Panel Discussion: Integrating Emerging Technologies in DevOps for Organizational Transformation

This panel discussion explores the intersection of emerging technologies, DevOps, and AI. The speakers share their backgrounds, emphasizing their extensive experience in application development, cloud-native solutions, and data security. They discuss the evolving role of DevOps within organizations, highlighting the importance of automation, platform engineering, and the integration of AI into development processes. Insights into the Generative AI hype cycle, MLOps, and security challenges in data management emerge as key themes. The conversation also touches on the future of work in tech and the implications of rapid technological advancement on organizational structures and skillsets.

[Music] hello hello every yeah you yeah people folks you are here for the def Ops panel discussion so yeah welcome so um we we can like start by introducing ourselves I think yeah um and we also have to admit that I think we each of us we might have meet met each other at some conferences but this this is like you know like another time that we

got put together and have a panel discussion so yeah and it it I'm sorry actually this is morning time for me like six o'clock or something and and the geese are outside wow that's fantastic so so so Mary where are you where where where have you got geese sure sure I um I'm based in Chicago and actually I just came back from Europe last week I was

at jcon the last thing and and also devox UK before that and then also India too so so I was gone from home for a month but I just got home and so yesterday I was also on the panel but for AI and software development but now I'm on devops and but uh bright and early today not as early but still it's kind of early like six

o'clock or something so yeah yeah so yeah so uh and so I I'll finish so I'm a actually I I've been doing mostly uh developer efficacy for the past six years so I was with data Stacks last but I'm transitioning now to become an AI practice lead for a consulting firm that's based in uh Ohio so I'll be starting that next week and anyway um myself though

I'm mostly I came from more of an application development background so I was a developer for over 20 years um mostly in primarily in Java but then also getting into open source web you know some devops and cloud and all all of these things so um yeah so so that's kind of quickly about me and I'm also an active uh Community organizer sir I I lead the

Chicago Java users group and also there's an AI camp in Chicago I'm the chapter co-lead yeah so so that's kind of The quick summary about me so and also the geese so every morning they make a lot of noise that's that's that's your early morning wakeup call yes exactly chick yeah well in former times I had chickens uh didn't had a chicken my my neighbor had the

chicken and the rooster but he was luckily not a morning guy he starts making his noises at 11 or so so oh was he was like all day long having weekends um yeah but besides that I'm Max I'm the founder of liquid reply we're focusing on platform Engineering Building internal developer platforms uh doing some finops um and develop a couple of Open Source tools or help incubating

open source tools um whenever organizations have an idea of doing something but they uh might don't know how to start it or where to find developer resources to shortly incubate it until it's up and running um besides that I always call myself technology adviser um most of the time in the cloud native space because that's what I'm doing since the last five six years um but I'm

have a very broad interest and and uh yeah participate in a couple of communities and do a lot of Open Source work so I'm part of the cncf ambassador program or also from the Linux Foundation Europe Advisory Board um being there member from the first day and help that to sh shape a little bit the direction of open source for from a Linux Foundation perspective and all

the organizations taking part in that that sounds really interesting uh ronins uh I'm based in the UK uh so uh to me outside it's gray and it's damp and it's wet and it's it's a very dull day I've got no no geese making noises outside I haven't got that that going on uh I've had a uh quite a long career in technology now I've been uh I

started as a developer in the the '90s started as a cobal developer uh and then picked up uh operating systems experiences Unix administrator Solaris administrator uh uh deck Unix as well and and Linux and from there I got the chance to become a a data professional so I uh I started the journey working databases originally Supra uh and ingis uh Supra is a network database engis was

a relational database and then from there migrated to oral and I've been with working with oral uh 30 years uh so uh it's it's stead me well uh so mainly ior Linux uh um part of the an oral Community program called Ace so uh in microsof you have MVPs VMware has v experts orle has Aces so Oracle has three tiers of Aces Ace associate Ace professional and

