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funinformatique · 4 years ago

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Comment vraiment pirater un compte Instagram ?

J'ai remarqué que sur les forums, beaucoup d’internautes se demandent comment pirater un compte Instagram. Dans cet article, je vais vous montrer comment le faire. Je vais utiliser Kali Linux, un système Linux, qui est populaire pour le piratage informatique. Si vous ne savez pas comment installer Kali sur votre machine, regardez simplement cet article: comment installer Kali Linux sur Windows.

Est-ce vraiment possible de pirater un compte Instagram ?

Sachez qu'un logiciel de piratage Instagram direct n’existe pas. En aucun cas, il n’y aura un miracle qui vous fera pirater une personne. C’est vrai, la sécurité informatique n’existe pas, mais pour pirater vraiment un compte Instagram, il faut être patient et intelligent. Ici, je vais donc utiliser la méthode attaque par force brute. Le principe de l’attaque consiste à essayer de trouver le mot de passe d'un compte Instagram en testant toutes les combinaisons de caractères possibles jusqu’à la découverte du mot de passe . Notez que pour réussir cette attaque, trois facteurs sont à prendre en compte: - La puissance de calcul de votre machine. - La complexité du mot de passe. - Les mots qui contient le dictionnaire du logiciel utilisé. Donc si le mot de passe que vous cherchez fait plus de 8 ou 9 caractères au total et qu’il contient des caractères spéciaux et des chiffres… cela risque d’être impossible de le trouver avec votre PC.

Étapes pour pirater un compte Instagram

Remarque: Cet article est à but éducatif et préventif uniquement. Apprendre l’attaque pour mieux se protéger. Vous êtes le seul(e) responsable de vos actions, et aucune responsabilité de la part de l’instructeur ne sera engagée quant à la mauvaise utilisation du contenu enseigné. Ce qu'il vous faut - Python v3.9 - L'application Instagram Bruter - Liste des mots de passe - Liste des proxy

Installer les dépendances Installer Pipenv apt install pip apt install pipenv Créer un environnement pipenv Assurez-vous que Python 3.9 est installé pipenv --python 3.9 Téléchargement du Programme Instagram Bruter Pour pirater un compte Instagram, vous devez tout d’abord obtenir le programme Instagram Bruter qui permet de réaliser des attaques par force brute. Pour cela, ouvrez le terminal sur Kali Linux et tapez simplement: git clone https://github.com/Bitwise-01/Instagram- Cette commande va cloner le programme sur votre ordinateur.

Ensuite, vous devez changer les droits du dossier Instagram- avec la commande chmod. Tapez donc: chmod -R 755 Instagram- && cd Instagram- Exécution du programme Maintenant que vous avez téléchargé le programme. Tapez: "ls" pour voir ce qu'il y a dans le dossier. Eh bien, nous avons trois fichiers dans le dossier: "Core", "README.md" et "instagram.py". Le fichier qui nous intéresse ici est "instagram.py". Lancez ce script en tapant: python3 instagram.py Oh non ! On dirait qu'il y a des erreurs ! Mais pourquoi ? Tout simplement parce que je n'ai pas encore ajouter le fichier txt contenant une série de mots de passe potentiels. Rappelez-vous qu’il s’agit d’une attaque par force brute. Pour trouver un mot de passe, le script doit tester une série de mots de passe potentiels, les uns à la suite des autres, en espérant que le mot de passe utilisé par le compte Instagram soit contenu dans le dictionnaire. Si ce n'est pas le cas, l'attaque échouera. Le programme a besoin également d'une liste de proxys pour fonctionner. Obtenir une liste de mots de passe potentiels Si vous voulez simplement tester ce programme, vous pouvez créer votre propre liste de mots de passe. Mais si vous essayez d'obtenir le mot de passe du compte Instagram de votre conjoint alors il faut télécharger une vraie liste. Pour cela, allez dans votre navigateur web et cherchez dans Google "daniel miessler passwords github". Ensuite cliquer sur le premier résultat des recherches Google. Maintenant, vous serez dans le site GitHub. Cliquez sur Passwords.

