Hey everyone, thank you for joining us

for our Ignite Azure Scaling Show

series. My name is Anna. I'll be your

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so much for joining.

>> Hello there everybody. Thank you for

joining us today. For anyone who is

returning in our series um and any of

our new viewers, my name is Aaron Stark

and this episode is all about migration

modernization and the role that AI plays

in there. I'm joined by two experts in

this area for today and I'll hand it

over for them to do a little intro about

themselves. Orin.

>> My [clears throat] name's Orin Thomas.

I've written way too many books. I'm

more of an infrastructure guy. I am

someone who is generally looking at the

side of people who actually have to care

and feed for workloads. that is often

the people might need to make sure that

they're backed up and running and uh

just operating in the most efficient

manner possible. Mike,

>> yeah. Uh so so glad to be here. My name

is Mike Weber. Uh I lead our product

marketing team when it comes to our app

platform and dev tools suite. Uh and a

big focus of ours is around application

modernization. uh and so excited to talk

about some of the things that we

announced at Ignite and uh some of the

market trends that we're seeing and kind

of diving deeper uh with Orurin here. So

excited to be here.

>> Absolutely. And I know I said that this

is going to be about AI's role in

migration modernization. But before we

jump into all of that, would love to

have you both kind of take us off um on

why modernization is a business priority

and what challenges customers might face

around there.

>> Yeah, sure. I'll I'll I'll jump in there

and then would love Orin's thoughts on

this as well. U so I mean we've we've

been talking about modernization for

some time now. It's it's it's it's

nothing new. Both uh we see customers

need to migrate and they need to

modernize. Uh but it's it's becoming an

even more uh imperative for our

customers to both migrate and modernize

their applications. Uh a recent study uh

that we like to share is around $85

billion uh is lost yearly in

productivity due to modernization

projects being deferred. Um, and so this

this really impacts uh our customers um

that that that are managing their

application and infrastructure budgets.

Um, this this impacts developers that we

talk to uh that they're they're they're

looking to innovate and move on to uh

the the next fun and exciting apps that

include AI and not uh be beholden to

managing their old systems. Uh and then

innovation is just happening uh so fast

as we all know. uh with AI, we now have

a lot of great opportunities in infusing

AI into uh agentic tools that allow this

to become more of a reality uh and

easier for developers and our customers

to do. Um the other thing with uh uh

with AI is that it's just becoming

imperative that C customers now move to

get their applications AI ready so that

they can take advantage of this next

wave. Um uh if we if if if applications

continue to stay legacy and and not and

not being updated to the latest

frameworks and being being able to take

advantage of the latest advancements in

cloud technology there uh we're we're

seeing that they're just continually

being uh further left behind. Um another

just just another few quick data points

I wanted to share uh and then and then I

want to uh would love to get Orin's

thoughts on this as well. Um we're

seeing that around twothirds of CIOS are

saying that they're spending new project

spend. Uh they're actually using that

budget to still maintain legacy systems.

So everyone is uh the AI craze is

pushing. Everyone knows that we need to

be taking advantage of the new

advancements in AI, but uh we're seeing

that CIOS aren't aren't able to use that

budget that's been allocated for those

uh new projects because they're still

they're still using that to maintain u

all of their legacy environment. Um and

we see that almost half about 40% of

developers time is still tied up in

maintaining uh uh legacy applications.