Ace director uh fact about 700 Aces globally uh and I'm in this top tier of Ace director there about 70 of those I'm in a very a very small group people and it's it's fantastic for me my company I work for and for my customers because uh I get to engage with loal product managers directly and go and speak about oral technology at conferences like this one

uh so my day job I'm a director of field solution architecture uh for a storage vendor called Pure Storage uh so today I I my job really is is advising organizations about data ma management data governance data security uh and how they can use modern ways of working to protect their data uh ransomware being and cyber security being you know big big trends in our industry at

the moment U really fortunate that throughout my career know working with data in highly regulated environment so mainly defense and Aerospace before I became work for a vendor and uh yeah excited to share really uh last week I got my uh my third Us paintting grounded so I've got three three paintings uh granted around data protection and security uh one of those in containers so I work

with kubernetes in the container space as well but really about data protection everywhere how it's done with storage and I've got another a number of other uh us painters which have been filed which I'm hoping to uh get ISU one day but it takes a long time for a painton to it takes a fored and then you have to wait many years like a sausage machine and

hopefully you it will come out the other end it's it's always astounds me that you know that and I have to pinch myself how lucky I've been in my career to have the experiences to be able to do this because to have an idea that you think wow that's that's unique enough to become painted and uh there is it's just it's just like such a thr there

isn't many things that in my career I can look go wow uh I never saw that coming uh from the time of being a cobal developer and they're moving into 4gls to actually having some some ideas of are going to outlive me they'll be on the US statute book with paints yeah but yeah you talk about patent patn or us Rec call patents but yeah I also

have applied to some when I was at IBM and uh IBM is like always like great and encouraging employees to file for patents so so I did that but the closest I got to like you said right I we we did it like many years it seems like finally that one that that actually moved a little bit but it says oh somebody already had that similar thing

so then we got some partial points so to speak and instead of like fully you know being recognized as as another pattern so but yeah it is very difficult to to get I I guess working for a a storage vendor is about sort data security dat protection coming from an application view point of view from the data and the dat base itself I had a different set

of ice so a lot of my colleagues are you know uh Harbor Engineers software Engineers you know talking about nand protection and uh uh the the drivers in the operating system and and that level of detail and I'm coming from the operational data side so it's you know yeah when we look at think of ideas they can come from anywhere they you know our our Engineers uh

in all technology companies you know are very creative uh but uh sometimes yeah you see things differently if you have a different experiences so whether that's from the application and operating system system integration point of view uh yeah we all have different uh yeah bit going on so max very uh yeah I I go to conferences globally and going to Nashville next month to speak at K

scope so what what are your next conferences you said you just come back for some is that you done for the year Mary Max are you uh got anything else no no no there will be a couple of events um talking about my uh own open source community events here Munich um for the commun community days and and others around Europe okay was you in cucon uh

recently yes for sure yeah will you be in cuon there's cubec con China too in Hong Kong right will you be in that one in August you'll be in that oh not that one okay there was a c in North uh North uh North America as well isn't it uh as the Americans like in the fall in the end of the year oh nice yeah but I

think you you were talking about patn and I think that it's actually good good good starting point also to look into like uh emerging Technologies because somewhere they need to come from right and um yeah so maybe you can catch a little bit here the curve towards this topic how um emerging Technologies uh integrated into devops yeah kick on move on push some transformational changes in organization

um in our short preparation we talk about like H how does it actually looks like what what is actually uh yeah an emerging technology right because it's might look for for everyone different so um my thought on that was like looking into the gner hype cycle because it's like the most of the time the source of to choose um at least for decision takers and um at

the moment there's just the version from last year out and which is kind of interesting especially in the space where we are working here with devops and talking about devops um a few topics highlighted there are things like platform engineering internal developer platforms giops um Advanced finops practices and so on um for obvious reason also some good stuff around AI but nothing very concrete nothing very yeah

