Create and Deploy a Blob Trigger Azure Function

To create a blob trigger Azure Function, you'll first need to create a new Azure Function project in Visual Studio. This will set up the basic structure for your function.

The blob trigger Azure Function is a serverless compute service that allows you to run code on-demand in response to changes to a blob in Azure Storage.

To deploy a blob trigger Azure Function, you'll need to create a new Azure Storage account and upload a sample blob to test the trigger.

The Azure Function runtime will automatically detect changes to the blob and execute the trigger function.

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Before you start building your blob trigger Azure function, you'll need to make sure you have the right tools and accounts in place. To get started, you'll need an Azure account with an active subscription. You can create one for free.

You'll also need to have the right software installed on your computer. This includes the .NET 8.0 SDK, Node.js 14.x or above, PowerShell 7.2, or the Java Development Kit, version 8, 11, 17 or 21(Linux). Make sure you're using the correct version of your chosen software, as using an outdated version may cause issues.

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For development, you'll need a code editor like Visual Studio Code on one of the supported platforms. You'll also need to install the C# extension for Visual Studio Code if you're using .NET, or the Python extension if you're using Python. Additionally, you'll need the Azure Functions extension for Visual Studio Code, which will install Azure Functions Core Tools for you the first time you locally run your functions.

Here's a breakdown of the specific tools and software you'll need for each programming language:

Remember, deploying to an existing function app will always overwrite the contents of that app in Azure.

To configure a blob trigger Azure function, you need to understand the properties that can be set on the options object passed to the app.storageBlob() method.

The path property specifies the container to monitor, which can be a blob name pattern. This is crucial in determining which blobs will trigger the function.

You can also set the connection property, which is the name of an app setting or setting collection that specifies how to connect to Azure Blobs. This is essential for connecting to your Azure Blob storage.

The source property sets the source of the triggering event, and you can use EventGrid for an Event Grid-based blob trigger, which provides much lower latency. The default is LogsAndContainerScan, which uses the standard polling mechanism to detect changes in the container.

Here's a summary of the properties you can set:

In the function.json file, you'll also need to configure the binding, which involves setting the type, direction, name, path, connection, and source properties.

To set up a blob trigger in Azure Functions, you'll need to choose the right binding type. The binding types supported by blob trigger depend on the extension package version and the C# modality used in your function app.

You can choose from string, byte[], JSON serializable types, Stream, or BlobClient, BlockBlobClient, PageBlobClient, AppendBlobClient, and BlobBaseClient.

For small blob sizes, binding to string or byte[] is recommended, but for most blobs, use a Stream or BlobClient type to avoid loading the entire contents into memory.

To use these types, you need to reference Microsoft.Azure.Functions.Worker.Extensions.Storage.Blobs 6.0.0 or later and the common dependencies for SDK type bindings.

Here are the supported types:

If you get an error message when trying to bind to one of the Storage SDK types, make sure that you have a reference to the correct Storage SDK version.

You can also use the StorageAccountAttribute to specify the storage account to use. This attribute can be applied at the parameter, method, or class level.

Function Development is a crucial aspect of creating an Azure Blob Trigger Function.

You can develop a function in C#, JavaScript, or Python, which are all supported languages by Azure Functions.

Developing a function in C# allows for the use of .NET Core and other .NET libraries, making it a popular choice for many developers.

Annotations are a crucial part of function development, allowing you to access the blob that triggered the function.

The @BlobTrigger attribute is used to give you access to the blob that triggered the function.

You can use the source property to set the source of the triggering event, and consider using EventGrid for an Event Grid-based blob trigger, which provides much lower latency.

The default setting is LogsAndContainerScan, which uses the standard polling mechanism to detect changes in the container.

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You can create a function that runs in an isolated worker process and uses a blob trigger with both blob input and blob output blob bindings.

These types of functions are triggered by the creation of a blob in a specified container, such as the test-samples-trigger container.

The function reads a text file from the test-samples-input container and creates a new text file in an output container based on the name of the triggered file.

Expand your knowledge: Azure Function Container

You can also use a string in the blob trigger path, such as {name}, to create a binding expression that you can use in function code to access the file name of the triggering blob.

This is useful for accessing the file name of the triggering blob in your function code.

In C# functions, you can use the string {name} in the blob trigger path to create a binding expression that you can use in function code to access the file name of the triggering blob.

For example, the string {name} in the blob trigger path samples-workitems/{name} creates a binding expression that you can use in function code to access the file name of the triggering blob.

You can use SDK types to directly access the underlying BlobClient object provided by the Blob storage trigger in your function code.

This is demonstrated in an example that uses the SDK types to directly access the underlying BlobClient object provided by the Blob storage trigger.

In addition, you can use a function.json file to configure your function and include a binding with the type of blobTrigger and direction set to in.

This is shown in an example that demonstrates how to create a function that runs when a file is added to source blob storage container.

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Reviewing the code generated for your EventGridBlobTrigger function is a great way to understand how it works.

In the generated code, you'll see a definition for the EventGridBlobTrigger function that indicates the source of the event that starts the trigger.

