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updates/organize better the project documentation
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‎README.md

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# Microservices with .Net Core, Docker and Azure Service Fabric
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# Microservices with .Net Core, Docker and Azure Service Fabric/Kubernetes
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## Prerequisites and Installation Requirements
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## Prerequisites and Installation Requirements (only for development)
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1. Install [Docker for Windows](https://docs.docker.com/docker-for-windows/install/).
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2. Install [.NET Core SDK](https://www.microsoft.com/net/download/windows)
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3. Install [Visual Studio 2019](https://www.visualstudio.com/downloads/) 16.4 or later.
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4. Share drives in Docker settings, in order to deploy and debug with Visual Studio 2019 (See the below image)
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1. Install Docker for [Windows](https://docs.docker.com/docker-for-windows/install/)/[Mac](https://docs.docker.com/docker-for-mac/install/).
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2. Install [.NET Core SDK](https://www.microsoft.com/net/download)
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3. Install [Visual Studio](https://www.visualstudio.com/downloads/) 2017 15.8 or later (Visual Studio 2019 16.4 or later recommended) or [Visual Studio Code](https://code.visualstudio.com/).
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4. [Tuning Docker for better performance and Debugging](https://github.com/vany0114/microservices-dotnetcore-docker-sf-k8s/blob/master/TunningDocker.md)
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5. Clone this Repo
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6. Set `docker-compose` project as startup project.
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7. Press F5 and that's it!
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![](https://github.com/vany0114/vany0114.github.io/blob/master/images/docker_settings_shared_drives.png)
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## Architecture and Deployment
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* [Local deployment](https://github.com/vany0114/microservices-dotnetcore-docker-sf-k8s/blob/master/local-deployment.md)
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* [Service Fabric Architecture and Deployment](https://github.com/vany0114/microservices-dotnetcore-docker-sf-k8s/blob/master/SF-architecture.md)
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* [Kubernetes Architecture and Deployment](https://github.com/vany0114/microservices-dotnetcore-docker-sf-k8s/blob/master/k8s-architecture.md)
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> Note: The first time you hit F5 it'll take a few minutes, because in addition to compile the solution, it needs to pull/download the base images (SQL for Linux Docker, ASPNET, MongoDb and RabbitMQ images) and register them in the local image repo of your PC. The next time you hit F5 it'll be much faster.
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### Tuning Docker for better performance
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It is important to set Docker up properly with enough memory RAM and CPU assigned to it in order to improve the performance, or you will get errors when starting the containers with VS 2017 or "docker-compose up". Once Docker for Windows is installed in your machine, enter into its Settings and the Advanced menu option so you are able to adjust it to the minimum amount of memory and CPU (Memory: Around 4096MB and CPU:3) as shown in the image.
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![](https://github.com/vany0114/vany0114.github.io/blob/master/images/docker_settings.png)
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### Architecture
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![](https://github.com/vany0114/vany0114.github.io/blob/master/images/Duber_Production_Environment_Architecture.png)
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### Demo Screenshots
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#### Website
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## Screenshots
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### Website
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![](https://github.com/vany0114/vany0114.github.io/blob/master/images/duber-in-action.gif)
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#### Trip API
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### Trip API
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![](https://github.com/vany0114/vany0114.github.io/blob/master/images/duber-trip-api.png)
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#### Invoice API
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### Invoice API
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![](https://github.com/vany0114/vany0114.github.io/blob/master/images/duber-invoice-api.png)
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## Support
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If you find this project helpful you can [support me](http://www.paypal.me/vany0114/3)!
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Visit my blog <http://elvanydev.com/Microservices-part1/> to view all the posts and to know all the details about this project.
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Visit my blog <http://elvanydev.com/Microservices-part1/> to view the whole posts series and to know all the details about this project.

‎SF-architecture.md

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# Service Fabric Architecture and Deployment
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## Architecture
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![](https://github.com/vany0114/vany0114.github.io/blob/master/images/Duber_Production_Environment_Architecture.png)
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## Deployment
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Visit [my blog](http://elvanydev.com/Microservices-part4/) to see all about the deployment using a Service Fabric cluster.

