Showing posts with label serverless. Show all posts
Showing posts with label serverless. Show all posts

How to Deploy your Azure Function Automatically with ARM template (4 different ways)

It's so nice to be able to add some serverless components in our solution to make them better in a snap. But how do we manage them? In this post, I will explain how to create an Azure resource manager (ARM) template to deploy any Azure Function and show how I used this structure to deploy an open-source project I've been working on these days.

Part 1 - The ARM template

An ARM template is a JSON file that describes our architecture. To deploy an Azure Function we need at least three recourses: a functionApp, a service plan, and a storage account.


The FunctionApp is, of course, our function. The service plan could be set as dynamic or describe the type of resource that will be used by your function. The storage account is where is our code.


In the previous image, you can see how those components interact more with each other. Inside the Function, we will have a list of properties. One of those properties will be the Runtime, for example, in the AZUnzipEverything demo, it will be dotnet. Another property will be the connection string to our storage account that is also part of our ARM template. Since that resource doesn't exist yet, we will need to use the dynamic code.

The Function node will contain a sub-resource of type storageAccount. This is where we will specify where is our code, so it cant be clone to Azure.

Building ARM for a Simple Function


Let's see a template for a simple Azure Function that doesn't require any dependency, and we will examine it after.

You can use any text editor to edit your ARM template. However, the bundle VSCode with the extensions Azure Resource Manager Tools and Azure Resource Manager Snippets is particularly efficient.
{
    "$schema": "https://schema.management.azure.com/schemas/2015-01-01/deploymentTemplate.json#",
    "contentVersion": "1.0.0.0",
    "parameters": {},
    "variables": {},
    "resources": [
        {
            "type": "Microsoft.Storage/storageAccounts",
            "apiVersion": "2018-07-01",
            "name": "storageFunc",
            "location": "[resourceGroup().location]",
            "tags": {
                "displayName": "storageFunc"
            },
            "sku": {
                "name": "Standard_LRS"
            },
            "kind": "StorageV2"
        },
        {
            "type": "Microsoft.Web/serverfarms",
            "apiVersion": "2018-02-01",
            "name": "servicePlan",
            "location": "[resourceGroup().location]",
            "sku": {
                "name": "Y1",
                "tier": "Dynamic"
            },
            "properties": {
                "name": "servicePlan",
                "computeMode": "Dynamic"
            },
            "tags": {
                "displayName": "servicePlan"
            }
        },
         {
              "apiVersion": "2015-08-01",
              "type": "Microsoft.Web/sites",
              "name": "functionApp",
              "location": "[resourceGroup().location]",
              "kind": "functionapp",
              "dependsOn": [
                "[resourceId('Microsoft.Web/serverfarms', 'servicePlan')]",
                "[resourceId('Microsoft.Storage/storageAccounts', 'storageFunc')]"
              ],
              "properties": {
                "serverFarmId": "[resourceId('Microsoft.Web/serverfarms', 'servicePlan')]",
                "siteConfig": {
                  "appSettings": [
                    {
                      "name": "AzureWebJobsDashboard",
                      "value": "[concat('DefaultEndpointsProtocol=https;AccountName=', 'storageFunc', ';AccountKey=', listKeys('storageFunc','2015-05-01-preview').key1)]"
                    },
                    {
                      "name": "AzureWebJobsStorage",
                      "value": "[concat('DefaultEndpointsProtocol=https;AccountName=', 'storageFunc', ';AccountKey=', listKeys('storageFunc','2015-05-01-preview').key1)]"
                    },
                    {
                      "name": "WEBSITE_CONTENTAZUREFILECONNECTIONSTRING",
                      "value": "[concat('DefaultEndpointsProtocol=https;AccountName=', 'storageFunc', ';AccountKey=', listKeys('storageFunc','2015-05-01-preview').key1)]"
                    },
                    {
                      "name": "WEBSITE_CONTENTSHARE",
                      "value": "storageFunc"
                    },
                    {
                      "name": "FUNCTIONS_EXTENSION_VERSION",
                      "value": "~2"
                    },
                    {
                      "name": "FUNCTIONS_WORKER_RUNTIME",
                      "value": "dotnet"
                    }
                  ]
                }
              },
              "resources": [
                  {
                      "apiVersion": "2015-08-01",
                      "name": "web",
                      "type": "sourcecontrols",
                      "dependsOn": [
                        "[resourceId('Microsoft.Web/sites/', 'functionApp')]"
                      ],
                      "properties": {
                          "RepoUrl": "https://github.com/FBoucher/AzUnzipEverything.git",
                          "branch": "master",
                          "publishRunbook": true,
                          "IsManualIntegration": true
                      }
                 }
              ]
            }
        
    ],
    "outputs": {}
}

The Storage Account


The first resources listed in the template is the Account Storage. There nothing specific about it.