And so there's there's a huge

opportunity uh to free up developers to

focus on what they love to do and that's

to create new exciting uh agentic

applications and agents and let them um

not just focus their time on uh

maintaining existing systems. So uh

we've seen a huge influx just in this

past year. uh we'll talk about some of

the advancements that we have here, but

would love Orin your thoughts uh on what

you're seeing around migration and

modernization and why and why is it so

important now? I mean, we've been

talking about it for so long. Uh but why

now? Well, I'm going to take a slightly

different approach to the way that you

have and I come from operations and

operations tends to be very pragmatic

and that is that once I I had a boss

that said, I don't want to go and

replace this thing that absolutely works

unless I absolutely need to. So, they're

not necessarily thinking about all of

the financial aspects. They're going, if

you've got something that works, don't

go and mess with it. But that's actually

a key point in this whole modernization

story because even when legacy code's

been in production for decades, it can

break because of the underlying changes

in the environment in which it runs. And

people don't think about this. Now, one

of the really, really challenging things

about older code, and anybody that's a

developer knows this, is if you go back

and look at code that you personally

have written that might be five years

old, sometimes it can be a real

challenge to comprehend what you're

looking at. So, imagine going back and

looking at the code that some bloke

wrote 15 years ago or 10 years ago.

That's not you. So when you're thinking,

"Oh my gosh, I've got this code base

that's almost incomprehensible to me."

And then if there's something that goes

wrong with that, that becomes insanely

difficult to remediate. So, one of the

other reasons, let's put the financial

and the numbers aside, is that you want

to make sure that if something that your

business relies on breaks, you can get

in there and fix it without becoming an

an insane problem. And I've got two

props that are about this and I

absolutely recommend people read it.

There's a book here called Over

Complicated by a bloke named Samuel

Arbersman and there's another one called

Kill It With Fire by Marian Balotti. And

both of these are about the challenges

that organizations have with legacy code

and legacy systems. But over complicated

really deals with this idea that our

code bases and our existing systems have

become so insanely complicated that

they're beyond human comprehension,

which is why AI tools actually become

useful. Because one of the things an AI

has is an AI almost has an infinite com

uh uh [clears throat] infinite

concentration span. So when we're

talking about AI tools and one of the

things that we'll go through in terms of

the application modernization and also

just understanding your existing

ecosystem is that you can go and use

these tools to comprehend something in a

way that might take you if you were

doing it in a rigorous manner personally

many weeks or many months to come to

terms with. So one of the other elements

of looking at the new tools that we've

released is that they solve a problem of

comprehensibility. That is they allow

you to comprehend

the codebase in some cases when you're

looking at the GitHub code pilot app

modernization story which we'll get to

in a moment but also just the

dependencies and the entire ecosystem of

what you've got. There's a a point that

Arlesman makes in this book and he talks

about the IRS codebase and all of the

applications that exist in the IRS and

how there's constant uh attempts to

upgrade some of the older systems and

that simply because no one fully

understands the functionality of this

insanely complicated system, every time

they try and upgrade it, they find that

they miss bits of functionality that

still remain necessary. So they get into

this situation where they've introduced

new applications that have new features

and functionality that they need to do

their job, but they don't take the whole

cart across and there ends up being

these weird edge cases that they need to

keep the old stuff around for. So

another point in sort of this whole

story is how do you even comprehend

what's going on with your codebase? How

can you shift the paradigm of your

codebase so that it becomes maintainable

in future? How do you get it off that

insane morass where someone looks at it

and goes, I kind of understand what's

going on here, but I wouldn't know where

to start and I'm very reluctant to start

pulling off cogs and playing with gears

because it might actually cause many

more problems. And how do you move your

code base to the point where it's easier

to maintain?

>> Got it. I mean, that sounds like a

really connected issue to what Mike was

talking about, especially around that

one piece he had mentioned. Um, about

40% of developers that spend their time

in trying to maintain all these code

bases. uh which really interesting point

because I would love to hear from both

of you maybe Mike uh to start but what

would you feel like Microsoft's um agent

approach to modernization is given a lot

of the points that already made and some

of the data that you shared previously.

>> Yeah. Yeah, for sure. So we made we made

some exciting announcements at Ignite.