Choisissez un fichier txt. Je choisi la liste des 10 millions de mots de passe. Le plus gros sera le mieux, car vous aurez plus de chances de réussir. Enfin, téléchargez et enregistrez le fichier texte dans le dossier Instagram-. Maintenant nous pouvons commencer le test de piratage Instagram en toute simplicité. Télécharger une liste de proxys Pour lancez cette attaque, il faut téléchargez une liste de proxys dans le programme. Le fichier proxy doit avoir un format ip:port proxies_list.txt 3.238.111.248:80 206.189.59.192:8118 165.22.81.30:34100 176.248.120.70:3128 191.242.178.209:3128 180.92.194.235:80 Pour télécharger une liste de proxys, c'est par ici: https://github.com/clarketm/proxy-list/blob/master/proxy-list-raw.txt Enregistrer ce ficher texte dans le dossier Instagram- Ensuite, pour installer ces proxy dans la base de données du programme, tapez la commande suivante: Python3 instagram.py -px proxy-list-raw.txt Exécuter à nouveau ... Faisons ce que nous avons fait avant: ouvrez le terminal Kali Linux et tapez: python instagram.py -u nom_utilisateur_Instagram -p liste_des_mots_passe.txt Remplacer nom_utilisateur_instagram par le nom de votre cible et liste des_mots_passe par le nom de votre liste des mots de passe. Félicitations! L’attaque par force brute va commencer. Sur le terminal vous allez voir s'afficher les tentatives et le mot de passe que le script tente actuellement.

Patientez quelques temps, vous aurez la progression au fur et à mesure que le script avance dans la procédure. Si le script trouve le mot de passe, celui-ci sera clairement affiché. Il ne vous restera plus qu’à le saisir dans la page d'identification Instagram. Read the full article

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holytheoristtastemaker · 5 years ago

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Introduction

Hello, freeCodeCamp readers. I hope I can bring you some great coding content for inspiration, education and of course, fun! In this tutorial, we will learn about keyword density and how to build a tool that can calculate keyword density with Laravel. The web tool will allow us to paste in a full page of HTML. Then, magic will be executed to give us a precise keyword density score. In a quick summary, here are some basic skills we will touch upon whilst building the tool.

Laravel routes, controllers, and views

Laravel layouts

HTML & forms

JQuery & Ajax

Some native PHP

A bit of SEO!

What is keyword density?

If you have your own website or blog, you possibly already know what keyword density is. For those who don't know what it means I will give a short and sweet explanation below. Keyword density is a calculation of word or keyword occurrences usually in a large piece of text. The density is reported in a percentage which is simply calculated with the following formula. KeywordDensity = (Keyword Count / Word Count) * 100

Why is this important?

Keyword density is a key factor in the Google search engine algorithm. It is widely thought that a good keyword density for optimising web pages for Google rankings is around 3.5%. If the percentage is higher, for example 20%, then this could be seen as 'keyword stuffing' and therefore could badly affect your Google search rankings. So, that is a minuscule lesson on SEO and to give you a bit of context of what we are trying to build.

Building a Keyword Density Tool with Laravel

This tutorial will presume we are all starting with a fresh Laravel build enabling anyone to follow on from any particular point. (Apologies if the beginning sections are telling you to suck eggs!) Also, just for further context, I'm building this on MacOS with XAMPP locally.

Prerequisites

A PHP environment installed and access to the root directory

Composer installed

Your favourite code editor that interprets PHP, HTML, CSS & JS.

With all of these prerequisites checked off, we can now get our hands dirty.

Creating Our Laravel App

First of all we need to download and install a fresh Laravel build. Follow the steps below to achieve this.

Open your command line interface at the root directory of your web server, for example XAMPP⁩/⁨xamppfiles/⁩htdocs/

Run the following command and let composer do it's magic

composer create-project --prefer-dist laravel/laravel KeywordDensityApp

Top Tip: If you are working on MacOS, then check out the following steps to enable permissions on the Laravel storage folder.

Navigate to your CLI to the project folder ('KeywordDensityApp')

Run the following command

sudo chmod -R 777 storage/*

Adding a controller and view

Now that we have the basics out of the way, we can start to build our controller and web page that will allow a user to paste in and analyse some HTML. We can create a new controller in two ways: via the PHP artisan command line helper or simply by creating with your code editor. Feel free to use any of the below methods, just make sure the controller matches

Create controller with PHP artisan

php artisan make:controller ToolController

Create controller with code editor

Locate the following - ProjectFolder/App/Http/Controllers

Create a new .php file named ToolController

Make sure this newly created file has the following contents:

<?php namespace App\Http\Controllers; use Illuminate\Http\Request; class ToolController extends Controller { // }

Now let's create the view.