The Service Plan


The service plan is the second resource in the list. It's important to notice that to be able to use the SKU Dynamic you will need at least the API version of apiVersion to be "2018-02-01". Then you specify the SKU.

    "sku": {
        "name": "Y1",
        "tier": "Dynamic"
    }

Of course, you can use the other SKU if you prefer.

The Function App


Final resources added to the mixt, and this is where all the pieces are getting together. It's important to notice that the other in which the resources are listed are not considered by Azure while deploying (it's only for us ;) ). To let Azure knows you need to add dependencies.

"dependsOn": [
    "[resourceId('Microsoft.Web/serverfarms', 'servicePlan')]",
    "[resourceId('Microsoft.Storage/storageAccounts', 'storageFunc')]"
]

This way the Azure Function will be created after the service plan and the storage account are available. Then in the properties we will be able to build the ConnectionString to the blob storage using a reference.

{
    "name": "AzureWebJobsDashboard",
    "value": "[concat('DefaultEndpointsProtocol=https;AccountName=', 'storageFunc', ';AccountKey=', listKeys('storageFunc','2015-05-01-preview').key1)]"
}

The last piece of the puzzle is the sub-resource sourcecontrol inside the FunctionApp. This will define where Azure should clone the code from and in which branch.

"resources": [
    {
        "apiVersion": "2015-08-01",
        "name": "web",
        "type": "sourcecontrols",
        "dependsOn": [
        "[resourceId('Microsoft.Web/sites/', 'functionApp')]"
        ],
        "properties": {
            "RepoUrl": "https://github.com/FBoucher/AzUnzipEverything.git",
            "branch": "master",
            "publishRunbook": true,
            "IsManualIntegration": true
        }
    }
]

To be sure that everything is fully automatic the properties publishRunbook and IsManualIntegration must be set as true. Otherwise, you will need to do a synchronization between your Git (in this case on GitHub), and the Git in Azure.

There is excellent documentation that explains many deferent scenarios to Automate resource deployment for your function app in Azure Functions

Azure Unzip Everything


To deploy the project AzUnzipEverything available on GitHub, I needed one more Azure Storage with pre-define containers (folders).


Of course, all the source code of both the Azure Function and the ARM template are available on GitHub, but let me highlight how the containers are defined from an ARM template.

"resources": [
    {
        "type": "blobServices/containers",
        "apiVersion": "2018-07-01",
        "name": "[concat('default/', 'input-files')]",
        "dependsOn": [
            "storageFiles"
        ],
        "properties": {
            "publicAccess": "Blob"
        }
    }
]

Just like with sourcecontrol, we will need to add a list of sub-resources to our storage account. The name MUST start by 'default/'.

Part 2 - Four Deployment Options

Now that we have a template that describes our needs we just need to deploy it. There are multiple ways it could be done, but let's see four of them.

Deploy from the Azure Portal


Navigate to the Azure Portal (https://azure.portal.com), from your favorite browser and search for "deploy a custom template" directly in the search bar located at the top of the screen (in the middle). Or go at https://portal.azure.com/#create/Microsoft.Template. One in the Custom deployment page, click on the link Build your own template in the editor. From there, you can copy-paste or upload your ARM template. You need to save it to see the real deployment form.


Deploy with a script


Would it be in PowerShell or in Azure CLI you can easily deploy your template with these two commands.

In Azure CLI

# create resource group
az group create -n AzUnzipEverything -l eastus

# deploy it
az group deployment create -n cloud5mins -g AzUnzipEverything --template-file "deployment\deployAzure.json" --parameters "deployment\deployAzure.parameters.json"  

In PowerShell

# create resource group
New-AzResourceGroup -Name AzUnzipEverything -Location eastus

# deploy it
New-AzResourceGroupDeployment -ResourceGroupName  AzUnzipEverything -TemplateFile deployment\deployAzure.json

Deploy to Azure Button


One of the best way to help people to deploy your solution in their Azure subscription is the Deploy to Azure Button.