We made a few uh all the way back to

last spring which feels like years ago

but it last Microsoft build where uh we

we had some private preview features in

GitHub copilot. We we call it app

modernization and GitHub copilot. And so

we use GitHub copilot as as our hero

offering here when it comes to

modernization projects. And so what we

announced uh last spring at build was

like allow or it allows customers to

quickly perform uh end toend code

assessments. We ended up gaing this

actually in September and then we had

some new stuff that came out here in u

just just a few weeks ago at ignite uh

with these AI agents. So we've taken an

agentic approach where within within

GitHub copilot you can use these AI

agents to upgrade both Java and .NET

versions. Uh this this allows you to

make sure that your your apps are cloud

and AI ready. Um and then what we just

announced uh at Ignite expanded this to

where now we have endtoend uh portfolio

assessment with Azure Migrate Doctor

Migrate and Cast. That's in that's in

public preview. We expanded the

framework upgrades. So now now uh what's

available is uh .NET framework to the

latest.NET net all the way up to Java

version 25. Um, and then you can now uh

do uh Jakarti transformation and

integration with Intelligj. And then for

containerization, we have a

containerization assistant uh to help

autogenerate Docker files. And then we

announced a new offering around a manage

instance on Azure App Service that

allows you to accelerate uh to path

migration with just minimal uh

configuration and code changes. And so

we're really excited about this. We have

some other announcements around uh Azure

Copilot uh where we have additional

agents there. I'll let I'll let Orin

talk about that. But maybe before we

jump into that, we do have a short video

um that highlights some of these new

features there. This is actual product

that we're showing. It's just sped up um

so that we don't go through a 15 or 20

minute demo. But uh if we could maybe

run that video and then we can talk a

little bit about Azure Copilot.

>> Sounds good.

Slowly but surely.

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>> Hey,

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hey hey.

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>> [music]

>> I pull up again.

[music]

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Hey [music]

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hey, hey. [music]

Heat.

[music]

Heat. [music]

>> [music]

>> So, there was a lot to understand on

what was going on in that video. Um, but

if you wanted to break it down, the

GitHub copilot app modernization, what

it'll do is it'll go and analyze the

current state of your project and

generate you a set of modernization

plan. It'll go in and using artificial

intelligence, it'll look at what you've

got and it'll figure out what the

dependencies are. It'll figure out what

your outdated libraries are. It'll also

figure out what your potential migration

issues are and give you a set of

strategies. What it'll also do is it'll

assist with code transformation. It will

suggest API replacements, dependency

updates. It'll also go and use the

existing knowledge that Microsoft and

partners have figured out by doing this

in the past. So, one of the great things

about AI is it sort of has a corpus of

knowledge about everywhere where

everybody stubbed their toe on problems

in the past and how they've sort of got

past that and uh are able to resolve

that. So, the system learns from

existing changes and applies fixes. Um

it also includes build validation. It

will also uh create production

pipelines. It will also do security

vulnerability management which would

will scan your codebase and your

dependencies for CVEes automatically

applying security fixes. So there's a

lot there to look at in that video and

you have to watch it a few times to

understand what's going on. But the

documentation actually goes through in

good detail all of the bits and pieces

that this this set of new tooling will

provide for you.

>> I appreciate that.

>> Yeah. Yeah. And just and just to add

that there or thanks thanks for diving

into that detail. Like we show we showed

this video in a few different sessions

at Ignite and and uh in two of the

sessions uh people did come up

afterwards and asked uh you know how

does the tool actually work? like that's

great kind of vaporware that you were

showing up there and we had to we had to

reiterate to them like no that that is

the actual tool uh we just sped it up

you know so it wasn't a 15inute video so

that's something you can go access now

you can take advantage of that you can

use it in VS Code uh using GitHub

copilot so that's actual real product

and you can go uh play around with it so

it's it's live

>> and it's not a big press a big red

button and it goes off and does it for

you all of the checks and balances so

it's not going to be like, "Oh, I've

done that." And then it's sort of like

a, you know, an Uber Eats delivery where

you've got no control over it after

that. You can go in and you can pause,

you can review, you can think about it.

What it is is that this isn't a tool to

extend your capabilities. And this is

what AI is really great at. If you've

everybody sort of sat there and used AI

to go and write themselves something,

but what AI is really good at is if

you've written something yourself, and

take this from someone who writes a lot

of books, you can go and get it to

techedit. you can go and get it to

review it. You can go and get it to make

suggestions. So when you've got an

existing thing, that's where AI is

really, really, really, really useful

because it's saying, "Oh, you've got

this existing code base. I know how to

go and upgrade this code because I

understand I can see the entire context.