Create view with code editor

Locate view folder under ProjectFolder/resources/views

Create a new folder named tool

Create a new view PHP file named index.blade.php

Now let's create a layout file

With most Laravel applications, you will want to build a layouts file so that you don't have to repeat lots of HTML over and over to get the same design across the board. This layout is pretty basic, using a simple Bootstrap template and has a @yield call to the 'content' area which we will utilise in our views. In addition, there's a @yield call to 'scripts' which we will utilise later.

Locate view folder under ProjectFolder/resources/views

Create a new folder here named layouts

Create a new file named master.blade.php

Add the following code to the file

<!DOCTYPE html> <html lang=""> <head> <meta charset="utf-8"> <meta name="viewport" content="width=device-width, initial-scale=1"> <title>Keyword Density Tool</title> <link rel="stylesheet" href="https://stackpath.bootstrapcdn.com/bootstrap/4.4.1/css/bootstrap.min.css" integrity="sha384-Vkoo8x4CGsO3+Hhxv8T/Q5PaXtkKtu6ug5TOeNV6gBiFeWPGFN9MuhOf23Q9Ifjh" crossorigin="anonymous">  <link href="https://fonts.googleapis.com/css?family=Nunito:200,600" rel="stylesheet"> <meta name="csrf-token" content=""> <style> body {padding-top: 5em;} </style> </head> <body> <nav class="navbar navbar-expand-md navbar-dark bg-dark fixed-top"> <a class="navbar-brand" href="#">Keyword Density App</a> <button class="navbar-toggler" type="button" data-toggle="collapse" data-target="#navbarsExampleDefault" aria-controls="navbarsExampleDefault" aria-expanded="false" aria-label="Toggle navigation"> <span class="navbar-toggler-icon"></span> </button> <div class="collapse navbar-collapse" id="navbarsExampleDefault"> <ul class="navbar-nav mr-auto"> <li class="nav-item"> <a class="nav-link" href="/">Home <span class="sr-only">(current)</span></a> </li> <li class="nav-item active"> <a class="nav-link" href="">Tool</a> </li> </ul> </div> </nav> <main role="main" class="container mt-3"> @yield('content') </main> <script src="https://code.jquery.com/jquery-3.2.1.min.js"></script> <script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/umd/popper.min.js"></script> <script src="https://stackpath.bootstrapcdn.com/bootstrap/4.4.1/js/bootstrap.min.js"></script> @yield('scripts') </body> </html>

Extend our views to use the layout file

Let us now use the newly created layouts file in both our welcome view and tool index view. Follow these steps to extend to the layout.

Add the following code to both ProjectFolder/resources/views/welcome.blade.php and ProjectFolder/resources/views/tool/index.blade.php

@extends('layouts.master') @section('content') @endsection

Try rendering the index page of the tool directory, for example localhost/tool. It should look something like below.

Basic view layout

Linking up the Controller, Route, & View

Now that we have a controller and view we need to first define a route and second add a return view method to the controller.

Define the route

Locate web routes file under ProjectFolder/routes/web.php

Add the following code to the bottom of the file:

Route::get('/tool', 'ToolController@index')->name('KDTool');

Create the new controller method

Now, go back to your ToolController and add the following function:

public function index() { return view('tool.index'); }

Feel free to change the view names, route URLs, or controller functions to your personal liking. Just make sure they all match up and the page renders.

Building up our tool view

Now, with our earlier set up of views and layout files, we can start to add the content in the form of HTML that we are going to need. It will consist of nothing more than some text, textarea input form, and a submit button. Add the following HTML to the content section of the ProjectFolder/resources/views/tool/index.blade.php file.

<form id="keywordDensityInputForm"> <div class="form-group"> <label for="keywordDensityInput">HTML or Text</label> <textarea class="form-control" id="keywordDensityInput" rows="12"></textarea> </div> <button type="submit" class="btn btn-primary mb-2">Get Keyword Densities</button> </form>

The view should now render like this:

Keyword Density Tool View with Text Area input

Creating the bridge between the front end and the back end

Now, we pretty much have everything we need on the front end: a simple input text area where users can paste in their plain text or HTML. What's missing is the logic for when the button is pressed 'Get Keyword Densities'. This bridging logic will essentially do the following.

Listen for clicks on the Get Keyword Density Button

Grab the contents of the non-empty text area input

Use JQuery Ajax to send the data to the backend to be processed and await a response.

When the response is passed back, handle the data and create a HTML table with the human-readable statistics (keyword density).