You need to create an image link (in HTML or Markdown) to this to a special destination build in two-part.

The first one is a link to the Azure Portal:

https://portal.azure.com/#create/Microsoft.Template/uri/

And the second one is the location of your ARM template:

https%3A%2F%2Fraw.githubusercontent.com%2FFBoucher%2FAzUnzipEverything%2Fmaster%2Fdeployment%2FdeployAzure.json

However, this URL needs to be encoded. There is plenty of encoders online, but you can also do it from the terminal with the following command (A big thanks to @BrettMiller_IT who showed me this trick during one of my live streams).

[System.Web.HttpUtility]::UrlEncode("https://raw.githubusercontent.com/FBoucher/Not-a-Dog-Workshop/master/deployment/deployAzure.json")

Clicking the button will bring the user at the same page on the Azure Portal but in the user subscription.

Azure DevOps Pipeline

From the Azure DevOps portal (https://dev.azure.com), select your project and create a new Release Pipeline. Click on the + Add an artifact button to connect your Git repository.



Once it's added, you need to add a task the current job. Click on the link 1 job, 0 task (4). Now you just need to specify your Azure subscription, the name of the resource group and select the location of your ARM template inside your repository. To make the deployment automatic with each push in the repository, click that little lightning bolt and enable the Continuous deployment trigger.


Wrapping-up

Voila, you know have four different ways to deploy your Azure Function automatically. But don't take my word for it, try it yourself! If you need more details you can visit the project on GitHub or watch this video where I demo the content of this post.


The Dog-Not-a-Dog Workshop


I recently presented, a workshop at the TOHack to get started with Azure. The goal was to try different Azure services, and see how we could augment an existing website using serverless function and artificial intelligence.
(Aussi disponible en français)


During this workshop, a website is deployed automatically from GitHub. Then by adding an Azure Function and using the Vision API of Azure Cognitive Services, the final solution is able to detect when uploaded pictures are or not dogs and keep our image folder "clean". We call that application: The automatic Not a Dog application.

The step by step instruction with the code can be found on GitHub - Not-a-Dog-Workshop. The workshop can be done in about 45-60 minutes.

I also did a video that is available on my YouTube channel:



You have questions, you are blocked, it will be a pleasure to help you.


Be more Productive by using Inline Code in your Azure Logic App

In a project using Azure Logic Apps that I am working on, I needed to manipulate strings. I could create APIs or Azure Functions, but the code is very simple and is not using any external libraries. In this post, I will show you how to use the new Inline Code to execute your code snippet directly inside your Logic Apps.

Quick Context


The Logic App will read a file from my OneDrive (it will also work with DropBox, Box, etc.). Here an example of the file:

Nice tutorial that explains how to build, using postman, an efficient API.[cloud.azure.postman.tools]

The goal is to extract tags, contained between the square brackets, from the text.

Logic App: Get File Content


From the Azure Portal, create a new Logic App by clicking the big green "+" button in the top left corner and searching for Logic App.

For this demo, I will use the Interval as a trigger because I will execute the Logic App manually.

The first step will be a Get File Content action from the OneDrive connector. Once you authorized Azure to access your OneDrive folder, select the file you want to read. For me, it's /dev/simpleNote.txt

Integration Account


To access the workflowContext the Azure Logic App required an Integration account. Next step would be to create one. Save the current Logic App, and click on the big "+" button in the top right corner. This time search for integration. Select Integration Account, and complete the form to create it.


We now need to assign it to our Logic App. From the Logic App blade, in the options list select Workflow Settings. Then select your integration account, and don't forget to save!

Logic App: Inline Code


To add the action at the end of your workflow, click the New step button. Search for Inline Code, and select the action Execute JavaScript Code.