what you can touch right and I found this kind a kind of an interest uh direction to see because on the one hand side I believe AI is not that far Advanced that it's really on the top of its hype it's may be super hyped but it's not that useful um while other topics which are predicted to be influential in just four to five years like um

giops for example I really don't understand why it's just takes four or five years because practically with most all of our customers we Implement G UPS all day long and it's more like the the stateof the art rather than the future whatever topic what's your perspective that Mary do you go for that yeah well um let let me think a little bit too that's a a very

good question like in terms of U yeah I I think you know for for Gen AI side right for AI side is basically I look at you mentioned about GitHub but there's also all the models that needs to be shared so to speak and there there's hugging face which is sort of like the GitHub kind of con conceptually I think like for GitHub for all the source

code repository then on j i side will be hugging phase that's HS a lot of the you know llms and models for people to do it but that's kind of um interesting too and um so so so that's that's what I can uh kind of uh think of um at this point to to kind of kind of talk about this and let me think a bit too

about this and um yeah and how about you run right yeah yeah I think uh you know even the devops side is interesting to see people have re rebadged themselves yeah from you know a devops engineer to a an Sr to a platform engineer and and we we sometimes use words and they have different meaning different countries different Industries somebody's a devops engineer uh maybe devops engineer

Cuts more code than a an SRE who's more interested in automation tools uh but I think there is a coming together and I think we we we we sometimes think of AI as something which is in one little box you know it's in a large language model and rag but it it's going to be across the whole of our industry uh so you you mentioned there you

know the Change Control the GitHub equivalent for models and then you have standards for the models and how you can distribute them and then there is H the vector databases which uh and that's just another Vector type uh data type and they're going to probably end up in our traditional databases so you know the the open Source Community leads the way very often uh pine cone uh

you know and some of these born in the cloud Solutions that's but the the traditional Enterprise C uh you know technology companies like all called Microsoft IBM they very quickly look at you know what red Hat's doing what hashy corp's doing and are able to take that and make it available to the masses and I think this is when it stops becoming a a hype and a

a topic which is of interest to a few people to an emerging technology which is available to everyone I think that's the differ when when it's becomes emerging it's available it's availability so you know there was and I think that happens a lot quicker than it used to with with you know Cloud platforms whether that be Google as yours Services can be spun up really quickly and

then something can get can go from a 100 users to a thousand users to take users in a matter of weeks we see different libraries being adopted really fast uh and I guess accessibility to the code open source Community you know so many people are so generous with what they develop and make it available so you can today I can go to uh mivia website and I

can download whole tutorials to create a a rag Solution on my laptop and it's just incredible really that uh I can use open source tools like brute and pod man or my laptop to create virtual machines and run containers and all of this is available to use so whereas maybe the adoption curve was always Stranglehold by a few people that had licenses now actually anyone that's wants

to learn anyone wants to experience anyone industry in Academia uh students they can Embrace technology and learn and we can learn by doing which is the most powerful way of learning yeah so yeah so I think uh it's it's an interesting space AI uh I think it's it's it's moving to the emerging it's it's no longer fad it's no longer hype it's a real uh what I

think has been agreed is is what is the standard oh yeah we saw that I guess with uh like automation the earlier doctors maybe your Chef your puppet your salt maybe they they they created the market and then anable became the dominant player yeah and terraform become very dominant in that space as well uh so there's always one or two technologies which that gain traction and then

they snowbo get bigger and bigger and I'm not sure what will be the uh uh the major players in AI going forward but it's an interesting space to watch yeah totally yeah and which impact do you see in the in the the organization what what does it change what does it yeah have an impact on or I think organizationally uh if we think there's technology and platforms

to do the work but there's also the people yeah and the people are the hardest ones so I think what we're seeing very quickly is and we had this with like big data and analytics it was the uh it was done by the the data scientists the people that actually understood the algorithms and we're seeing that in AI uh initially and you know you had to be

a really good python developer and really good data scientist to be able to do this now I think with open source and the way it's been uh uh shared and presented you don't have to be that PhD student now to to uh do AI it's that the bit Chang I think it's become accessible like everyone can use Linux you don't have to uh know the Linux kernel