I'm not generating code from whole

cloth. I'm actually understanding your

existing intent by what your codebase

does and where you want to go with it."

>> Yeah. Yeah. And sorry and sorry just one

more thing to add on to that. Uh I love

I love that point Orin that you're

making there. Uh so we have a concept

here that we call Agentic DevOps. Um we

view it as the next evolution uh of of

DevOps for developers. And so app

modernization is a piece of that. Uh the

point I wanted to make that Orin was

stressing there was uh our our our point

of view is that developers stay at the

center of this. We have other agents uh

within GitHub copilot that developers

can leverage in their in their everyday

tasks. Um but it is the developers at

the center where they are there making

like you are there making the decisions.

You are there validating things as they

come through. It's not just going to go

off and run and modernize your

application and then you still don't

have what's uh you still don't have an

idea of what's going on. So uh our view

is that developer stays at the center.

We have multiple agents and we'll

continue to develop new agents for

developers to take advantage of. Uh and

this is just one of of an offering

within Agentic DevOps where we focus on

the app modernization piece. And we've

got a question in the chat there about

does it do databases. And if I remember

correctly, not only will it modernize

Postgress and SQL, it'll also do um mig

database migration. So I think one of

the demos I saw at Ignite, but don't

quote me on it was moving Oracle to

Postgress.

>> Yes. Yes. Yeah. Yeah. And sorry, I had I

had forgotten to mention that before

that video ran. So we did we did have

some announcements uh around database uh

modernization and migration uh because

uh an app doesn't operate without

without a a modern database and so we

did we did unveil uh the next generation

of Azure Azure SQL manage instance and

so that's now generally available it

doubles the storage it's five times the

performance for mission critical

workloads and then we also have it for

postgress SQL which added elastic

cluster clusters it uh launched AI

powered tools to accelerate that Oracle

to postgress SQL migrations And it's all

integrated in GitHub copilot. And so in

that video there was one little snippet

on that but u yeah I hadn't called that

out before we showed that. So yes

databases is now covered as well.

>> Anything else that we want to add on

databases for atmod gap co-pilot?

>> Uh not from me. No. Um look there's a

obviously as uh Mike said that there's a

many many many many applications have

that data layer which and so one of the

things and when we get more into talking

about the Azure migrate tool it's about

understanding the dependencies and the

relationships between different

workloads and then you can understand

how all of that works.

>> Awesome. And it looks like

some of the other questions were

answered in chat, but there was one from

Steve Wolf 3214 just about if these

tools can all run locally on a local

codebase or is it only um pertaining to

GitHub.

>> So they can run that from my

understanding they can run that in the

in the CLI using GitHub co or using

GitHub copilot. So wherever you can run

GitHub copilot you can access these

capabilities.

>> Yeah. So you don't have to have a a

public repo or a private repo. You can

basically run it against and I believe

you can also use it with other tools.

You're not just limited to VS Code.

>> And there's another question from Husam

Hal. Apologies if I mispronounced that,

but what's the best tool to use ADMS

with or VS Code or SQL management

studio?

Um, I don't think it plugs into SQL

Server Management Studio at this point

in time. Um, I know that it uh we at

Ignite they were talking about I think

they were talking about Jet Brains, but

don't quote me on that, but I know it

was certainly in Visual Studio and VS

Code and a few other uh editors.

>> Awesome. Um, okay. Without any other

questions for now, we can continue here.

But given we're talking about a bunch of

these different tools, all the new tools

that you went over, Mike, that has come

out recently and some things that are

just ging um as well. Uh what is kind of

the overall thinking around the new

tools that are in market, but any early

successes that we've seen with customers

so far based off all the new things that

have launched?