Before copy-pasting the code into the new Inline Code action let's have a quick look.

var note = "" + workflowContext.actions.Get_file_content.outputs.body;
var posTag = note.lastIndexOf("[") + 1;
var cleanNote = {};

if(posTag > 0){
        cleanNote.tags = note.substring(posTag, note.length-1);
        cleanNote.msg = note.substring(0,posTag-1);
    }
return cleanNote;

On the first line, we assign a variable note the content of the Get_file_content outputs. We access it using the workflowContext. This context has access to the trigger and the actions. To find the name of the action you can replace the spaces by the underscore character "_".


You can also switch to Code View, and see the name of all components from the JSON code.

Logic App: Use Inline Code Result


Of course, you can use the output of your Inline Code with other steps. You just need to use the Result from the dynamic content menu.


If for some reason the dynamic content list doesn't contain your Inline Code, you can always add the code directly @body('Cleaning_Note')?['body'].


Your Logic App should now look like this:


Verdict


The Inline code is very promising. Right now it's limited to JAvaScript and cannot access variable nor loops. However, for simple code that doesn't require any references, it's easier to maintain and deploy. You can learn more about what is exactly covered or not here.
And it works as this result shows.


You prefer watching instead or Reading


I also have a video of this post if you prefer.



References


Reading Notes #373

Cloud


Programming


Books



Donald Miller

A really interesting book that helps to focus and keep in mind the most important. I didn't read it with a purpose of business really, but it did make me remember past experiences and it was easy to make the relationship between success and when the story was clear. Take the time to read it, do the exercises/ reflections required... it's worth it.










~

Reading Notes #371

Cloud


Programming


Miscellaneous


Reading Notes #359

DockerDesktopCloud


Programming


Databases


Miscellaneous


Books

How to Be a Bawse_cover
How to Be a Bawse A Guide to Conquering Life
Lilly Singh
Not only the message is strong, but the way she delivers it is awesome. Many times I laugh and nod of the head... Definitely a great book to read at the end of the year when resolution time is not far...









~

Reading Notes #357

71lKlEYntPL._SL1500_Suggestion of the week


Cloud


Programming


Miscellaneous



~


Reading Notes #351

MVIMG_20181111_190706

Cloud


Programming


Data


~


Reading Notes #333

flag-28555_640Cloud


Programming


Data


How to Deploy your Azure Functions Faster and Easily with Zip Push

Azure functions are great. I used to do a lot of "csx" version (C# scripted version) but more recently I switched to the compile version, and I definitely loved it! However, I was looking for a way to keep my deployment short and sweet, because sometimes I don't have time to setup a "big" CI/CD or simply because sometimes I'm not the one doing the deployment... In those cases, I need a simple script that will deploy everything! In this post, I will share with you how you can deploy everything with one easy script.

The Context


In this demo, I will deploy a simple C# (full .Net framework) Azure functions. I will create the Azure Function App and storage using an Azure Resource Manager (ARM template) and deploy with a method named Zip push or ZipDeploy. All the code, script, a template is available on my Github.

The Azure Functions Code


The Azure Function doesn't have to be special, and it can be any language supported by Azure Functions. Simply to show you everything, here the code of my function.


namespace AzFunctionZipDeploy
{
    public static class Function1
    {
        [FunctionName("GetTopRunner")]
        public static async Task Run([HttpTrigger(AuthorizationLevel.Function, "get", "post", Route = null)]HttpRequestMessage req, TraceWriter log)
        {
            log.Info("C# HTTP trigger function processed a request.");

            string top = req.GetQueryNameValuePairs()
                .FirstOrDefault(q => string.Compare(q.Key, "top", true) == 0)
                .Value;

            if (top == null)
            {
                dynamic data = await req.Content.ReadAsAsync< object>();
                top = data?.top;
            }

        return top == null
                ? req.CreateResponse(HttpStatusCode.BadRequest, "Please pass a number to get your top x runner on the query string or in the request body")
                : req.CreateResponse(HttpStatusCode.OK, new { message = $"Hello, here is your Top {top} runners", runners = A.ListOf(int.Parse(top)) });
        }
    }

    class Person
    {
        public string FirstName { get; set; }
        public string LastName { get; set; }
        public int Age { get; set; }
    }
}

It's a really simple function that will return a list of Person generated on the fly. The list will contain as many person as the number passed in parameter. I'm using the very useful GenFu library, from my buddies: ASP.NET Monsters.

