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Azure Azure Functions

Using Azure Functions with Rider

Previously we’ve written about how to get started with Azure Functions using JetBrains Rider – but that’s now an outdated article, as the Azure plugin now offers seamless integration with the Microsoft Functions tooling. Gone are the days of manually updating project configuration files.

What you’ll need

In order to follow along, you’ll need to make sure you:

Getting started

First you’ll want to install the Azure Toolkit for Rider. Open Rider then navigate to Preferences (JetBrains Rider > Preferences on a Mac) and Plugins.

In the Plugins screen, go to the Marketplace tab  and search for “Azure Toolkit for Rider”. Click install.

This will now allow you to manage and deploy a whole bunch of Azure services from within Rider, such as App Services and SQL databases.

Let’s open a new Functions app. Now that you’ve installed the Azure Toolkit, a new template for AzureFunctions has been added to your new project window. From within Rider, click File > New and choose Azure Functions from underneath the .NET Core section.

Enter a solution name, project name and choose a directory and language, and then click Create. If you’re using this as a test project, you can probably leave these values as is.

Running the Functions app

And that’s almost all there is to using Functions apps in Rider now! The toolkit will automatically detect that it’s a function app, and provide the necessary scaffolding to allow you to run and debug the app.

Gone are the days of hacking the project settings and configuration to make it work – it’s a seamless experience now.

To verify that the config is correct, click the run configuration in the top right-hand side of Rider, and edit the configurations. You should see a default Azure Functions host configuration, complete with all the settings required to run a functions app. You can see in this example that the function will run on port 7071, and pause on error.

Even better, is that if you don’t have the required Functions command line tools to run the app (which Rider relies on behind the scenes) then you’ll even get prompted to install them – which Rider will do automatically on your behalf. You’ll also get prompted if your tools are out of date.

And that’s how easy it is now to get started using Azure Functions in Rider!

Categories
Azure Azure Functions

Building Azure Functions in the Rider IDE

Many people now use Rider as their integrated development environment editor for .NET. However, when it comes to using it for developing Azure Functions, the out-of-the-box experience is (currently) less than ideal.

I say currently, because in the next update to the Azure Toolkit plugin for Rider Functions support has been added. This’ll make running and debugging function apps a breeze.

Until then though, here’s how you can run a functions app from Rider.

How to run Azure functions in Rider

First, you’ll need to install the function CLI (see creating an Azure function for the Mac).

Then, open your functions app in Rider by selecting the project or solution.

Create a Properties folder in the root directory if you don’t have one already, and then inside of that create a new JSON file called launchSettings.json.

Inside the JSON file, place the following object:

{  "profiles": {    "functions": {      "commandName": "Executable",      "executablePath": "func",      "commandLineArgs": "start --port 7071 --pause-on-error"    }  }}

You should see Rider now refresh, and add the configuration profile to your configurations with a little rocket icon. Click run, and your function app should start running within Rider.

Note that debugging is a little tricker for now. On Windows, once your function app is running you can go “Run” > “Attach to process” and choose your function app to listen to. But on a Mac, this has had mixed results.

Categories
Azure

Azure App Configuration vs App Settings

For a long time now, App Settings have been the way to configure your app’s settings such as environment variables and connection strings for Azure App Services.

In February 2019, Microsoft announced a new service called App Configuration – which, currently in preview – allows you to easily centralise your app settings across multiple resources.

Want to secure your Azure DevOps application secrets in Key Vault? Find out how in  our short e-book guide on Amazon

Why is App Settings a problem?

App Settings are great – if you only need those settings for one resource (eg. an app service). But if you’re working with, say, a microservice that might be made up of many resources including an app service and maybe a functions app that all share similar configurations, keeping track of what settings were made where can quickly become problematic.

Amongst other things, there’s no easy way to do things like point-in-time replays of settings, so you can see what changed or keep the settings the same if you need to rebuild or deploy a specific version of your app.

What does App Configuration offer that App Settings doesn’t?

App Configuration is a fully managed service that offers the ability to store all your app configuration values in one location, with the ability to compare settings at specific times and with specific labels.

Operating in a similar fashion to Key Vault, it’s a separate resource from your app service (although you can configure it immediately by going to the new preview tab in your app services), and there are a number of SDKs available to integrate with it for .NET core,  .NET and Java.

You can think of App Configuration as a counterpart to Key Vault for properties that don’t need to be stored as secrets. Connection strings would likely still go in Key Vault, but properties that aren’t secrets should be stored in App Configuration.

First you’ll need to setup a connection string which you can find under the “Settings” → “Access Keys” section of your App Configuration resource. Then, within App Configuration, you set a number of key value pairs, which you can then access in a similar fashion to the way you get environment variables in App Settings:

var configBuilder = new ConfigurationBuilder();configBuilder.AddAzureAppConfiguration(Environment.GetEnvironmentVariable("YourKeyNameFromAppConfiguration"));var config = configBuilder.Build();

You can also import and export settings easily, and can use JSON, YAML or a Properties file. You can also export the settings for a specific time and date.