‎TunningDocker.md

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# Tuning Docker for better performance and Debugging
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It is important to set Docker up properly with enough memory RAM and CPU assigned to it in order to improve the performance on your local/development environment, or you will get errors when starting the containers with VS 2019 or "docker-compose up". Once Docker is installed in your machine, enter into its Settings and the Advanced menu option so you are able to adjust it to the minimum amount of memory and CPU (Memory: Around 4096MB and CPU:3) as shown in the image.
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![](https://github.com/vany0114/vany0114.github.io/blob/master/images/docker_settings.png)
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Share drives in Docker settings, in order to deploy it as a Docker Compose application and also to debug with Visual Studio 2019 (See the below image)
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![](https://github.com/vany0114/vany0114.github.io/blob/master/images/docker_settings_shared_drives.png)
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> Note: The first time you hit F5 it'll take a few minutes, because in addition to compile the solution, it needs to pull/download the base images (SQL for Linux Docker, ASPNET, MongoDb and RabbitMQ images, etc) and register them in the local image repo of your PC. The next time you hit F5 it'll be much faster.

‎deploy/k8s/local/deploy-local.ps1

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# k8s dashboard
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kubectl apply -f https://raw.githubusercontent.com/kubernetes/dashboard/v2.0.0-beta8/aio/deploy/recommended.yaml
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kubectl apply -f dashboard-adminuser.yaml
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# nginx-ingress
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kubectl apply -f https://raw.githubusercontent.com/kubernetes/ingress-nginx/master/deploy/static/mandatory.yaml
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kubectl apply -f nginx-ingress\custom-service.yaml
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# mongo
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kubectl apply -f mongo\mongo-admin.yaml
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kubectl apply -f mongo\mongo-deployment.yaml
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kubectl apply -f mongo\mongo-service.yaml
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# rabbit
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kubectl apply -f rabbit\rabbit-admin.yaml
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kubectl apply -f rabbit\rabbit-deployment.yaml
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kubectl apply -f rabbit\rabbit-service.yaml
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# sql-server
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kubectl apply -f sql-server\sql-admin.yaml
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kubectl apply -f sql-server\sql-deployment.yaml
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kubectl apply -f sql-server\sql-service.yaml
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# external system
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kubectl apply -f external-system\payment-deployment.yaml
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kubectl apply -f external-system\payment-service.yaml
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# invoice
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kubectl apply -f invoice\invoice-deployment.yaml
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kubectl apply -f invoice\invoice-ingress.yaml
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kubectl apply -f invoice\invoice-service.yaml
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# trip
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kubectl apply -f trip\trip-deployment.yaml
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kubectl apply -f trip\trip-hpa.yaml
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kubectl apply -f trip\trip-ingress.yaml
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kubectl apply -f trip\trip-service.yaml
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# website
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kubectl apply -f website\website-deployment.yaml
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kubectl apply -f website\website-hpa.yaml
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kubectl apply -f website\website-ingress.yaml
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kubectl apply -f website\website-service.yaml

‎k8s-architecture.md

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# Kubernetes Architecture and Deployment
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## Architecture
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WIP
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## Deployment
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WIP

‎local-deployment.md

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# Local deplyment using Kubernetes
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## Prerequisites and Installation Requirements
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1. Install Docker for [Windows]((https://docs.docker.com/docker-for-windows/install/))/[Mac](https://docs.docker.com/docker-for-mac/install/).
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2. Make sure to check the opton *Enable Kubernetes* on your Docker settings.
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![](https://github.com/vany0114/vany0114.github.io/blob/master/images/docker-desktop-k8s.png)
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3. Run `deploy-local.ps1` script to deploy the solution on your local Kubernetes cluster.
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4. Add `duber.local.com` domain to your `hosts` file. That's the host using by our Ingress in order to expose the Frontend.
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```
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127.0.0.1 duber.local.com
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```
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Optionally, if you want to expose the API's you have to add `invoice.local.com` and `trip.local.com` domains too.
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```
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127.0.0.1 invoice.local.com
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127.0.0.1 trip.local.com
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```
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6. Go to http://duber.local.com:81/ and you'll see the application up and working!
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## Admin tools
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To be able to access to our SQL or Mongo databases through an IDE, or to RabbitMQ' dashboard, we exposed a port through a `Node Port`:
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* SQL Server: `31433`, connection example: `tcp:127.0.0.1,31433`
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* Mongo: `31434`, connection example: `mongodb://0.0.0.0:31434/`
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* RabbitMQ: `31672`, connection example: `http://localhost:31672/#/`

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