Sageable CTO Andi Mann on Observability and IT Ops

foreign speaks we're having a wide-ranging discussion about digital transformation about observability about it Ops and devops including the role of AI on those topics to discuss that I'm joined by a major industry expert with me is Andy Mann Global CTO and founder of sageable Andy happy Friday to you hey James it's great to be with you again so amazing based on your latest research digital transformation there's so much going on with digital transformation it's such a catch-all term I think it basically means using software and Hardware to make our lives more streamlined but there's a lot underneath that what technologies are bubbling up to the top as as you see it yeah James um at sageable we recently did research it's unpublished so you're getting a scoop here within the next couple of months or so I'll be publishing this but we researched 20 different Technologies in digital transformation and I asked respondents of Enterprises and a mixture of senior Executives all the way down to individual contributors but organizations of this of a decent size what were the most important so not just my opinion here James but the five that bubbled up to the top I'll tell you cyber security is always number one right um it's the long-term leader it's it's it's the MVP of the I.T stakes and digital transformation is all things to all people but you're one thing you've got to make sure is you're not leaking customer data you're not linking proprietary information you're not getting hacked and so cyber security bubbles up to the top in every single category uh by by business size by individual role uh by goals all sorts of stuff so cyber definitely most important um public Cloud software as a service so SAS so if digital transformation is doing manual stuff in digital computer ways one of the easiest ways is to adopt software as a service so rather than doing manual billing you go out and get netsuite for example right so that obviously makes a lot of sense too so not a new idea necessarily but but still hot after all these years exactly exactly because it's just it's such an easy way by signing up for a cloud service right right right um third is devops no surprise there again right I've actually got a a whole research note on why devops actually contributes to digital transformation you know it's a it's a way of doing new things in new ways it's a way of iterating quickly using Cloud resources for example uh using devsecops to be able to create and deliver new capabilities in digital forms really quickly using devops so we've seen that over a long time creating this faster iteration and Innovation cycle so that makes sense as well sure what else have we got uh just look at my notes Here API Technologies again if I want to adopt something new that's that's digital instead of physical think about if I'm building widgets and shipping them to people then instead of doing manual shipping I just used FedEx's API or I use UPS or usps's API right and I use that API and all of a sudden my entire shipping process is now digitized so again that makes sense to me um it does so the one interesting thing about the API is being on the list is that of course EPA is is a classic that's been with us for quite a while too so it's not the the things leading digital transformation are not necessarily like oh gosh they're so brand new these are in many ways tried and true favorites actually true James um in the research that I'm looking at and and to some degree this also makes sense because a lot of these businesses I'm looking at Enterprise businesses right these people typically will have Legacy systems and traditional systems installed on premises maybe uh they might have you know multiple locations and geographies uh different skill sets as well they've got uh inertia in terms of being able to manage change at PACE right and so it actually sort of makes sense to me that traditional Technologies which are well proven but which provide that shortcut right get you into Cloud to get you into digital it actually makes a lot of sense to me um probably and rounding out by the way rounding out the five is platform as a service again it's pre-built right so think about dreamforce as a platform as a service jump on build what you need using their fourth generation language all of a sudden your customer engagement process is now digitized because you've used that platform and all of the sub substrate you don't have to build so again not a new technology in a lot of ways I mean Salesforce was the first SAS provider right back in the 90s even sure right way back and so this idea of using existing technology it's a really good point James I'm gonna have to write that up interesting of the five and the five all make perfect sense in a platform as a service of course um I I'm curious your machine learning slash AI was not on there but I guess it's not it's still you know on the growing hype curve as opposed to being a tried and true element yeah yeah look machine learning and AI is really interesting and I did ask about that separately as a technology and it did not come to the top five yeah but I actually believe that ML and AI is more of a feature than a technology per se when it just comes to these kinds of digital Transformations um you're applying ml applying machine learning to something you're doing you need something you're doing you to for it to learn from so obviously in it Ops this is very much manifested around I.T operations analytics and AI Ops and ml Ops and all of this sort of stuff right but again this is interesting back to your earlier Point James even machine learning is not that new foreign some of your audience