At present, because the service is in preview there are no additional charges. Microsoft hasn’t yet stated its intentions for charging for this service, but given the similarities with Key Vault (which is a paid service) it’s easy to see how a similar model could apply if they decided.

Categories
Azure Azure Functions

Which Azure Functions runtime am I using?

Microsoft currently support two versions of the Azure Functions runtime – version 1 and version 2. This post will look at the main changes between the two versions, and show you how you can check which runtime you’re using.

What are the key differences between versions?

Version 1 of the runtime was introduced back in 2016, when functions were first announced. At launch it supported JavaScript, C#, Python and PHP.

In late September 2018 Microsoft made the Functions 2 runtime generally available and with it bought a number of significant development, deployment and performance improvements including the ability to use the runtime anywhere – on a Mac or Linux machine too! It’s worth noting that as of March 2019, Python support for Functions 2 is still in preview.

There were significant under the hood changes made to improve performance – and .NET Core 2.1 support was added, alongside a move to .NET Core powering the functions host process instead of .NET.

Big changes were made to the way that bindings work – as part of 2.0 they became extensions instead of being bundled into the runtime itself (aside from HTTP and timer support which are deemed core to the experience). This means that some bindings didn’t make it over yet to the new 2.0 runtime – your mileage may vary, but the Microsoft bindings docs have a clearer comparison between the two.

There are also a bunch of new integrations with Functions 2 – for instance, Application Insights is supported with minimal configuration required, while you can easily use deployment centre to add code from other sources such as Github repos into your functions app.

How can I tell what runtime I’m using?

If you’re running a functions app on a Mac or Linux machine – there’s a fair chance you’re using the 2.0 runtime, as that’s what the functions command line tools support. You can verify this by opening the host.json file within the root directory of your app, which should look something like this:

{    "version": "2.0",    "extensions": {      "http": {        "routePrefix": ""      }    } }

The version field directly references the version of the functions runtime you’re using. If it says 2.0, you’re using version 2 – if it’s 1 or missing completely, you’re on the first version of the runtime.

Similarly, you can also view the runtime for your app through the Azure Portal – open your app in the portal, then navigate to “Function app settings” where you’ll see the below “Runtime version” setting.

Categories
Azure Azure Functions

Azure Functions App vs Functions

A common question asked by newcomers to the world of Azure Functions, is what’s the difference between an Azure functions app vs a function? Are they the same thing?

In short, there is a difference. You can think of the functions app as if it refers to a workspace that contains one or more functions. It’s essentially a wrapper (or in .NET terms, project), holding all your Azure functions in one place and allowing for easy deployment and management of them as one.

On the other hand, a function refers to a single, isolated piece of functionality. Typically in .NET this results in a class that performs one discrete piece of behaviour.

There are a number of ramifications for function apps that don’t apply to individual functions. For instance, it’s at the function app level that the pricing plan, runtime version and more are set in Azure. Microsoft refers to this as providing the execution context for your functions.

So keep in mind that when you first create a function resource in the Azure Portal, you’re creating a functions app. Once you navigate inside that resource, you can then start to add individual functions.

Categories
Azure

What’s an Azure Service Principal and Managed Identity?

In this post, we’ll take a brief look at the difference between an Azure service principal and a managed identity (formerly referred to as a Managed Service Identity or MSI).

What is a service principal or managed service identity?

Lets get the basics out of the way first. In short, a service principal can be defined as:

An application whose tokens can be used to authenticate and grant access to specific Azure resources from a user-app, service or automation tool, when an organisation is using Azure Active Directory.

In essence, service principals help us avoid having to create fake users in Active Directory in order to manage authentication when we need to access Azure resources.

Stepping back a bit, and its important to remember that service principals are defined on a per-tenant basis. This is different to the application in which principals are created – the application sits across every tenant.

Managed identities are often spoken about when talking about service principals, and that’s because its now the preferred approach to managing identities for apps and automation access. In effect, a managed identity is a layer on top of a service principal, removing the need for you to manually create and manage service principals directly.

There are two types of managed identities:

  • System-assigned: These identities are tied directly to a resource, and abide by that resources’ lifecycle. For instance, if that resource is deleted then the identity too will be removed
  • User-assigned: These identities are created independent of a resource, and as such can be used between different resources. Removing them is a manual process whenever you see fit

One of the problems with managed identities is that for now only a limited subset of Azure services support using them as an authentication mechanism. If the service you use doesn’t support MI, then you’ll need to either continue to manually create your service/security principals.

So what’s the difference?

Put simply, the difference between a managed identity and a service principal is that a managed identity manages the creation and automatic renewal of a service principal on your behalf.

Update 31/1/20: If you’re using Azure Web Apps, check out our new post on using managed identities with deployment slots