Front end

To do this we will use an in-page script which we can inject using the @section tag. Add the following to the tool/index.blade.php view, after the content section.

@section ('scripts') <script> $('#keywordDensityInputForm').on('submit', function (e) { // Listen for submit button click and form submission. e.preventDefault(); // Prevent the form from submitting let kdInput = $('#keywordDensityInput').val(); // Get the input if (kdInput !== "") { // If input is not empty. // Set CSRF token up with ajax. $.ajaxSetup({ headers: { 'X-CSRF-TOKEN': $('meta[name="csrf-token"]').attr('content') } }); $.ajax({ // Pass data to backend type: "POST", url: "/tool/calculate-and-get-density", data: {'keywordInput': kdInput}, success: function (response) { // On Success, build a data table with keyword and densities if (response.length > 0) { let html = "<table class='table'><tbody><thead>"; html += "<th>Keyword</th>"; html += "<th>Count</th>"; html += "<th>Density</th>"; html += "</thead><tbody>"; for (let i = 0; i < response.length; i++) { html += "<tr><td>"+response[i].keyword+"</td>"; html += "<td>"+response[i].count+"</td>"; html += "<td>"+response[i].density+"%</td></tr>"; } html += "</tbody></table>"; $('#keywordDensityInputForm').after(html); // Append the html table after the form. } }, }); } }) </script> @endsection

This entire script that we inject will handle all of the numbered list items above. What is left to do is handle the data coming in on the back end side of things.

Back end

Firstly, before we go any further with coding, we need to handle the fact that both plain text and HTML can be submitted. For this we can use a nifty tool to help us out. html2text is the perfect PHP library for this use case, so it's time we install it. html2text does exactly what it says on the tin, converts HTML markup to plain text. Luckily, this package has a composer install command, so enter the following command into the CLI on the projects root directory.

composer require html2text/html2text

Now, our backend controller is going to receive either HTML or plain text in requests firing from the HTML form we created in our view. We now need to make the route to handle this call and to route the call to the specific controller that will work the magic. Add the following PHP to the web.php routes file:

Route::post('/tool/calculate-and-get-density', 'ToolController@CalculateAndGetDensity');

Secondly, add the following to ToolController.php file:

public function CalculateAndGetDensity(Request $request) { if ($request->isMethod('GET')) { } }

OK, so the stage is set. Let's code in the magic that will calculate the keyword density and return the data. Firstly, add use statement is required for the newly installed html2text package. Add the following to the top of the ToolController.php, just below other use statements:

use Html2Text\Html2Text;

Then we need to handle the get parameter that is to be passed in, making sure it's not set and then converting the parameter of content to plain text. Refactor the CalculateAndGetDensity function to look like below:

Now that we have a variable to hold all of the text stripped for the keywordInput parameter, we can go ahead and start to calculate density. We need to handle the following:

Determine the total count of words

Analyse the textual string and convert it to a key value array (the key being the keyword, the value being the occurrence of the word)

Sort into order by descending with the biggest occurrence first in the array

Loop over the key and value array, pushing the values to a new array with an additional field of 'density' which utilises the keyword density formula we looked at earlier in the article. This formula will use the value (occurrence) and the total word count.

Finally, to return the data

Refactor the function to look like the following, taking note of the comments:

public function CalculateAndGetDensity(Request $request) { if ($request->isMethod('GET')) { if (isset($request->keywordInput)) { // Test the parameter is set. $html = new Html2Text($request->keywordInput); // Setup the html2text obj. $text = strtolower($html->getText()); // Execute the getText() function and convert all text to lower case to prevent work duplication $totalWordCount = str_word_count($text); // Get the total count of words in the text string $wordsAndOccurrence = array_count_values(str_word_count($text, 1)); // Get each word and the occurrence count as key value array arsort($wordsAndOccurrence); // Sort into descending order of the array value (occurrence) $keywordDensityArray = []; // Build the array foreach ($wordsAndOccurrence as $key => $value) { $keywordDensityArray[] = ["keyword" => $key, // keyword "count" => $value, // word occurrences "density" => round(($value / $totalWordCount) * 100,2)]; // Round density to two decimal places. } return $keywordDensityArray; } } }

Note: The beauty of html2text is that it doesn't really care if it's converting HTML or plain text in the first place, so we don't need to worry if a user submits either. It will still churn out plain text.

Putting it to the test

Finally, we are ready to test the tool, wahoo! Go ahead and render the tool index view (localhost/tool).