So one of the things things that we

haven't covered so far is probably

talking about the Azure migrate tool and

how so one stock we've talked about how

do you deal with your codebase but we've

already got a tool that's called uh as

you migrate and we've added a whole lot

of functionality to that agentic

functionality to that to make that

process of assessing your workloads and

then moving them a whole lot better. So,

uh, one of the new things that we

announced at Ignite was essentially

Azure Migrate Collector. And the idea

behind Azure Migrate Collector is it's a

discovery tool that you don't need

outbound connectivity, but what it's

going to do is it's going to actually go

in and autonomously go and look at your

workloads and figure out all of the

dependencies and what is there. And what

it really does is it's often extremely

difficult to identify what the

dependencies are for a particular

workload. We sort of sit there sometimes

and we go, well, we've got it in a VM.

It must be fine. It must only exist in

the VM, but if you really understand it,

well, the VM's got a whole lot of

dependencies. Not only is it dependent

on DNS because everything's dependent on

DNS, but you will have a whole lot of

maybe there's authentication, there's

that there's different data elements, it

may be talking to something else, it's

running a function over here, it's

running something else over here. So in

the past, dependency analysis generally

only provided you visibility at a single

server. With this new tool, you're able

to visualize network dependencies across

servers. So what it's doing is analyzing

network traffic. It's analyzing the

applications. It's going in and looking

at your ecosystem so that you're able to

then understand what's going in going on

in your environment. It also um looks

you can plug it into as your uh into

GitHub copilot. So it'll go and look at

code if you've got code but often a lot

of organizations especially when they're

looking at stuff and they just want to

do the migration aspect they might not

actually have the code for their

application but they want to move that

application from onrem to Azure. It

might be uh you know an application

that's sitting on IAS. it might be or or

some other form of application. They

want to move it to Azure but they don't

know the best way to go and do that and

it's not like they can go and refactor

the code at this particular point in

time. The other thing that these

migration tools can now do is that they

can look at the way that your

application functions within its

ecosystem and go and plan an Azure

landing zone and configure an Azure

landing zone when you're going to

perform that migration. An Azure landing

zone is a way of applying Azure best

practices to your migration. So instead

of just sort of picking it up and

throwing it into the cloud and going

we're great, what it's actually going to

do is it's going to make sure that

you've got all the right policy, the

right configuration, the right security,

the right network infrastructure for

your environment. And what it'll do is

it'll go and generate the necessary code

and templates to go and apply that for

you prior to you performing your

migration. Something else that the new

agentic functionality in Azure Migrate

does is wave planning. That's where it

provides a structured approach to you to

your cloud migration and modernization.

It'll essentially break it down and

allow you to prioritize and go right

well this dependency probably needs to

be moved first. Once we've got this

dependency, we're going to move on to

this dependency. So, it's about making

sure that you know if you go and build a

complex Lego model like some of the ones

you see behind me, um you've got to do

it in a particular way. You can't just

go, well, you know what I'd really like

to work on is this part of the model.

And that part of the model might be at

page 50 where you really need to start

at page one. So, it gives you much

better planning, sequencing, and

prioritization and also gives you a

whole lot of automation where automation

can be actually done. So to come back to

um Aaron's question about uh some of the

um great examples of this, my favorite

one is Xbox because Xbox we obviously

run an insanely large service at

Microsoft for Xbox Live and the Xbox

team used GitHub C-Pilot to upgrade and

test multiple projects for the Xbox

present services and was able to migrate

it from .NET 6 to Net 8 by automatically

generating an upgrade plan for that

accounted for all dependencies, applying

changes through a guided step-by-step

commit process. The team accelerated the

workflow and was able to achieve this

migration four times faster than they

would if they'd been doing it using

older techniques.

>> Yeah. So we're definitely taking

advantage of the tools here and a lot of

it is are uh some of the new use cases

that we're building is from our own

teams and the work that they need to do

uh in in uh modernizing our own

applications is our capabilities that

we're making available uh to customers.

