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From YouTube: Super-Charge Kubernetes App Development Workflow with IDE Extensions - Ian Talarico & Etan Shaul‎

Description

Join us for Kubernetes Forums Seoul, Sydney, Bengaluru and Delhi - learn more at kubecon.io

Don't miss KubeCon + CloudNativeCon 2020 events in Amsterdam March 30 - April 2, Shanghai July 28-30 and Boston November 17-20! Learn more at kubecon.io. The conference features presentations from developers and end users of Kubernetes, Prometheus, Envoy, and all of the other CNCF-hosted projects

Super-Charge Kubernetes App Development Workflow with IDE Extensions - Ian Talarico & Etan Shaul‎

Kubernetes is portable, extensible, and powerful - but getting started and configuration management can be painful. Deploying a simple application on Kubernetes involves multiple configuration files and tedious steps. In this session, we'll explore Visual Studio Code and IntelliJ IDE extensions to simplify the Kubernetes development workflow. In this session we will: -Create a GKE cluster from the IDE with ease. -Go from nothing to a deployed multi language, multi microservice application in minutes. -Speed up the inner loop using Skaffold to build images and continuously deploy to GKE. -Live debug applications running locally and in a remote cluster from the IDE. -Simplify and reduce needed configuration with Kustomize. -Set up and manage multiple environments.

https://sched.co/Nrli

A

Everyone can hear me all right thanks everyone for coming. This is super charger: kubernetes, developer, workflow and Visual Studio code and IntelliJ. My name is Aiden shoal I work and Google cloud I've been at Google for about three and a half years now and I'm very happy to be back here in Shanghai and.

B

My name is Ian Tallarico I'm. Also a software engineer on Google cloud. I've been working on developer tools there for about the last five years. So today we're gonna talk about cloud code. What cloud code is in an integrated set of tools that help make your kubernetes and cloud native development experience easier? So what do we do? Is we try and solve a couple different problems?

B

We try and solve problems for developers and for the DevOps side of things so who here in the audience, is a developer, show hands good a lot of developers awesome any DevOps people, one okay got a handful of them too. So we've got tools for everybody here today, so for the developers. What we try and do is we try and abstract away the complexity of kubernetes. We let you write your code as you're writing your code. In the background we can build, deploy your images.

B

However, you like to whatever cloud you like anywhere kubernetes is running. So, if you're working on Amazon as your Google Alibaba, wherever it may be its kubernetes, you can make your deployments there and we handle it. So you just worry about writing your code and you let the extensions and the tools do the rest of it. On the DevOps side we have tooling to let you understand the state of your cluster better. So we give you a nice view and the tree view will hopefully have time some time to look at that.

B

You can kind of see all your services, your deployments, your pods, and you can see the health of those and easily drill down into them and inspect logs. You can inspect events and all those things you need to understand. On top of that, we do a little bit with yeah mole to because we know who's here. His favorite thing is to write yeah mole.

B

If you got one crazy guy in the front, I know him I, don't think that's true, but it for you who don't like to lie right yeah, but we have some snippets and some templating to make that easier for you and and not as complicated so Don's gonna go ahead and talk a little bit more in depth about exactly what cloud code has to offer.

A

Okay, great thanks Ian. So most this talk is gonna, be demo, but just to set some context, I'll give you a quick I level overview of some of the features of cloud code, but before we do that, just so, we can see what everyone in the room is using. How many people here use one of the intelligent IDs like IntelliJ IDEA goal and I charm cool, and what about the S code, not half and half, and just for fun? What about something else like vim or eclipse where you max cool okay?

A

So, let's take a look at some of the features, so the kubernetes inner development loop. What is that so say, you're tasked with building a micro service or a bunch of micro services that need to run on a kubernetes cluster one of the first things you probably want to do after setting up basic things like version control and so on, it's figuring out how to actually run your application locally.

A

So you can fire up a web browser and hit the endpoint if it's a web, app testing to make sure things work properly and then going back to your code, making changes and then iterating so in other words, an inner development loop and since you, since we're running our code eventually in kubernetes cluster, it's probably pretty important that your local development environment mirror production as closely as possible. So you can catch bugs early and this means running inside of an actual cluster, and so there could be any any cluster it can be mini.

A

Cube Dhokla for desktop cluster can be on gke, as your AWS and so on and as you'll see in the demo cloud code makes it very easy to set this up so with a single click.