Inside Out sure you if you want to contribute to it then you do do but if you just want to consume it and uh and speak about the features and and work within that environment you know you you can be a uh you can do amazing things with bash scripting you don't have to you don't know have to write C++ and an ad and other programming language

to uh and compile the colonel to do that yeah sure yeah yeah yeah yeah and I and I agree with it too um in terms of like you know well I kind of tend to because I come from more application or software development so I look at it like we're we're looking at this whole software people just say gen but there are actually many layers to how

to make things work you have that infrastructural layer which is doesn't go away that and I think that's where I think this particular this discussion panel will uh kind of focusing on is on that layer the dev Ops how do you actually make things happen and of course there I think what is wowing people is really the top layer that's kind of the the the results of

of uh you know like jet GPT like generating an essay writing you know a Pros or something and and producing a piece of music and doing text to image all these things um kind of wowing people but what is kind of going underneath I think all of these layers actually kind of boring if you kind of think of it as compare right not as glamorous as all

of these fancy things people can do stuff but actually underneath we know there are a lot of mechanical things that needs to happen like even data that comes in you need to come in and sort them machine learning you need to do you know the pre-training stuff and that's a whole set of stuff I think the pre-training I think that's where I'm kind of interested interested in

finding out mlops right this new kind of practice of devops kind of extending into the machine learning space like ml Ops and what about the pre-training is it possible to kind of do continuous you have new data coming in and do continuous um training of your of your uh model but I I think it will be very expensive because as such it's it needs so much uh

gpus and even with gpus it takes days weeks you know to kind of produce a model so that part I'm kind of curious to see you know can can we kind of do real time kind of training but I think I I don't I think I asked the question to some executive and they just void it because it's very expensive first of all to do training and

then the other part is taking the model to do inferencing which is to apply the models to actually solve problems and that's what kind of produce all the exciting things that are that people are finding like oh chat GPD Let's uh chat with the bot and and look at all the results is completed all the chat stuff and so anyway there there are like so many layers

of stuff so people are all saying I'm working on chat GPT it can be data scientist who doesn't know how to code and there's also data engineer AI engineer who are developing the the implementing libraries for you to use and that type of stuff so I think I think it's just a whole kind of ecosystem very complex and but uh but as as far as devops I

think it has to become uh making it easy for people to deploy without them knowing all the layers of the details so yeah I think anyone that's you has a devops background uh is going to be and continue to be important in an organization yeah uh I I was at Oracle Cloud weld fortunate to be there last year and Larry Ellison one of his Keynotes said that

uh that the next generation of uh software will be generated uh the reason being is when you have humans creating code uh there's always bugs there's always security vulnerabilities and uh by having machine generated code it's going to be a lot more reliable a lot more repeatable so I think so you know there is that change on the output side uh I think what we'll see is

the need to to make something simple there's always there's lots of complexity behind it uh and this is where the automation the the ways of working that the devops principles I mean we' extended devops to be Dev SEC ops isn't we because it's not just development and operations we also need to have security there I don't think Security's embedded in AI yet I think that's something that

we need to to grasp uh the but yeah the the data pipelines we mlops I think it's very similar to what we've all been doing because ultimately we start with some data we process it we store it we retrieve it uh and then we have to automate the platforms to do that piece of work yeah yeah but this is an very interesting Direction because uh um it

it's somehow a kind of funny coincidence like operating platforms would be actually at least when you think about Cloud native platforms because they usually generated through State files they're very you always compare like how they should be and how you get there and so on that's all existing but there is not enough data to or not enough re environments where you can train on any AI at

the moment because companies don't want to share the access to it right yeah for code it's simple because you have hundreds of thousands of millions of Open Source projects where people have put in the best practice how to write software so you can train on that um a co-pilot and and make it as good as possible but operating a platform operating pipelines and then the software on