Uh maybe maybe two other customers that

I'd love to talk about. Uh one is the

Ford subsidiary in China where they

focus on using GitHub copilot uh to

automate that middleware of code

migration tasks. uh this resulted they

saw up to about 70% reduction in the

software migration effort that helped

them just accelerate timelines uh and it

reduced the manual toil of actually

going in there uh and doing that work.

Um and then another new kind of fun

innovative company called Net View.

NetView uh builds these uh GPT enabled

smart bird feeders. Uh so very niche

product there. Um but they were able to

as they were migrating uh onto Azure

they leveraged these new capabilities

and they were able to reduce about 67%

of reduction in the manual effort to do

that and for them this helped free up

their engineers to focus on those new

advanced AI features. So uh as you can

imagine having a GP enabled smart bird

feeder there's a lot of fun and new

opportunities that they could build into

that product. uh and by them leveraging

these capabilities that allowed those

same engineers to not focus on the

manual toil uh of modernizing onto Azure

or migrating onto Azure. It allowed them

to, you know, focus on cool new features

that they could build into that product.

So, uh so those are two that we're

seeing. We have a bunch of other

customers that are taking advantage of

these new capabilities as well as other

teams internally at Microsoft that are

using them. One of the really cool

things about a lot of these tools is

that for most organizations, they're not

specialists in modernization or

migration. So what you're getting by

having access to these tools is sort of

the collected wisdom that's been built

into and trained into the AI and that

you can get that. So instead of, you

know, going and engaging a consulting

firm that might have done this a

thousand times, you're getting a sanity

check from an AI that, you know, won't

certainly be less expensive than the

consulting firm, but what it's giving

you is it's giving you a source of

advice. One of the things that you

always learn more of is having a

dialogue with the AI. You can go and ask

it questions. Oh, okay. So, what happens

if I did this? What happens if we do

that? So all of this is built on the

ability for you to get better access to

information instead of sitting there in

front of a search engine trying to

figure out okay what do I do or when you

run into a problem how do I debug this

particular you know roadblock that I've

hit you can go and use the AI tools to

try and figure out your way forward with

your migration of these workloads

because migration's really complex if it

was easy you would have already gone and

done

Yeah. Yeah, for sure. And just and just

and just just one thing to add on there

too. I mean like hopefully uh people

have been able to see that are watching

this now or watching the uh in the

future on demand is that uh at Microsoft

we're a we're a strong advocate believer

in the importance of migration and

modernization. We've we've done the work

to bring these tools together as Orin

was talking about with Azure Migrate. We

have Azure Copilot that has these new uh

agents that help uh uh do assessments

and then help push that over into GitHub

copilot to where then developers can

pick that up from the IT teams and they

can understand which apps need to be or

which apps are ready to be modernized.

Then they can go and do that work with

GitHub copilot. really that combination

of Azure uh Azure Copilot with GitHub

copilot uh makes this a real reality for

our customers now that uh as the video

said earlier what used to take months or

even years now you know can take a few

weeks uh in order to get your

applications uh ready for AI.

Super exciting stuff and I know I think

we had a poll going around what our

viewers are most excited about um in the

app modernization space specifically

with GitHub Copilot and v Visual Studio

for 2026 and the resounding answers seem

to be less manual effort and more

innovation. But would love to hear from

you too. Uh yeah, what are what are you

both most excited about as it relates to

app modernization with GitHub co-pilot

looking in the future for our

partnership with GitHub as well as for

Microsoft um Azure platform.

>> Yeah. Uh so I'll go first really quick

or I have a short one there. What I'm

excited to see what is [clears throat]

what is what customers are going to do

with this. So like I love I love the Net

View example where they're they're

they're creating really fun and engaging

new experiences for their customers uh

by taking advantage of these of of this

tooling. So I think in the in the era of

AI, we're we're at the cusp of that

where there's some really cool things

that have happened as far as new

experiences and new applications that

customers are developing and I think

this is just going to speed that up even

more for our customers. So I'm excited

to see what what the next gen of apps

that customers are going to build uh

taking advantage of these capabilities.