may remember and I certainly do amigamon on mainframes 30 years ago actually had Dynamic thresholding we called it right okay the what was normal and figuring out what was abnormal and creating a threshold based on that learning is that machine learning probably not really but you know it's the precedent for where we are and so bringing itoa bringing a i Ops and normalizing machine learning and bringing in some of the algorithmic or artificial or Advanced or augmented intelligence whatever the a in AI stands for right right Ops I've been doing this for a while but that's where it's coming in it's coming in through observability it's coming through AI Ops coming through itoa and I'm seeing some other uh use cases in itops and incident response especially all right you you use the word observability it's been hot for a while it seems like it's I've seen headlines about observability it seems like it's getting more hot as it infrastructure gets more and more complex we need observability more because we there's more to observe I mean what trends are you are you see seeing driving this modernization of it monitoring the observability thing's really interest so hot my goodness my friend um taking briefings every single day around observability what is observability is the interesting thing for me is that observability is not a technology or a market really it's a way of looking into something right it comes out of Manufacturing Systems right the idea that you could observe what is happening inside an opaque system and we're using that in it but the fact that the term came from this very general industrial use case means that we're now using it to apply to everything we do so it's a floor polish and it's a it's a dessert topic so we're getting observability for it Ops that's great that's part of the AI Ops landscape it's part of monitoring it's part of it operations management I.T infrastructure management is providing much better capabilities because it's real time it's actual signals not synthetics or simulations it's actually it's communicating not just infrastructure metrics like response time on service level but also business and business metrics so maybe revenue or customer ID or something like that you can actually make business decisions on as well and it's amazingly suited to Cloud native development in ways that traditional monolithic monitoring tools absolutely were not so that's one area I'm seeing but I'm also seeing it applying observability for software development so looking into the software pipeline observing observing the software development process so observability as a term it's an interesting one um I'm a big believer in it I think it's fantastic I helped create that space when I was at Splunk yeah but I do think that it's getting overused there's a lot of Ollie washing if you will but it is an interesting concept that is applicable to lots of different parts of it operations and devops do you think that uh companies are actually implementing observability is there any way to quantify like x amount RX amount already is it still is this still nascent on the cusp upward are we are we here to completely mainstream uh adoption yeah look it's it's hard to tell in some ways because a lot of the you know you can't just do normal Market sizing kinds of exercises and research like sageable does because observability is not a market observability folds into log management into it operations analytics into AI Ops into value stream management yes into APM or so it's not it doesn't stand alone and so when New Relic or pager Duty or Splunk or whoever when they sell a product are they selling it for monitoring are they selling it for observability it's it's it's a bundled case but I'll tell you I'm talking to clients who are absolutely doing it it's an advanced move it's not something that I'm seeing a lot of on-premises infrastructure for example Legacy or traditional applications very difficult to apply observability in those use cases but for modern Cloud native developments I'm absolutely seeing uh Enterprises applying it often in conjunction with some of these other Technologies with in conjunction with API Technologies to be able to get at and understand performance within a partner's function rather than just within my own system or to be able to connect my on-premises with my cloud through those apis so yeah I'm definitely seeing it but it's not Standalone Market feel the more the mod Ule the monument observability it will become part of the substrate of the it operations landscape interesting okay uh I also talk about it Ops and and devops I mean clearly we know that AI is everywhere and creeping into it apps do how is machine learning and AI impacting it Ops and devops today what do you see in the near future here oh wow it's it's it's look it's everywhere I mean everything's Ops right fin Ops we've got devsecott's got value Lots we've got net Ops uh yeah devops is the is the the original it's the OG right um and again devops is not a technology it's a way of working it's a cultural approach so devops persists and we we started to take the concepts of devops in re in in in practice so things like continuous delivery automation uh uh you know measuring what matters some of these technology aspects to devops and apply them to other areas so now we're using ml Ops for example using collaborative principles to manage the algorithms of machine learning um you know devsecops using the collaboration communication integration between teams but now including the security team as well as the dev and Ops Team so so these things all all come around AI Ops is is another star Ops to me um it's all Ops part of this I think James is because we've