top of it that's very unique and specific per organization if you implement one approach for one company and you want to transfer it to another it might doesn't work that well yeah maybe from fixing the things around it but not from the perspective of like um uh yeah be be implemented integrated into the process of an organization I think the uh the the focus will change from

the the training which won't be done because it's very expensive won't be done very often there's only be a few large organizations that have the volume of data to be able to do this we will standardize on a number of models which will be licensed and uh we will consume but then I think it's the it's the rag uh that will will every individuals will be using

and organizations retrieval augmented generation to take the the models and extend it with your own data set uh you know for every organization uh their own corporate data is the is their competitive advantage and they won't want to give that away and share that with other organizations and then there is the models is uh then we can have these the moral dilemma of models uh you know

uh whether that be they have a social or political or you different influences on them by the people that created and the data that was used to generate in the first place uh so the bias that can be built into uh machine learning I think you know we will we haven't had these challenges before in technology uh we have we haven't had a computer saying that no

uh this is what the answer should be because we as humans we've always determined that so yeah it's it's going to be an interesting period over the next 10 years yeah totally yeah and I can definitely see the security def SEC off will be actually very important because you could you could be working with data and and if if we don't know if there are hack there

always hackers out there looking way so there there are all these data flowing you know from from one things to another or the agents right we talk about that that processed data they're flowing through the pipeline and if it's not secure then then it it it it it could be like easily be um kind of uh exploited right by people who are malicious it could be too

organizations you know if you have a model and uh it's it's designed for travel that's true and uh it it was sponsored by an airline maybe it's always going to recommend wine over rail you know it could be uh uh influences in the models we we we don't see yeah the ghost in the machine yeah that's right that's right yeah and we have the other part that

we talk about in AI is the uh the machines creating data interpreting data incorrectly hallucinations yeah which is a is a really big challenge where we we've given it a partial data set or 95% of the data set but that missing 5% means that it can come up with the wrong answer yeah sure true yeah that that's what I'm thinking too is that you know we can

have robot and doing things and generating data and all that but all that uh is it being ensured that it is encrypted for example when it travels and it sends back the information all of these things and and all of these I think as needs to be or maybe they are already organization working on that level of details I'm sure to to kind of making sure that

yeah data that's being sourced from everywhere are they secure if if you especially when they kind of flow through like I'm Al always kind of thinking of from one system to another there there always ways of kind of attackers coming in and attack and steal them or however way it can be done maybe if it's not encrypted and all these things so yeah yeah I think the

endtoend communications we we can be secure and we can be confident with where I think the and lots of governments are struggling this at the moment and there was an AI Summit last year Where Heads of States got together and they realize uh they have lost control they won't know what's inside these models they won't know how these recommendations have been been generated uh whether that be

a CIA or or MI5 or other bodies that you know they they used to been able to to know and understand data and and track it uh so I think you know maybe people that creating models are going to have to uh under license and maybe uh you know share how they've uh they've come up with uh these results I mean we I guess with the US

elections going on this year there will be lots of people saying well you know H are you been influenced spy machine that's algorithm that's right exactly yeah maybe it's a time for a good question for for the audience uh to get to know like what are your emerging Technologies um that you see most influential maybe beside AI um towards the organization and and how it transforms the

uh devops process and procedures and teams um hopefully someone will answer on that and let's see because it takes some some time what people thinking about that what what technology is your one what is the uh what you you said you spent a lot of time working in the cloud native space so uh what is the the emerging technology there that uh you think people should be

interested in or take notice of um I think there's no no very simple and easy answer because it's more like the whole evolution of the of the of the whole Tech space um I believe that we have on the one hand side a problem with the people being heavily overloaded by too many Technologies and too many things someone needs to know to implement something um speaking here

of cognitive load you know there's millions of Tools around it and if you work for a large Enterprise and you talk about two three Cloud providers different platforms and so on so the whole Sue around it is too much um on the same side you have like a demographic change um you will see that like 20% of the of the current existing Market of people working in