Now, you can go to any website of your choice on the web, load a page from that site, right click and click view source.

Copy the entire contents and come back to the tool.

Paste the contents into the text area and click the Get Keyword Densities button.

Await the response and check out the table of keyword densities!

Check out my example below which uses the HTML of this page.

Keyword Density Tool & Table of keywords

And that is it!

Summary

In this article we learned how to build a Laravel application from scratch. It touched on some of the different parts of the full stack in development such as JQuery, PHP, HTML etc. Hopefully, with the understanding of this application, the same methodology can be used to build something else, perhaps bigger and better.

Possible further developments

The keyword density tool currently takes 'stop' words into account. Stop words are known to be ignored by Googles crawlers. Words such as it, the, as, and a. Looking at the tool screenshot above, you can see that they are used a lot! Further development could be carried out to filter the stop words and only calculate density on the non-stop words which is potentially a better view for SEO scoring.

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suzanneshannon · 6 years ago

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Moving an ASP.NET Core from Azure App Service on Windows to Linux by testing in WSL and Docker first

I updated one of my websites from ASP.NET Core 2.2 to the latest LTS (Long Term Support) version of ASP.NET Core 3.1 this week. Now I want to do the same with my podcast site AND move it to Linux at the same time. Azure App Service for Linux has some very good pricing and allowed me to move over to a Premium v2 plan from Standard which gives me double the memory at 35% off.

My podcast has historically run on ASP.NET Core on Azure App Service for Windows. How do I know if it'll run on Linux? Well, I'll try it see!

I use WSL (Windows Subsystem for Linux) and so should you. It's very likely that you have WSL ready to go on you machine and you just haven't turned it on. Combine WSL (or the new WSL2) with the Windows Terminal and you're in a lovely spot on Windows with the ability to develop anything for anywhere.

First, let's see if I can run my existing ASP.NET Core podcast site (now updated to .NET Core 3.1) on Linux. I'll start up Ubuntu 18.04 on Windows and run dotnet --version to see if I have anything installed already. You may have nothing. I have 3.0 it seems:

$ dotnet --version 3.0.100

Ok, I'll want to install .NET Core 3.1 on WSL's Ubuntu instance. Remember, just because I have .NET 3.1 installed in Windows doesn't mean it's installed in my Linux/WSL instance(s). I need to maintain those on my own. Another way to think about it is that I've got the win-x64 install of .NET 3.1 and now I need the linux-x64 one.

NOTE: It is true that I could "dotnet publish -r linux-x64" and then scp the resulting complete published files over to Linux/WSL. It depends on how I want to divide responsibility. Do I want to build on Windows and run on Linux/Linux? Or do I want to build and run from Linux. Both are valid, it just depends on your choices, patience, and familiarity.

GOTCHA: Also if you're accessing Windows files at /mnt/c under WSL that were git cloned from Windows, be aware that there are subtleties if Git for Windows and Git for Ubuntu are accessing the index/files at the same time. It's easier and safer and faster to just git clone another copy within the WSL/Linux filesystem.

I'll head over to https://dotnet.microsoft.com/download and get .NET Core 3.1 for Ubuntu. If you use apt, and I assume you do, there's some preliminary setup and then it's a simple

sudo apt-get install dotnet-sdk-3.1

No sweat. Let's "dotnet build" and hope for the best!

It might be surprising but if you aren't doing anything tricky or Windows-specific, your .NET Core app should just build the same on Windows as it does on Linux. If you ARE doing something interesting or OS-specific you can #ifdef your way to glory if you insist.

Bonus points if you have Unit Tests - and I do - so next I'll run my unit tests and see how it goes.

OPTION: I write things like build.ps1 and test.ps1 that use PowerShell as PowerShell is on Windows already. Then I install PowerShell (just for the scripting, not the shelling) on Linux so I can use my .ps1 scripts everywhere. The same test.ps1 and build.ps1 and dockertest.ps1, etc just works on all platforms. Make sure you have a shebang #!/usr/bin/pwsh at the top of your ps1 files so you can just run them (chmod +x) on Linux.

I run test.ps1 which runs this command

dotnet test /p:CollectCoverage=true /p:CoverletOutputFormat=lcov /p:CoverletOutput=./lcov .\hanselminutes.core.tests

with coverlet for code coverage and...it works! Again, this might be surprising but if you don't have any hard coded paths, make any assumptions about a C:\ drive existing, and avoid the registry and other Windows-specific things, things work.