A

Clog code will take care of building your image for you, pushing it out to a registry, doing the Diploma deployment it'll even watch for changes in your source code and then surface them live on the cluster, with something changes without needing to switch contexts and drop off to the CLI and run dagger commands or coop coop control commands and so on.

A

Debugging so say you run into issues in your code. One thing you probably want to do is be able to set up a debugging experience, so just the standard ID debugging like setting breakpoints stepping through code running running expressions and so on, and remember, since we're now running our code inside of a container in a cooper, Neddy's cluster. If you've ever tried to do this, you know this isn't so trivial. It's a little bit messy to try to set up debugging against an actual cluster, yet to figure out how to set up the correct length.

A

The language species-specific debug configuration do the port forwarding attach the remote debugger and so on. So as you'll see in the demo cloud code will help you here again with a single click without any configuration needed you'll be able to debug your code as if the application we're running outside of a container locally except you're, running inside of a cluster with the full fidelity cluster browsing. So now that you can set up the inner development loop, the local development experience debug your code.

A

One thing you might want to do is get some insight into the state of your cluster, so looking at pods checking to see if they're, healthy, maybe stream, logs from a container and so on and cloud code will help here so without switching contexts directly in our IDE. What will enable you to do that in the form of in an ID cluster browser?

A

So since these are IDE, plugins and extensions? Obviously we provide templates and editing support things like auto-completion, quick documentation, various things to help you editing all of the ammo and we provide integrations with popular tools and libraries so, for example, scaffold which powers a lot of the local development experience and also the debugging that I talked about. It's integrated right into cloud code.

A

Scaffold also works with Helms. So if you're using Elm, everything will just work, we also have integrations with jibs. So for you Java developers out there. Jib is a Java image builder, which lets you easily containerize your java applications without needing to have a docker file, even without having to run a doctor daemon locally. If we have time, I'll show a little bit about a little bit of that and lastly, if you happen to be using Google cloud platform GCP, we also have some key integrations there. So, for example, we have in API browser lets.

A

You discover. Api is right from your ID things like the Google cloud vision API, which I'll show you a little bit in the demo later. So you can. You can discover that API add data, so added The, Associated, client library, directly to your build even do things like set up authentication right from the ID, creating service accounts and adding roles, and we also provide integration with stackdriver debugger, which is google's production. Forensic debugger gun works similarly to regular debugging, except you said snapshots which don't halt the execution of the application.

A

Okay, great I promise that most of this will be demo, so I'm gonna. Add it off to Ian now to kick off the demo. All.

B

Right thanks everyone, so hopefully you're not too sick of us talking yet I'm gonna talk a little bit more and then we'll get into the demo here so up here on the screen. Just to give you an idea where what we're building what we've built today, we have a bookshelf application, the application it sells, pretty simple. It's just a place where you can add books cover some information about the book from our architecture we see here we have a bookshelf front-end, that's our UI and a worker.

B

The worker talks to an image recognition service that Atanas written that does some fancy stuff for us and the bookshelf app talks for some storage API s and the image recognition service talks to some vision and book api's to help us out understanding what's happening. So you can see here that big gray, blob or square shape is just our representation of our kubernetes cluster, and that can be anything it can be.

B

Docker desktop, kubernetes anything mini cube, gke, AWS, Azure, whatever you want to run on it'll work with any communities cluster, so I'm gonna go ahead and jump into our demo. Real quick here we're gonna start out with vs code. I'm gonna place this mic right here.

B

Thank you. It's an so we're gonna jump here in to vs code. So here one more time who here uses BS code, nice perfect, this parts for you. So we can see here. I've got vs code up here in the left hand side here we have our cloud code view here. You can see here. I've got a cluster and Catan was talking about. We have some some browsing here so just to get started so Sam, a new user I'm new to kubernetes, I'm new to cloud code. I, don't really know what to do.

B

We have some templates and we can type cloud code and we see here a list of all the contributions we make and I'm gonna start with a new application. So a new application is just going to give me a list of applications. I can test with so there's a hello world and the bookshelf app, and you can just kind of use these as a starting point to understand to look around to see how everything works. The guestbook app is actually based.

B

Similarly, off this bookshelf app, we have here so I'm just go ahead and start out with this guestbook app, so you can take a look at it. Real quick, just gonna tell it where to put it- and this is just we have a github repository of samples and all it's doing is doing a git clone. It's pulling down all the needed configuration and setup there and it's cloning it to our machine. I think the conference Wi-Fi is taking a little bit longer than it normally should.

