 Hello everyone, welcome to this session. And I am Chuan Yichen from Huawei. And today's session, I will introduce a platform for MEC, which is Edge Gallery, a developer-oriented open MEC platform. And today I will first introduce what it is for Edge Gallery and then I will introduce, have a brief introduce for what is the developer-oriented open MEC platform, the details for Edge Gallery. And then I will have a demo on Edge Gallery, which shows how an application vendor can develop one application based on Edge Gallery and use Edge Gallery to deploy the application to the Edge. So here, as we know, 5G will release the power of industry applications. So the industry applications in future, we are more and more running on MEC. So for this scenario, how to do the service governance, how to do the traffic off-loading, and also the capability openness. So we need a unified application management platform to deal with the connection and the management and the application cooperation with the MEP platform. Also, care code will need a MEC open source platform to let covers the whole ecosystem, which includes the developers. So how we support the developers? In future, the developers will develop applications on the Edge. So how we support that? How developer can develop their applications very easily? And also in future, how to support market place for the Edge application, it is also should be considered. And for the operator themselves, how to manage the Edge applications in real runtime systems. So it is also very important. So one platform which covers the developers and also the market places and also covers the management for the operators. It is monetary for the MEC. Here, it is a brief introduction for Edge Gary, which is trying to build a telco-lead Edge platform and ecosystem. Our mission is to create one MEC open architecture and the standard. And then we are trying to build one to be ecosystem. We are simplified development. So you can see here in the right side, we will have four parts mostly important components. One is MEP. Well, for MEP, it will unify the service management and also the network capabilities and also the open APIs and MEP management APIs. So it is really important in future in the MEC system. And the second one, it is MECM and the administrator who unified the application lifecycle management to set up a unified platform for the operator. And the third one, it is the App Store, which is Unified Applications Hub Store. Our applications in future for MEC will be published in this App Store. And the fourth one is the developer portal. So this is for the application developer. For this developer platform, Edge Gallery is trying to build up a very simple development platform for Edge application. There will be multiple of plugins and also test tools will be supported in this platform to support developer to develop a new Edge application. Okay. And the second one is about the developer-oriented open MEC platform. So here it is the overview of Edge Gallery. We have four components, which is MEP and also MECM and also App Store and also developer platform. So for MEP, there is no UI layer in MEP component. Here is three UIs for the Edge Gallery platform. The first one is developer GUI. And the second one is for the App Store GUI, which is the centralized APP Store for Edge applications. And the third one, it is the management portal for Edge for the MEC system, which will be called by operator or some service provider of MEC system. Okay. And while we say Edge Gallery, it is developer-oriented open MEC. Here you can see we have one flow for the application vendor to migrate to layer or develop a new application to MEC system. So we will support the application developer from developer preparation and also on the coding and the developer and the test phase and also about the application published phase. So the first one, when we supported the application development, we will support a platform selection, which is X86 or such as ARM platform. And also we have MEP capabilities selection, such as traffic capability or some RAN network capabilities, such as location capabilities, which application depends on. And also we have tools installation and sample codes for these capabilities and all application to call these applications, all these capabilities. And the second one is one, during the user developer and test the application, we will have plugins, we will have the API simulators, platforms to support application vendors to develop their applications. And during the application test, we also have a sandbox, some tools to support such as to do remote debug. And we have a sandbox, which already deployed the dependent capabilities layer. So that they can very easily to test their applications. And during the application publish, they also have, we also support applications. They can publish their own services to other applications. So that other application consume the vendor's application. So here they also have a platform to verify the application and to package the application and then publish to the app store. Here, the app store can be or actually that is an app store layer, which means all the applications already published to this app store is already verified by the platform. It can be directly deployed by the MECM. So here app store also can be some commercial app store in future. And then the last one is about the MECM. The MECM is the management system for the edge application lifecycle management. They will manage all the resources of the system and all the packages of the system and they can also do application orchestration in the system. Okay, and in the following time, I will have a very demo for to show how to develop and deploy an application based on edge gallery as we know, we have applications develop a platform to support developer application vendor to develop one application. Here, this demo and we name it as positioning service. As you can see here, in this demo, we will show how edge gallery developer platform supports the new application developing. And in this demo, we can see the left side here, we have a face recognition service which is already deployed in the MEP platform. This application depends on and the application we're trying to develop here, it is we name it positioning service, which is once in this positioning service. Okay, let me introduce what's the capability of face recognition. Face recognition, this service, there is capabilities is