The only thing we need to do is to create our compress file (Zip or Rar) that contains everything our project required.

createZip

In this case, it's the project file (AzFunction-ZipDeploy.csproj), the function's code (Function1.cs) the host (host.json) and local settings of our function (local.settings.json).

The ARM template


For this demo, we need one Azure Function App. I will use a template that is part of the Azure Quickstart Templates. A quick look to the azuredeploy.parameters.json file and we see that the only parameter we really need to set is the name of our application.


{
    "$schema": "https://schema.management.azure.com/schemas/2015-01-01/deploymentParameters.json#",
    "contentVersion": "1.0.0.0",
    "parameters": {
        "appName": {
        "value": "zipdeploydemo"
        }
    }
}

To be able to ZipDeploy, we need to add one Application Setting to let the Kudu interface we need its help to compile our code. To do that let's open the azuredeploy.json and go to the appSettings section. We need to add a new variable named: SCM_DO_BUILD_DURING_DEPLOYMENT and set it to true. After adding the setting it should look like this (see the last one... that's our new one):


"appSettings": [
    {
    "name": "AzureWebJobsDashboard",
    "value": "[concat('DefaultEndpointsProtocol=https;AccountName=', variables('storageAccountName'), ';AccountKey=', listKeys(variables('storageAccountid'),'2015-05-01-preview').key1)]"
    },
    {
    "name": "AzureWebJobsStorage",
    "value": "[concat('DefaultEndpointsProtocol=https;AccountName=', variables('storageAccountName'), ';AccountKey=', listKeys(variables('storageAccountid'),'2015-05-01-preview').key1)]"
    },
    {
    "name": "WEBSITE_CONTENTAZUREFILECONNECTIONSTRING",
    "value": "[concat('DefaultEndpointsProtocol=https;AccountName=', variables('storageAccountName'), ';AccountKey=', listKeys(variables('storageAccountid'),'2015-05-01-preview').key1)]"
    },
    {
    "name": "WEBSITE_CONTENTSHARE",
    "value": "[toLower(variables('functionAppName'))]"
    },
    {
    "name": "FUNCTIONS_EXTENSION_VERSION",
    "value": "~1"
    },
    {
    "name": "WEBSITE_NODE_DEFAULT_VERSION",
    "value": "6.5.0"
    },
    {
    "name": "SCM_DO_BUILD_DURING_DEPLOYMENT",
    "value": true
    }
]

The Deployment Script


Now that all the pieces are ready it's time to put it together one script. In fact, only the two last commands are required; everything else is just stuff to make it easier to re-use it. Check out my previous post 5 Simple Steps to Get a Clean ARM Template, to learn more about the best practices related to ARM template. So let's see that script, it's pretty simple.

    # script to Create an Azure Gramophone-PoC Solution

    resourceGroupName=$1
    resourceGroupLocation=$2

    templateFilePath="./arm/azuredeploy.json"
    parameterFilePath="./arm/azuredeploy.parameters.json"

    dateToken=`date '+%Y%m%d%H%M'`
    deploymentName="FrankDemo"$dateToken

    # az login

    # You can select a specific subscription if you do not want to use the default
    # az account set -s SUBSCRIPTION_ID

    if !( $(az group exists -g  $resourceGroupName) ) then
        echo "---> Creating the Resourcegroup: " $resourceGroupName
        az group create -g $resourceGroupName -l $resourceGroupLocation
    else
        echo "---> Resourcegroup:" $resourceGroupName "already exists."
    fi

    az group deployment create --name $deploymentName --resource-group $resourceGroupName --template-file $templateFilePath --parameters $parameterFilePath --verbose

    echo "---> Deploying Function Code"
    az functionapp deployment source config-zip -g $resourceGroupName -n zipdeploydemo --src "./zip/AzFunction-ZipDeploy.zip"

    echo "---> done <--- code="">

The only "new" thing is the last command functionapp deployment source config-zip. That where we specify to the Azure Function App to look to --src to get our source. Because I'm running it locally, the path is pointing to a local folder. However, you could execute this command also in the CloudShell, and that would become a URI... to an Azure Blob Storage by example.

Deploy and Test


If you didn't notice yet, I did my script in bash and Azure CLI. That because I want my script to be compatible with all platforms. Of course, you could have done it in PowerShell or anything else that would call the REST API.