B

So, while we're waiting for that to come on down, show you here on the left-hand side here we can see all of our oh there. It goes real, quick. We can see the deployments and pods so stuff we already have deployed here. You can see here, I'm, not sure if you can see, there's a little green if it's viewable there. This is giving me the state of the application if it's yellow or red there's something wrong. My application, so we're gonna jump back to the the code here.

B

So this is the template we just created, so we have a dot ID ID, a folder for those who are intelligent users to help you get started, our dot BS code folder, which has our launch instructions, tasks and other configuration for debugging. We of course have kubernetes manifests. We have some source and then, as we mentioned a couple times, something called scaffold and this is kind of the engine under the covers. That's doing all of our deployments for us and we'll talk a little bit more in depth about what scaffold is later.

B

So we're gonna go back to our code here. So we have our application and I'm gonna go back here and I'm. Just gonna do a deploy, and you see here.

B

We have two different deploys when I say cloud code, deploy, there's, deploy and continues to play and deployed just does one single deployment, building your images, pushing them off and deploying them, while the continuous deploy is kind of what a ton that we're talking about at the beginning, which does a continuous deploy and it sits and it waits for changes to your code and as you're, working and saving your changes.

B

It's rebuilding your images, pushing them and deploying them, so I'm gonna go ahead and do a deploy and I'm gonna, deploy it to my development environment, which is running on gke, and we can see here right off the bat and the bottom here. We're kicking off a build and deploy I rebuilt this just before the talks that hopefully won't take too long. But while this is going, I'll go ahead. Oh just like that it was done.

B

The Wi-Fi has come back perfect, so here we see that it's we're waiting for a deployment to roll out and just like that, we have an IP address. The bottom of our screen. I can open that and now I can see my bookshelf application, so I'm gonna go ahead and start off here. I'm gonna. Add a book see that so I'm gonna use the book cloud native infrastructure. Anyone here read that book, no ok, pretty cool book written by Justin and Chris.

B

If you want to learn about some pretty crazy cloud native infrastructure, I say you should give it a read: I, don't remember when it was published. So sometime the description, it's a super cool book, let's say super cool book and all I'm gonna do now is I'm gonna upload, an image of the title or the book. So now we're gonna hit, save and just like that. Hopefully the Wi-Fi will be kind to me. There we go.

B

We have our book in our bookshelf, so me being the person that loves books, loves, kubernetes, I, think all kubernetes books, all books are pretty cool, so I'm gonna go ahead here and just to show you how this works. I'm gonna go ahead and start editing my application and I'm gonna edit.

B

The description of every book that comes in I'm gonna, say every book is a super cool book and then I'm gonna go back here and I'm also gonna add a space, so it looks right so I'm gonna hit save here and as soon as I hit save here, we can see now that our deployment is kicking off again. So without me having to do anything every time, I'm changing my files, their deployments just start. So, while this is running, I'm gonna go ahead and jump back into that scaffold file.

B

To give you an idea of what's happening. So in this scaffold file we see here we have different version and the config which is saying this is a config and ways to build and deploy. We set up profiles which is kind of gives you the notion of where I'm deploying and how I'm deploying so, for this instance I'm using a dev and a QA, and we see here our build is based.

B

It's just telling us we're building the image and we're sending it to a repository and our deploy is based on cue cuddle and of course we have our manifests here and you can see here, dev manifests, we have our QA and our QA here again we're doing the same, build, but this time we're using cloud build. So when we're doing our QA builds, we want a little more consistency. We want to be able to track how the builds are done so we're doing them on a remote, a remote build.

B

So it's consistent for autonomy and then again we have our deploy again we're using cube cuddle and our manifests again. Here we have QA, so you can see the differences here. The cloud build and the QA, but everything else is the same and we can do of course continuous deployment with our QA or our dev.

B

All right and again, this is a deploying is taking some time. The Wi-Fi is a little rough today, so I'm going to go ahead and jump back into the Explorer. So we can take a quick look here, so we have some pre deployed stuff. So you guys can see what is happening here. So, for instance, we have our deployments, we have all of our pods and our services, and we can see right now with all the green here, everything's healthy.

B

We also have the notion how we show you. Your replica sets any service accounts and secrets you may have as well as config Maps and then also for the custom resource definition. So right now. This is not it's not a lot of support here, but we're working on adding support. So you can easily browse and view custom resources in a better way than you do do now and have a more integrated view.