that you can pass one image, maybe one photo of one person, they pass this to this service and also you can pass him a video or a camera or RTSP flow. And the face recognition service, it can return the result of recognition to find out if this person exists in this video. So this is the basically the platform capability and in this positioning service, which is in the middle part, we try to develop one application. This can be consumed as one monitor system. The monitor system, there is many cameras located at different places. And in this monitor system, we want to support one feature is that you can pass one image of one person and then in this system, we'll try to find out if this person has ever showed in any camera. So in this feature, the monitoring, the positioning service, it will depends on the face recognition. It will use the capability of face recognition service to find out if the person exists or ever showed in this camera. So, and also it itself will calculate, find out where this person and when this person ever exists in this, in which camera. And also this is about the feature of this positioning service and to show the capabilities for expose the APIs of this positioning service. As we know for our application platform, we also support the application vendor to expose their capabilities to be consumed by other service who develop a new system, new application can consume the positioning service. So it will also expose one APIs is that for user, you can pass me one image, one image of person and this positioning service will responsibly if this person ever it shows in the monitoring system. So this is the brief introduction for this application. And in this demo, I will try to develop this application to show how edge gallery support to develop this positioning service and support to manage it, to deploy this positioning service to the real MEC system. And now I will go into the real system. And you can see here, okay, I will change it to English. And here there is edge gallery developer platform. We already have this platform here. This platform is used to support edge application developers to develop their applications or they can use this platform to directly deploy or verify or patch their existing applications to MEC system. Okay. And now here the flow is you will find we will first create one project. Sorry, I need to login the system. And then the first step for user to develop one platform is to create one project. So I will name it as positioning service. And also here I will upload the one icon for it. Okay. I will change it to English for a user to easily understand positioning service. And also here can also feel some descriptions for the application. It can be detailed description. But here I will have a quick brief introduction. And also we can have, you can see here the version and the industry and the type that I've captured some brief informations for this application you want to develop. And the second step is to choose the abilities you want to use of the platform. As we know our positioning service will depends on face recognition service. So here you will find that we have two first type one is the edge gary capabilities. And the second is edge gary eco abilities. There is no difference for usage. Only difference is that the edge gary capabilities is pre-deployed in the platform. So it is not provided by some third party applications. And the edge gary ecosystem capabilities that means user who contribute to the services to the platform. And they also can expose their capabilities to be consumed by other services or just for difference. So here I will select the face recognition service. And here you see also for the face recognition we also we have two version. And in my example, in my demo I use this face recognition service but not class. And okay. And until now we have just a create one project for user to manage their pet project. So after created that is by default you will show the details of this project. And you will find in the left side we have APIs we have for beard and test we have for other static tools and here. And for the API as we know user want to consume face recognition service they need to know how to use this application. So you will find here for face recognition service you can also hear face recognition service is published as HTTPS. And you can in this platform you also can try it out for you to know how to use this application. How to use this API. And you will find here you can excuse this API and also in the result it will returns you the JSON format you can find here I just upload one image and the result is will returns you a JSON format to dream which contains the face number and also the result. And based on these application developers they can very easily to know how can I can use these APIs. Okay. And after application developers they know how to develop this and then we will start to try to coding and they will manage this positioning service project and you can find here in our systems we also have for plugins and the API introductions. The APIs in this project user can very easily to find it out. And also here we have for plugins here you will find that we have, we already have Python plugins and Java plugins but at least it's an open source platform. So this is a plugin repositories and the user can also contribute to their application plugins here and in future we will also support more and more plugins. And here when I develop one develop this face recognition demo and I will use this Python plugin and okay and the next step for user is they trying to develop their applications. So here I already showed this demo because we have no time to show how to develop this. This is the developer for the application and in this application it will, you will find in their codes they will depends on the face recognition MEP capabilities they will send a request to the face recognition service to get the image recognized result. And also here I mentioned we have plugins for the ideas you will find I have already add one plugin here for MEC you will find here and you can also select the details of depend the capabilities that you depends on. So here it is very easy for user to use to know how we need to, how we can use the face recognition service. And also here once you plug in here, okay and here there is one limitation here we need to refresh it, you will find in here there is a two new folder will be generated and these two new