Test Run Successful. Total tests: 23 Passed: 23 Total time: 9.6340 Seconds Calculating coverage result... Generating report './lcov.info' +--------------------------+--------+--------+--------+ | Module | Line | Branch | Method | +--------------------------+--------+--------+--------+ | hanselminutes.core.Views | 60.71% | 59.03% | 41.17% | +--------------------------+--------+--------+--------+ | hanselminutes.core | 82.51% | 81.61% | 85.39% | +--------------------------+--------+--------+--------+

I can build, I can test, but can I run it? What about running and testing in containers?

I'm running WSL2 on my system and I've doing all this in Ubuntu 18.04 AND I'm running the Docker WSL Tech Preview. Why not see if I can run my tests under Docker as well? From Docker for Windows I'll enabled the Experimental WSL2 support and then from the Resources menu, WSL Integration I'll enable Docker within my Ubuntu 18.04 instance (your instances and their names will be your own).

I can confirm it's working with "docker info" under WSL and talking to a working instance. I should be able to run "docker info" in BOTH Windows AND WSL.

$ docker info Client: Debug Mode: false Server: Containers: 18 Running: 18 Paused: 0 Stopped: 0 Images: 31 Server Version: 19.03.5 Storage Driver: overlay2 Backing Filesystem: extfs ...snip...

Cool. I remembered I also I needed to update my Dockerfile as well from the 2.2 SDK on the Docker hub to the 3.1 SDK from Microsoft Container Registry, so this one line change:

#FROM microsoft/dotnet:2.2-sdk AS build FROM mcr.microsoft.com/dotnet/core/sdk:3.1 as build

as well as the final runtime version for the app later in the Dockerfile. Basically make sure your Dockerfile uses the right versions.

#FROM microsoft/dotnet:2.1-aspnetcore-runtime AS runtime FROM mcr.microsoft.com/dotnet/core/aspnet:3.1 AS runtime

I also volume mount the tests results so there's this offensive If statement in the test.ps1. YES, I know I should just do all the paths with / and make them relative.

#!/usr/bin/pwsh docker build --pull --target testrunner -t podcast:test . if ($IsWindows) { docker run --rm -v d:\github\hanselminutes-core\TestResults:/app/hanselminutes.core.tests/TestResults podcast:test } else { docker run --rm -v ~/hanselminutes-core/TestResults:/app/hanselminutes.core.tests/TestResults podcast:test }

Regardless, it works and it works wonderfully. Now I've got tests running in Windows and Linux and in Docker (in a Linux container) managed by WSL2. Everything works everywhere. Now that it runs well on WSL, I know it'll work great in Azure on Linux.

Moving from Azure App Service on Windows to Linux

This was pretty simple as well.

I'll blog in detail how I build andd eploy the sites in Azure DevOps and how I've moved from .NET 2.2 with Classic "Wizard Built" DevOps Pipelines to a .NET Core 3.1 and a source control checked-in YAML pipeline next week.

The short version is, make a Linux App Service Plan (remember that an "App Service Plan " is a VM that you don't worry about. See in the pick below that the Linux Plan has a penguin icon. Also remember that you can have as many apps inside your plan as you'd like (and will fit in memory and resources). When you select a "Stack" for your app within Azure App Service for Linux you're effectively selecting a Docker Image that Azure manages for you.

I started by deploying to staging.mydomain.com and trying it out. You can use Azure Front Door or CloudFlare to manage traffic and then swap the DNS. I tested on Staging for a while, then just changed DNS directly. I waited a few hours for traffic to drain off the Windows podcast site and then stopped it. After a day or two of no traffic I deleted it. If I did my job right, none of you noticed the site moved from Windows to Linux, from .NET Core 2.2 to .NET Core 3.1. It should be as fast or faster with no downtime.

Here's a snap of my Azure Portal. As of today, I've moved my home page, my blood sugar management portal, and my podcast site all onto a single Linux App Service Plan. Each is hosted on GitHub and each is deploying automatically with Azure DevOps.

Next big migration to the cloud will be this blog which still runs .NET Framework 4.x. I'll blog how the podcast gets checked into GitHub then deployed with Azure DevOps next week.

What cool migrations have YOU done lately, Dear Reader?

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Moving an ASP.NET Core from Azure App Service on Windows to Linux by testing in WSL and Docker first published first on https://deskbysnafu.tumblr.com/

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philipholt · 6 years ago