B

So still taking some time here. So we can go back and we can look at our deployments and some other things we can do with this is we can work with that yeah mo so from the dev ops side of things? We can go ahead and edit our yam or view our yam?

B

Oh, so what this is gonna do is it's gonna pull our server yeah Mille, and we can see here just like this is just grabbing our most recent gamal from the server, and you can see all sorts of different information here and if you want I'm, not gonna do now since we're in the middle of the ployment, but you can actually change stuff, so I could say: I want to have set of one replica.

B

I want to have two replicas and I would hit save, and it would ask me if I would like to apply this change and that would just do a cube. Pedal apply great. So it looks like our deployment is finally slower finishing up here.

B

Almost there we go alright, so our deployment is now out perfect. So we can go back to our application here. I'm gonna go back to my bookshelf. I'm gonna go ahead and add another book. Real quick same I'll add the same book again.

B

It was written, sometimes super nice book and then I will choose the same title and we'll hit save again.

B

So there we go, we have the book, it says nice book as well as the super cool book, the edition there. So we didn't have to do anything and just like that we can make changes that are automatically propagate propagated to our kubernetes cluster and deployment.

B

So a ton and I being the slightly lazy engineers that we are, we added a feature called Auto awesome and what that does is it takes away the necessity for title author date published, and we can get most of that information from the image of a book cover, so we're just gonna grab that and we click Auto awesome, use the image to get book details and I'm gonna hit, save, and so now this is doing it's calling the calling the service that Tom wrote.

B

So it's calling the image recognition service, which is making some calls out to books, API and a vision API to get this information and understand it and then sending it back. So it's taking a little bit longer, but it's actually taking even longer than I expected, so I'm think something's, probably wrong with this request. I'm gonna go ahead and stop this request and go back to the books here and we see we still have two books, so I'm gonna go ahead and go back to my divisional studio code.

B

I'm gonna go ahead and go to the debug and I'm just going to attach a debugger. So this is just your launch configuration your debugger, and now we are attached to the bugger just like that. So now, we've attach the debugger to a cluster. That's running remotely off our machine, so we're able to live debug our application without really having to do anything else. She's using a pod, selector just decide which pod just connect to so I'm gonna go ahead and just go back to my source code.

B

I'm gonna set a few breakpoints see if we hit them. I always also like to catch uncaught exceptions, because I think that's probably a safe thing to do. Something's going wrong. That might be the problem and we're gonna use. Auto-Awesome here again choose my title and I'm gonna hit save, and so now, just like that, we see we hit a breakpoint running on our kubernetes cluster, which is remote away from our machine and I'm.

B

Just gonna start moving through some of these breakpoints and just like that, I see an air pop up here, unable to read a file, and we see here on our side panel. We have an exception request to image. Rec service, it might be a little hard to read, is not found so what's happening is I was trying to make a call to 8:00 on service which doesn't exist on my my development cluster, so I think we kind of know what's wrong now.

B

We know that there's something wrong, because the service is missing, so I'm gonna go ahead and I'm going to stop debugging here, and you can see here we're waiting for changes, I'm, gonna, stop our deployment and I'm gonna make a deployment to QA, but first of all, I'm actually going to delete this line because I don't think we want that in our QA environment and I'm, going to do a single deployment to QA and that's just going to go ahead and kick off another deployment, and hopefully at on, can deploy as image recognition service to QA and everything working in the end.

B

I'm not going to show you this deployment, because it'll be kind of boring, so I'm going to go ahead and hand it off to it Tom. Thank you.

A

A

Okay looks like we're connected yep all right, so, like Ian said we're gonna build out the image. Recognition, service and I already started building the service before the demo, and it happens to be written in Java, so I'm using IntelliJ IDEA here. This is the standard. Welcome screen, like I, said before cloud code will work in all of the JetBrains IDs. So if you're working with go, you can fire this up in goal and Python and PyCharm and so on, and just to quickly show you here's the quad code plug-in installed alright.

A

So let's go ahead and open up the image recognition service and immediately here you can see a notification here prompting me to create some kubernetes run configuration so I'm gonna accept that prompt. It's full screen it okay.