companies will retire within the next years and this will grow grow up to 30 40% which is insane when you think about how many people go until the until 2030 into their into their pension and have done their Duty right um while on the same time we have a very shortcoming on people um entering this space and really interested in in working on it um so there's

a lot of like a human factor around it which in my opinion will force us to reink a lot of Concepts I don't believe that running cloud or infrastructure like we did in the last 30 years is actually useful it's no one no one cares that you need to set up like still a network and you want need to set up your VPC and whatsoever it's like

why you have to do it that that's the the most stupidest simple thing why not just a platform can decide it for you right you don't need to spend time and money and effort in it and still it's like in the um when we see Cloud migration it's one of the biggest amount of time and money where an organization spends spend on is like how do I

get to the Cloud and it's like why why we need still need to discuss this right you you set up your virtual data center like yeah you have set up your physical data center yes it is faster it doesn't take three years it just takes six months but still it's too long for whatever you're going to do in some way so I believe the whole Space will

change um towards that we will see more like Federated platforms um really unified entry points for uh pushing workload somewhere um you will give the the the the parameters to it um telling what is important for you where are your uh audience located at do you consider sustainability as relevant for your workload do you are cost driven is latency topic and then the platform will just figure

out what is the best place to host it right things like that so I think overall um we It's a combination of of many of topics um I said in the beginning you have all the automation Parts um you have maybe an enhancement through AI um you have a more deeper visibility of the applications even if they're highly distributed things like that so it's a very PR

a PR field which needs all over together move somewhere else um else I see there's a really big problem to keep keep up with the with the development of of what is expected from from most corporations putting out there some products yeah I see similar challenges I think with you know infrastructur a service platform of service have provided great foundations uh databases a service and software as

a service have given us that that that experience well we don't have to worry about the infrastructure we just run and care about the application but there isn't that overall solution it doesn't get stitched together so yeah it's still a fighing experience having to set up your network and your sec in the cloud uh and uh that that loss of control which some people fear when they

uh they go all into the cloud uh I mean I I see people working more and I think what we will see is where people went maybe all in for one Cloud maybe stepping back because realized that they're using the the most appropriate Cloud for the right services and for the M application so uh it's all about date it's all about application so the uh with your

used in hosted applications you're going to be using multiple clouds so the the multic cloud the interoperability between the clouds is going to become more and more a a challenge and the security around that so I think that they're the challenges that we got to fix over the next 10 years sure so so if I may ask since I'm less involved with like infrastructural type of things

right but anyway um I'll be curious right to see if Max you're saying that all these uh you know platform becomes a service and folks don't even need to worry about it's an environment that we get and so uh how about like you know the security side right I feel like okay you know you you may say you're managing my my system my data and all that

I mean the security side is it is is it you think service providers are clearly understanding like the implications right we're managing we're a custodian of of the data that we're managing for people so are those like standardized in in terms of you know I I I need you know a service I'm I'm using a service is it pretty standard standardized between different Cloud providers or are

they pretty much you know proprietary I have my own way of managing uh things so yeah like that right yeah well I think overall the the large providers but also minor ones are usually extremely good in doing security better than the most organization do it for yourself okay when I'm when we Implement platforms you know a platform is cross cutting through all of the Technologies and you

have to integrate observability you have to integrate security you have to integrate the development uh software life cycle passes um you have to integrate cm and um most of the time the people with the shortest amount of resources are security and they usually don't have an idea about what are you actually doing there right so you need to teach them need to train them and they even

don't have time for that that might be is not in every organization like that yeah but I would say in many organization and to believe that you nowadays can operate better for example the data center than um any of the large providers I don't I really doubt it that it's possible what I see is when you have that relationship with a cloud provider it's a shared model

so it's it's your dat so most clouds will say well it's your data we don't want to see your data you know have a BL break glass approach that you know you you they shouldn't have access to your data uh but they will be they will secure the platform and the patching of the operating system and the network equipment and the firmware but the data from the