To deploy, just execute the script passing the ResourceGroup name, and its location.

    ./Deploy-AZ-Gramophone.sh cloud5mins eastus

ScriptOutputs

To get to Function URL, go to the Azure portal (portal.azure.com) and click on the Function App that we just deploy. Click on the function GetTopRunner in this case, and click on the </> Getfunction URL button.

GetFunctionURL

Use that URL in postman and pass another parameter top to see we the deployment ws successful.

postmanTest

In Video Please


If you prefer, I also have a video version of this post.



~Enjoy!

Reading Notes #329

IMG_20180527_154913

Suggestion of the week



Cloud



Programming



Books

jab_cover
Jab, Jab, Jab, Right Hook: How to Tell Your Story in a Noisy Social World (Gary Vaynerchuk) - Great book, for all of us you are trying to tell something, pass a message on the social media... This is a must.




Miscellaneous


Reading Notes #323

Suggestion of the week


Cloud


Programming


Miscellaneous


Databases


Books


This book doesn't age! 

This book may be old, but it's still incredibly true. I loved the way the reader was speaking and the rich vocabulary. It's definitely a must.

ASIN: B003WEAI4E







How to access an SQL Database from an Azure Function and Node.js

The other day, a friend asked me how he could add some functionality to an existing application without having access to the code. It the perfect case to demo some Azure Functions capability, so I jumped on the occasion. Because my friend is a Node.js developer on Linux, and I knew it was supported, I decided to try that combination. I know Node, but I'm definitely not and expert since I don't practice very often.

This post is my journey building that demo. I was out of my comfort zone, coding in Node and working on a Linux machine, but not that far... Because these days, you can "do some Azure" from anywhere.

The Goal


Coding an Azure Function that will connect to an SQL Database (it could be any data source). Using Node.js and tools available on Unbuntu.

Note: In this post, I will be using Visual Studio Code, but you could also create your function directly in the Azure Portal or from Visual Stusio.

Getting Started


If you are a regular reader of this blog, you know how I like Visual Studio Code. It's a great tool available on Mac Linux and Windows and gives you the opportunity to enjoy all its feature from anywhere feeling like if you were in your cozy and familiar environment. If VSCode is not already installed on your machine, go grap your free version on http://code.visualstudio.com.

Many extensions are available for VSCode, and one gives us the capability to code and deploy Azure Function. To install it, open VSCode and select the extension icon and search for Azure Function; it's the one with the yellow lighting and the blue angle brackets.

AzureFunctionExtension

Create the Azure Function


To get started let's great an Azure Function project. By sure to be in the folder where you wish to create your Function App. Open the Command Pallette (Ctrl + Shift + p) and type Azure Function. Select Azure Functions: Create New Project. That will add some configuration files for the Functions App.

Now Let's create a Function. You could reopen again the Command Palette and search for Azure Function: Create Function, but let's use the UI this time. At the bottom left of the Explorer section, you should see a new section called AZURE FUNCTIONS. Click on the little lighting to Create a new Function.

AzureFuncButton

After you specify the Function App name, the Azure subscription and other little essential, a new folder will be added in your folder structure, and the function is created. The code of our function is in the file Index.js. At the moment, of writing this post only Javascript is supported by the VSCode extension.

Open the file index.js and replace all its content by the following code.


var Connection = require('tedious').Connection;
var Request = require('tedious').Request
var TYPES = require('tedious').TYPES;

module.exports = function (context, myTimer) {

    var _currentData = {};

    var config = {
        userName: 'frankadmin',
        password: 'MyPassw0rd!',
        server: 'clouden5srv.database.windows.net',
        options: {encrypt: true, database: 'clouden5db'}
    };

    var connection = new Connection(config);
    connection.on('connect', function(err) {
        context.log("Connected");
        getPerformance();
    });

    function getPerformance() {

        request = new Request("SELECT 'Best' = MIN(FivekmTime), 'Average' = AVG(FivekmTime) FROM RunnerPerformance;", function(err) {
        if (err) {
            context.log(err);}
        });

        request.on('row', function(columns) {
            _currentData.Best = columns[0].value;
            _currentData.Average = columns[1].value;;
            context.log(_currentData);
        });

        request.on('requestCompleted', function () {
            saveStatistic();
        });
        connection.execSql(request);
    }


    function saveStatistic() {

        request = new Request("UPDATE Statistic SET BestTime=@best, AverageTime=@average;", function(err) {
         if (err) {
            context.log(err);}
        });
        request.addParameter('best', TYPES.Int, _currentData.Best);
        request.addParameter('average', TYPES.Int, _currentData.Average);
        request.on('row', function(columns) {
            columns.forEach(function(column) {
              if (column.value === null) {
                context.log('NULL');
              } else {
                context.log("Statistic Updated.");
              }
            });
        });

        connection.execSql(request);
    }

    context.done();
};