A

So we have two new run configurations here, and these are analogous to the commands from vs code that Yin talked about a kubernetes deploy which is a single deployment to a cluster and continuous deploy, which does a deployment to a cluster, but will then keep the process open, watch for changes in your source code and then surface them on the cluster. Let's quickly take a look at the structure of our application, so open up the pond here.

A

So this is a Java app, like I said happen to be using spring boot and we're going to be using the cloud vision API to extract some features from the book image from the book cover.

A

We also have a scaffold diamo here, Ian kind of went into detail, so I won't talk about it too much, so the default profile here is using the web demo. We have a couple: kubernetes manifests here, one for dev, one for QA and our deferred profile here is deploying using coop control using the web dev Yano and just very quickly. Looking at the source code.

A

We have a simple controller and a service that does the feature extraction, but let's just run things and check to see how things look so I'm going to use the continuous deployment, let's open it up and edit it so, like I said this watches the dependencies of your doctor image for Changez and then it'll build and redeploy your application to the cluster automatically detects the scaffold, dynamic configuration and just to point out, you can bring any kubernetes application here in cloud code will work.

A

We even have some ability to auto generate the scaffold Yambol for you. We're gonna use the default profile and let's choose our contexts or the cluster that we want to deploy to. I'm gonna deploy to docker for desktop, and let's apply that. So now, I'm going to run this in debug mode, let's open up the event, log, okay, so scaffold, which is the tool that's running under the hood, is now building our application. Building our image, pushing it out to a container registry.

A

You can see some information here in the event log, showing you the status of the deployment you can see here, that it did some port forwarding for us, so at port forwarded port 8080, which is a default application port for spring boot. If you notice here it also port for dead port 5005, this is for debugging. So this is the standard je DWP Java debug wire protocol. It's the Java debug protocol. This is a standard port that they use, so it automatically did the port forwarding for me, since I ran this in debug mode.

A

So it looks like my application. My spring application is now running, so I can switch over to the browser and let's test it out so I have this test endpoint right here, just to kind of show you oops.

A

Just to show you what's going on that big enough yeah, so it's just a simple form where I'm gonna upload an image and we can test things out. So let's choose this book right here, kubernetes up and running I'm sure a few of you have read this. So let's select the book and upload it so now it should be calling out to the cloud vision API in the books API to extract some of the features from the book cover.

A

There we go and so I have it printing out some some of the things that it's doing behind the scenes. So we can take a look. So this is the JSON payload that it's producing, and here just so you can see some of the the annotated book with bounding boxes of some of the features that had found like the title, the author and so on. So this payload mostly looks good, so it actually completely looks good.

A

So let's go back into my code and quickly show you so, let's say I wanted to change the description and instead of showing this long description, I actually wanted to show the subtitle here like dive into kubernetes future of infrastructure.

A

Let's take a look and see how we can do that so I'm gonna set a breakpoint right here. This is where it's calling the books, API and I'm gonna upload. This book cover one more time.

A

There we go so just like that: I hit the breakpoint. This is an application running inside of a docker for desktop cluster and I'm, able to debug my code. So let's just run quickly run an expression, so volume info dot get description so yeah this. This is what we currently are displaying. But let's see, if there's a subtitle field yeah, so there's one here and yeah dive into the future of infrastructure and that's actually what I want to show.

A

Instead, so I'm gonna just make the change right now so get subtitle, and at this point I could do a redeploy go through the entire pipeline, rebuild my image and do the deployment, but I don't want to wait that long. So what I'm gonna do here now is hit command shift f9, which basically tells IntelliJ just to recompile this file.

A

So let's open up the there we go so IntelliJ detected that the class was change and it's prompting me to reload it so I'm gonna hit yes, and here you can see so the class was reloaded and basically what it did is just hop to swap the change for me. So at this point, I can go back to my application, choose the same book again and let's upload it and of course we still hit the same breakpoint. Let me remove it and there we go so now we have the updated description.

A

Didn't have to do any redeployment at this point, I'm happy with the payload I'm ready to deploy it up to the QA environment to test it end to end with the bookshelf application that Ian created so I'm gonna go ahead and kill the continuous deployment process, and at this point the only thing left to do is to point to the web QA yamo.

A

So we opened my scaffold file and it looks like I already did it here. So I have another profile here called QA. Let me just go through this manually, so you can see so I'm going to create a new profile and we want to override the deployment configuration here and I'm gonna give it the strategy. The deployment strategy in this case I want to use coop control, but it also supports helming customize, so I'm gonna, select, coop control and then I'm going to override the path to the manifest kubernetes web QA die yeah.