database upwards and the application it's down to you to secure the database you to secure the application so if you have application accounts which have World access you know you can have the most secure infrastructure in the world but if the application allows you to log on as a a default user account and access all the data in your Erp or CRM or payroll system that's your

uh that's your exposure so we we need to have good good security at every layer the techology true yeah very good point yeah that's right yeah and I think like um you have Technologies coming up um let's say web assemply as a around time where you solve a lot of the security p security issues which youve have for example in container runtime a classic container runtime so

um when when we talk about introducing kubernetes for example um the first concern everyone comes up is like security complexity and overhead it's like okay I I can solve two of them Security in my opinion depends on what is your requirement does it just needs to be hardened and the Network needs to be encrypted easy peasy no problem do I need to ensure that your that no

one can breaks into your container and and break out of your container well I can help you but it's also up to you what are you doing with your container because in the end it's a a very tiny virtual machine with an operating system so as long as you have an operating system you can always break something weap simply reduces this problem by you don't have any

kind of operating system you have just a pure binary format uh piece of code so using this as a runtime for um code and doesn't work for everything but for a lot of stuff um would reduce already drastically the uh open Gates the problem for potential Breakin um and I think you we will see there more and more uh of s topics coming up um when you

talk about the the host Network or networking at all ebpf is also such technology which is going way more advanced in um ensuring that not the wrong things can happen it for sure can also provide some new uh approaches but that's always the downside of it where where you create something new a new emerging technology obviously there will be also some potential future problems with it yeah

maybe they are discovered maybe they are undiscovered but I think we move in this right direction and I mean like sitting in Europe you often have discussions about Sovereign Cloud you want to build Sovereign Cloud something which is independent and secure and so on um I like the idea I have one problem with it um it's like 50 people 50 companies talking about it so what you

create is not one big solution you create isolated Solutions which all for the self doesn't work necessarily very well and they don't play well together so instead of that you put everyone into the same boat um build for example a big team of automation Experts of Security Experts whatsoever you separate slice and D it and maybe leave like a handful of people here and two three people

there for um setting these things up or building these things so I think um we we need to find the balance overall and that's maybe also one of my final statements for the transformational process overall for the market um we need to find the balance between like more cooporation more sharing knowledge and this could be also the open source path um to ensure that the single implementations

are keeping advancing and not stop where they are because then we can also just like get back our bare metal server and uh start working on this and hosting our whatever else applications we have yeah true cool yeah so well looking at the time like time goes by fast when we're having fun right discussing something kind of very interesting it looks like we have only two minutes

left or so um and uh I guess uh for me actually I need to get ready for my presentation which is like in plug your presentation what should everyone be uh dialing into now oh dialing into yeah okay so I I actually will be talking about introductory to generative Ai and then with some Vector search so I'm in the AI and Cloud track so if folks wants

to join me there um it will be starting at the next session I think the last session of the day so yeah yeah so I might join you there topic and pine cone and actually you mentioned about Ingress yeah I worked a little bit with Ingress too that was long time ago so yeah that's amazing so yeah inic and and Ingress and those are the old database

I worked with in the past so yeah okay so oral 23 AI was uh uh was announced last week and and uh been rebound 23c to 23 Ai and Vector databases are now and Vector search is part of the oral database so with the with your Java skills and your oral Java there we can do that together now so we can do that whole end to end

ready AI pipeline vocal technology yeah okay thank you so there's no there's no questions in the Q&A so if someone's got one get it in quick we've only got a couple of minutes left before we uh the channel gets shut down and we have to move on uh but it's been a really uh really entertaining uh hour with you Max Mary so thank you for I've really

enjoyed it and hope we do it again next year yeah thank you thank you thank you you very Max and yeah I hope to see you both in Europe or you come to the US that'll be fun come the yeah give us an event our turn up yeah that would be great yes all right okay thank you yeah perfect have a great afternoon see you thank you

okay bye bye