, you know, that was something else that – Sinead, I learned early on, I – you know, my history is I’ve done a number of venture-backed startups in technology over the last 25 plus years and, you know, a hard lesson that I think every entrepreneur learns is you are never going to be successful selling something that’s nice to have. Like, no-one buys things that are nice to have. They look at things and say, wow, that is cool. It’s nice to have.
Shimel: But they don’t write checks until it’s a must-have.
Shimel: And – and that’s really the key. Sinead, we’re almost out of time, here. We’re probably over time already, but before we go, I want you to just give our listeners a place to go. They’ve heard – they’ve heard kind of a little bit about what you’re doing and what IBM is doing around this. Where can they find out more? Where can they engage with your team and – and, you know, start living this and doing – you know, they’re probably all – many of our listeners are faced with this very reality. How can they engage with IBM on this stuff?
Glynn: Absolutely. Well, just from a – I suppose from a Google-search perspective, there’s an IT Operations Analytics page. So if folks do a search on that, you’ll be brought in, and folks can reach out to me, of course, as well. We’ve an IT operations management page as well. For me, I – you know, it’s very hard to separate one from the other because we’re moving more and more towards that, you know, that AI-driven operations. That’s becoming essential – not a nice bolt-on to have and – on your operations management.
So certainly that’s the place. Again, if you go to IBM Marketplace and you look for IBM Operations Analytics you’ll find the details of the machine learning technologies around the, you know, the events and the performance that I’ve mentioned, and indeed, you know, the cognitive stuff.
But probably just to reach out to me, Alan, is a good start. And I can certainly point them in the right direction.
Shimel: Great. Okay, so let me ask the magic question. How do they reach out to you?
Sineed:Certainly. Well, my e-mail address is Sinead.Glynn@ie.IBM.com.
Shimel: And that is S-I-N-E-A-D dot Glynn G-L-Y-N-N at IE dot IBM dot com.
Glynn: That’s me.
Shimel: Got it. Sinead – Sinead, thank you so much for – for being our guest here today. I know I told you it was just 15 minutes and we – we’re probably double that. But I think it was a worthwhile conversation and I’m sure our audience will find it very interesting.
Shimel: Our webinar on this, by the way, DevOps.com webinar sponsored by IBM is on June 21, 2018, at 1 p.m. Eastern – it’s actually Eastern Daylight Time, not Eastern Standard Time. Right? Because we’re in daylight saving time. And 1 p.m. East Coast time.
So you can log on from wherever. If you go to DevOps dot com and under webinars, you could register for the webinar there. We’ll – we’ll have a link for it in our notes.
Sinead, thanks for appearing. Hope to have you – you know, the webinar I’m sure is going to be great but maybe we can continue this chat another time on another DevOps Chat.
Glynn: Certainly, certainly, Alan. And thank you. It’s always a pleasure.
Shimel: Thank you. All right, this is Alan Shimel for DevOps dot com, DevOps Chat. You’ve just listened to another chat. Have a great day everyone.