A

So that looks that looks good so now I'm ready to deploy it up to the QA environment, so I'm gonna, select, kubernetes, deploy. What's edited instead of the default profile, quad code detected that I have a new profile called keyway and instead of docker for desktop, I want to deploy it to coop con china, 2019 bookshelf, QA and I'll tell the logs just in case something goes wrong.

A

So let's run that deployment.

A

So now it's going to go through the entire cycle. Again, it's gonna build the image, push it out to the registry and do the deployment it should be quick since I already did this.

A

So the application was built, and now it's deploying and the deployment was complete. So at this point let's go ahead and test it and to end so here's the bookshelf application that he had showed you previously.

A

Let's go ahead and add a new book and we'll see we'll use this auto-awesome feature that Iain talked about and this time let's use the same book that Ian showed you before, and hopefully things work now so I'm gonna click Save and now it should be making a call out to the service that I just built to extract all the features for me and there we go so it extracted the title. The author and the subtitle is well patterns for scalable infrastructure and so now I'm happy with the application and everything works great.

A

Let's go back to the presentation.

A

All right recap: let's just quickly recap what we just saw. So you saw us in both IntelliJ and PS code set up this inner development loop with a single click or a single command execution. We were able to deploy an application to a cluster and have the have cloud code watch for changes to our source and then surface. The changes live on a cluster, giving you a local development experience. It feels like actually running your code locally, like a traditional development server. For example, we also showed you one-click debugging and our applications.

A

In my case, I was running my application in a docker for desktop cluster ian was running his application on gke and with the single click we were able to set up this debugging and showed you a little bit of the resource browser yep peeking into your cluster. Looking at your pods streaming logs and just to point out, this feature is coming very soon to IntelliJ as well, so stay tuned for that and lastly, we showed you a little bit about the editing support that we have so I. Didn't some of here. Ya'mo configuration.

A

Great- and that concludes our talk. Thank you very much for coming. We have a URL up here. If you'd like to try it out, we encourage you to try it out. You can visit the github page as well and post issues in future requests, and we have our email addresses up here. If you have any questions and we'll do our best to get back to you and that's it. Thank you very much for coming and.

A

We have a little bit of time for questions.

C

So my question is this: a open source project is a product right.

A

So we have issue tracking on github, but the source right now is not open. This is a new project, we're trying to make sure we get it right, but and once we're ready for community contributions, we're gonna consider opening it up, but right now we're just trying to make sure we get the experience. Yeah.

C

I, just wonder how it works in the woods architecture, behind this demo, so I don't see any architectures diagrams or how it works.

A

So how the application works.

A

B

Asking about the the plug-in, not the code, we showed here correct, right yeah, so it actually mostly relies on a project called scaffold. So under the covers, that's using scaffold to do all the builds and deployments and that's an open source project. So we actually, if you want to go ahead and check out that it's a github, slash, Google cloud platform, slash scaffold with a k sk, so that is open source and that will give you the bulk of the infrastructure. That's doing the builds and the deployments for the code.

C

But it's also a scaffold. It is just a building toast so I mean so you have a debugging server and the client DNA you communicate, communicate each other right right.

A

The debugging features a combination of infrastructure that scaffold provides and the ID so scaffold what's happening under the hood with the debugging, so I showed you debugging the java application right. So what it was doing under the hood is it was instrumenting my kubernetes manifest add an environment variable to add the JT WP configuration it didn't actually mutate, my local configuration, but it did it at deploy time. Actually so scaffold instrumented the manifest for me and.

C

A

Also, take care took care of doing the port forwarding, and so then the plug-in using events coming in from scaffold was unaware.

C

A

This transformation and and then was able to hook up a debugger into the port that it forwarded for me, ok.

C

Thank you. Thank you much very much. Yeah.

D

Hi, it looks great for the developers for them to like a deployed it automatically. How does that work with the QA team and like operation team? Could you give us a bit of background on how that works so.

B

The extension is mostly focused on like the developer experience, as well as some information for the QA team. So what's your QA team or your your DevOps team is going to do they're still going to have the traditional roles set up and and all the configuration so that that's not really going to change, but we don't necessarily provide support for helping with the roles and the lockdown and security and stuff like that. Does that answer your question.

A

All right, no more questions. Okay,.

B

Cool thanks everyone. Thank you.