And just to hit one of the questions

that came up in the chat, yes, these

tools do include building unit tests and

functional tests for the migration. So

it's not like cowabbanger. What it

actually is is it's go you can go and

provide your whole tests and what it'll

do is it'll also create separate branch

on your repo so that you can go and do

all of this mcking around against that

instead of just you know deploying to

production because deploying to

production always works so well all the

time. Now you can go and do it in your

test environment and use it in your test

environment and figure out if it

actually works. But what I'm excited

about to come back to Aaron's question

is that the challenge with all of this

as you know uh Arbersman points out it's

the complexity of these systems right

we're dealing with systems that are

increasingly becoming hyper complex.

There's a there's an old story about

Steve Wnjak when they were building the

Apple computers and Steve Wnjak knew the

entire codebase of the operating system

and that's basically you know late 70s

early 80s. You spin forward to today and

you would need several thousand people

in the room to understand the codebase

of an operating system for your desktop

computer. We have ex as things get more

and more complicated, we don't know how

they fail and we don't know how they

interact. And luckily for us, we now

have these uh the these tools that have

almost an insane amount of

concentration, right? They can't get

distracted because something someone

posted something funny on Instagram.

What they can do is that they can focus

and that you can go and talk to them and

then you can ask questions and then you

can follow up so that you really

understand what's going on because

everybody in it knows that sometimes

you're sitting there going, "I'm

desperate. I've hit a blocker and I

don't know what to do." And maybe you're

sitting there trying to search through

forums to find the answer to whatever

your blocker is. and you're getting to

the stage of being perhaps a bit

religious because you're praying that

whatever you're going to try might

actually work. But with these tools,

you've actually got a better way of

understanding how to resolve blockers,

how to understand issues, and understand

what the trade-offs around the

workarounds are.

>> Well said. Um, if there's no other

questions for any of our viewers,

continue to feel free to drop those. um

would love to hear a little bit more um

on just maybe how our viewers, how

customers, developers, anyone who might

be new to this and or experienced can

learn more and get more involved around

Microsoft agentic migration and

modernization.

>> Yeah. So, we have a couple uh aka links

that we'll either put in the chat here

or they'll pop up here. So, we have some

great resources uh when it comes to just

learning more and actually accessing

these tools. So, we can we can pop those

up there. We also have a blog that we uh

uh published out uh around Ignite that

that highlighted everything that was

available uh when it came uh leading

into Ignite and then everything that we

announced uh at Ignite around this. So

that blog's a good read uh to understand

all the different capabilities that are

there and then there's uh two different

links that we can put in there around

going and getting access directly to

these tools and be able to use those.

>> And if you want to review the Ignite

sessions, they're still up on the Ignite

session website. They're in video

format. The ones that you want are

BRK103

and you also want BRK uh 139. And not

only is the video there, but there is

also all of the slides that are involved

in those sessions that you can download

for free without even having to

register.

>> Yeah, I would I would just add one more

in there. BRK 100 also uh has some great

customer examples in there as well. We

had some customers on stage. So yeah,

plenty of content. We had about six

sessions I think in total or seven uh

around this topic at uh at Ignite, but

those are those are three of our

favorites there or I guess not to say

favorites, but those are great to check

out. And just know there's even more

that you can check out there as well.

>> And if you're not liking to wanting to

go through it to speed on the video,

there are transcripts available as well

that you can just read through.

>> Awesome. Well, thank you both. Um

couldn't have said it better myself.

There are a plethora of resources that

you guys can engage with the blog, a lot

of our on demand content that's coming

back from Ignite. Um, but yeah, just

want to do a very big thank you to both

of our experts for joining us today.

Thank you to the viewers who watched

this episode. If you're part of this

series, I'll see you in our next

episode. Um, and thank you for the team

behind this that makes all this

possible. So, appreciate it and until

next time. Bye, guys.

All right.

Thank you all for joining and thanks

again to our speakers.

This session is part of a series. To

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