folder it is letter for this APP example it shows for user for Python language how you call this API you will find here it is also the face recognition API for Python language how you call these APIs. So it is very easily will be very easily for user to know in Python language how I can use this language use this capabilities. And also there is one more folder it is for the package application package generated example. So in this example there will be very easy for user to know how we package this application. Here you will find this application the scripter template here and the user can easily to know how we package it and okay and here we assume user have already finished this coding work in this application they will calling the capabilities of MEP of face recognition and then after this you will find in for the application itself there is a file here like which can build the application as an image. And then I will go to one VM and which also have these applications there and I will also show how we build it here by this command we will deploy we will build this application as one image as one Docker image. And then once we finish this stock image we also need to Docker save to save it as positioning service to get one package of this application. So it will take a few seconds and here I have already save it as a package file. So once user or application developer they get this file this application package they can go back to the edge gallery platform and they go back to this positioning service now they need to test their applications and then they need to upload their packages here. Here by this upload package this is for user to test and package their applications. So by upload their image they can this image can be deployed to a sandbox for user to test it. But here I need to mention is lack of for upload it will take a few minutes because this Docker image is a bit large. So I will use this I will directly specify the image name because I have already uploaded before because for user they test the application will takes several times. So it is not only one time operation. So once the image is already uploaded and if the image is not changed they can directly test it again. So they directly specify the image name which have already uploaded and they can also upload some deploy files and also here it is for the APIs. As we know our positioning service we have exposed the capabilities for other application to consume. So here it is to assign the APIs of the service itself and also here it is to assign what's the part and the service information that they exposed. Well, we name it as positioning service this will be showed in the for the edge gallery echo capabilities there. So here it is the sandbox list and as you know here in future it will automatically allocated one sandbox but currently it is manually selected I will deploy it to a sandbox sorry, okay. And the list sandbox it is also directly this one I will show to you here. Okay, you will find that there is one positioning service which is launched at 80 seconds before and also you will find here for this service it is already deployed and it is already exposed this post and port and the user can directly test their applications as I need to say here is later because in the real system we use camera but today to be easy to show I use a video it is the same if it's both RKSP videos here. So all this it can be showed currently I have not set any image so it will always show unknown here now I will upload one image of this person and you will find, you will find here Zhang Hailong here at this camera position one it is fine in this camera. So this feature can be exposed to other for other applications to consume it, okay. And this means this application has already tested and we can finish test and once we finish test this sandbox will be released and here you will have they can choose to publish the application to App Store and they can also publish their API capabilities to echo system here we both selected as true and here we will find in APIs MEP echo API's latest positioning service here and I will show here once if another application is created you will find that is echo capabilities which is the veto application and the next step you will find that is positioning service which exposed by our positioning application here can be find in the echo edge Gary echo capabilities which user can develop based on this new API's, okay. This is a brief introduction for our edge Gary developer platform and then let's go to the app store as soon as we know last we have selected to publish our positioning service to App Store so you will find here there is one positioning service it is new here in our app store okay I will change to English and you will find the time is okay it is just now we past published it in App Store so this positioning service already published in as a verified application that published in this app store and then I will have a quick introducing for our MECM system this MECM system it is a real running system which for service providers can manage the application lifecycle management so I have already here you will find I have already uploaded this package in our MECM management system and this is a real system they have capabilities to manage the edge nodes the resources and the packages and the application lifecycle management so here I will show how to deploy this positioning service to the real system so we have to get the positioning service package here and we will distribute this package to one edge node here edge node it is also in my system I just have one node here so okay now it is processing for distribution this application package to edge node so okay it is already distributed and in this I can deploy this service instance to the edge node so this time it is not just for test it is for real running system user can deploy their applications to the real edge node okay it is already instantiated because I'm using the same node so you will find now it is working this edge node it is already deployed so that's all it is for the edge gallery developer platform, the app store and the running time MEC management system okay and I think I have just finished today's introduction and thank you everyone and here we have I want to have one introduce its lat here it is our main page of edge gallery and everyone who is interested on this who can contact me or directly go to this webpage to contact us thank you very much