The code just to demonstrate how to connect to an SQL Database and do not represent the best practices. At the top, we have some declaration the used the package tedious; I will get back to that later. A that, I've created a connection using the configuration declared just before. Then we hook some function to some event. On connection connect the function getPerformance() is called to fetch the data.

On request row event we grab the data and do the "math", then finally on requestCompleted we call the second sub-function that will update the database with the new value. To get more information and see more example about tedious, check the GitHub repository.

Publish to Azure


All the code is ready; it's now time to publish our function to Azure. One more time you could to that by the Command Palette, or the Extension menu. Use the method of your choice and select Deploy to Function App. After a few seconds only our Function will be deployed in Azure.

Navigate to portal.azure.com and get to your Function App. If you try to Run the Function right now, you will get an error because tedious is not recognized.

Install the dependencies


We need to install the dependencies for the Function App, in this case tedious. A very simple way is to create a package.json file and to use the Kudu console ton install it. Create a package.json file with the following json in it:


{
    "name": "CloudEn5Minutes",
    "version": "1.0.0",
    "description": "Connect to Database",
    "repository": {
       "type": "git",
       "url": "git+https://github.com/fboucher/CloudEn5Minutes.git"
    },
    "author": "",
    "license": "ISC",
    "dependencies": {
        "tedious": "^2.1.1"
    }
}

Open the Kudu interface. You can reach it by clicking on the Function App then the tab Platform features and finally Advanced tools (Kudu). Kudu is also available directly by the URL [FunctionAppNAme].scm.azurewebsites.net (ex: https://clouden5minutes.scm.azurewebsites.net ). Select the Debug console CMD. Than in the top section navigate to the folder home\site\wwwroot. Drag & drop the package.json file. Once the file is uploaded, type the command npm install to download and install all the dependencies declared in our file. Once it all done you should restart the Function App.

Kudu

Wrapping up & my thoughts


There it is, if you go back now to your Function and try to execute it will work perfectly. It's true that I'm familiar with Azure Function and SQL Database. However, for a first experience using Ubuntu and Node.js in the mix, I was expecting more resistance. One more time VSCode was really useful and everything was done with ease.

For those of you that would like to test this exact function, here the SQL code to generate what will be required for the database side.


    CREATE TABLE RunnerPerformance(
        Id           INT IDENTITY(1,1)  PRIMARY KEY,
        FivekmTime   INT
    );

    CREATE TABLE Statistic(
        Id          INT IDENTITY(1,1)  PRIMARY KEY,
        BestTime    INT,
        AverageTime INT
    );

    INSERT Statistic (BestTime, AverageTime) VALUES (1, 1);

    DECLARE @cnt INT = 0;

    WHILE @cnt < 10
    BEGIN
    INSERT INTO RunnerPerformance (FivekmTime)
            SELECT  9+FLOOR((50-9+1)*RAND(CONVERT(VARBINARY,NEWID())));
    SET @cnt = @cnt + 1;
    END;

Video version



References


Reading Notes #297

Jekyll_AppService

Suggestion of the week

  • How to uninstall Scrum (Erwin Verweij) - When you will read that post (because you must read it... Seriously), you will smile, giggle and maybe even laugh.


Cloud


Programming


Miscellaneous





Reading Notes #294

MagPi60-Cover

Suggestion of the week


Cloud


Programming


Miscellaneous



Reading Notes #293

IMG_20170813_103816-EFFECTSCloud


Programming




Reading Notes #292

cloudheight


Suggestion of the week


Cloud


Programming


Databases


Miscellaneous



Reading Notes #285

IMG_20170614_194330Cloud

Programming

Suggestion of the week

Miscellaneous