spent a lot of time on what I like to call Big Dev little Ops right so it's Dev Oxford it's mostly Dev how many life cycles did you see finish at release right devops life cycle ends at release that doesn't make any sense now operations is I won't say catching up but applying its own rigor and discipline to this idea of collaboration communication integration delivering apps faster and better and so applying things like AIX AI for um for for code quality for example if it operations are equal Partners in quality decisions pre-release then let's get some Automation in there it has been automating stuff for 40 years right we want to do what every novel thing we want to do it one time and then automate it so things like using AI to do code quality inspections using AI to do anomaly detection and oh Dynamic thresholding we talked about before it's still in important using observability to feed AI engines to create anomaly predictions these are the sorts of areas where AI is coming into it Ops because within the devops landscape now where we're no longer a Service Unit to the to the dev team we're now able to be reliability Engineers platform engineers and so applying Ai and machine learning and these sort of AI Ops Technologies and using the data we're getting from observability tooling is providing this opportunity for it Ops to really accelerate that path of innovation makes perfect sense actually um all right the final question uh I want to ask you about the the next big thing for option I'll give you my pet Theory which you can either disabuse me of or humor me of I'll let you know so it's thinking about AI Ops which I think is traditionally as artificial intelligence for operations which which often manages the I.T department but I think it's it will finally grow to really AI apps will manage the entire business make any sense to you or not and or what's the next big thing in opposite any rate yeah look I love that James um because exactly as I said observability is now accessing data that we never got before historically we would get performance response time storage load latency all these technical metrics observability is able to get at anything that is emitted by the system so if the system is admitting uh you you know things like uh product codes and now I know which products are more popular I can put that into my marketing campaigns um repeat buyers now I understand at least to some extent why buyers come back to my store and so I can continue to you know promote that to new customers so they'll come back for repeat buyers so this is just a couple of metrics we're getting out of observability we never got before which are business metrics so I absolutely believe in that I think for the senior people ctOS architects who are creating the next thing then that's going to be huge being able to pull signals out of your applications and feed them into business units to make business decision super I love that James um a couple of other things that's going to play out I think for devops leaders for development leaders uh value stream management is huge this idea of observability for the software development life cycle value stream management what is it I think I understand what is value stream management oh so value assume management again we're still in terms for industry um every time you add a new component think about building a car if I add or steering wheel I'm adding value when I put wheels on it I'm adding value gotcha okay you stream management is managing every bit of new value you add so in a software world planning coding testing QA released these are all separate phases that add value so value stream management and it is monitoring the software development life cycle more efficiency faster better teaming uh you get people working on things they love rather than things they maybe don't you know more more Innovation less bug fixing um you know so so value stream management I think is really going to be important software development observability is another term I've heard for that by the way um and I think for the for the coal face it Ops individual contributors applying AI to problems and incidents again we've seen that for a long time about you know dynamic thresholding but now we're getting AI that's actually doing things like going out and collecting more triage and troubleshooting information automatically based on which service is affected or which users are affected accessing documentation so that I don't have to go and look at yeah so things like speeding up the recovery process but also making recovery easier for level one without calling out level two or level three all of this applying knowledge to the work we're already doing see I think of AI as augmentation more than anything else because for experts like devs and Ops there are always things that the AI will never know and never be able to do so being able to get the AI to augment our own intelligence so that we can focus on unknown unknowns right that's where I think AI goes in the IT world fascinating stuff Annie thank you uh so much for your expertise today I hope I want to keep up with sageable what's going on is there by the way a release date for the report that you mentioned oh James don't don't push me on a hard deadline please I know no deadlines my deadline is yesterday James I want to get you gotcha I'm looking at a early July release I want people to be able to take this away on vacation have something pleasant to read nice nice all right Annie thanks so much for stopping by and please come back and talk with us again sometime thank you very much thank you so much for having me it's always a pleasure

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