For example, in the EventGridBlobTrigger.cs file, you'll see Source = BlobTriggerSource.EventGrid, which means an event subscription to the blob container is used as the source of the event.

Similarly, in the EventGridBlobTrigger.java file, you'll see source = EventGrid, indicating an event subscription to the samples-workitems blob container is used as the source of the event.

In the function.json file, you'll find a binding definition with a type of blobTrigger and a source of EventGrid, which also points to the samples-workitems blob container as the source of the event.

In the EventGridBlobTrigger.js file, you'll see a definition for a function with a source of EventGrid, indicating an event subscription to the samples-workitems blob container is used as the source of the event.

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In the EventGridBlobTrigger.ts file, you'll see a definition for a function with a source of EventGrid, indicating an event subscription to the samples-workitems blob container is used as the source of the event.

To ensure your host.json project file is up to date, review the extensionBundle element and check if extensionBundle.version is at least 3.3.0.

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To emulate Azure Storage services locally, you can use Azurite in Visual Studio Code. Install the Azurite v3 extension for Visual Studio Code.

Verify that the local.settings.json file has "UseDevelopmentStorage=true" set for AzureWebJobsStorage, which tells Core Tools to use Azurite instead of a real storage account connection when running locally.

Press F1 to open the command palette, type Azurite: Start Blob Service, and press enter, which starts the Azurite Blob Storage service emulator.

To create a blob container, select the Azure icon in the Activity bar, expand Workspace > Attached Storage Accounts > Local Emulator, right-click Blob Containers, select Create Blob Container..., enter the name samples-workitems, and press Enter.

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Choose a file to upload to the locally emulated container, such as a text file, which gets processed later by your function to verify and debug your function code.

Here's a step-by-step guide to setting up local storage emulation:

Deployment is a crucial step in creating a blob trigger Azure function. You'll need to deploy your function code to a function app.

To deploy your function code, first enter and select Azure Functions: Deploy to Function App in the command palette. This will allow you to select the function app you just created.

Next, select the function app you just created when prompted about overwriting previous deployments, and then select Deploy to deploy your function code to the new function app resource.

After deployment is completed, you can view the creation and deployment results, including the Azure resources that you created, by selecting View Output. If you miss the notification, you can also select the bell icon in the lower-right corner to see it again.

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Here's a step-by-step list to help you deploy your function code:

To deploy your code, you'll need to follow a few steps in the command palette. Enter Azure Functions: Deploy to Function App and select the function app you just created.

You'll be prompted about overwriting previous deployments, so select Deploy to deploy your code to the new function app resource. This is a crucial step, as it will update your function app with the latest changes.

When deployment is completed, select View Output to see the creation and deployment results, including the Azure resources you've created. Don't worry if you miss the notification – just click the bell icon in the lower-right corner to see it again.

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To test your blob trigger Azure function, you can follow these steps. In a new browser window, return to your function app page and select Log stream, which displays real-time logging for your app. This will allow you to see the function in action.

Select Upload > Browse for files from the samples-workitems container page and choose a file from your local computer, such as an image file. Then select Open and upload the file.

Note that there may be a delay of up to several minutes between the blob being added or updated and the function being triggered, especially if your function app runs in the default Consumption plan.

You can verify the function by checking the Azure portal. Go to the Events page in your storage account and select Event Subscriptions. You should see that an event was delivered, although there might be up to a five-minute delay for the event to show up on the chart.

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Connections in Azure Blob trigger functions are crucial for establishing a connection to Azure Blobs. The connection property is a reference to environment configuration that specifies how the app should connect to Azure Blobs.

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A connection can be specified by the name of an application setting containing a connection string or by a shared prefix for multiple application settings, defining an identity-based connection. If a configured value is both an exact match for a single setting and a prefix match for other settings, the exact match is used.

Stream binding is used in the standard Visual Studio Azure Functions template for blob-triggered functions, applicable for both In-process and Isolated Azure Functions models.

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Metadata is a treasure trove of information that can be accessed through the blob trigger. It provides several metadata properties that can be used in binding expressions or as parameters in your code.

These properties have the same semantics as the CloudBlob type and can be accessed through the bindingData property of the supplied context object. The blobTrigger property, for example, contains the path to the triggering blob.

The blob trigger also provides a Uri property, which is the blob's URI for the primary location. This can be useful for accessing the blob's location.

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The properties property contains the blob's system properties, while the metadata property contains the user-defined metadata for the blob. This can be accessed through the $TriggerMetadata parameter.

Here are the metadata properties available through the blob trigger:

Metadata can be obtained from the triggerMetadata property of the supplied context object, as shown in the following example, which logs the path to the triggering blob.

You can filter on blob names to trigger your Azure Functions on specific files. A container name can't contain a resolver in the name pattern.

To filter on blob names, you can specify a blob name pattern in the path property in function.json or in the BlobTrigger attribute constructor. The name pattern can be a filter or binding expression.

You can use a name pattern to trigger only on blobs in the input container that start with a specific string, like "original-". If the blob name is original-Blob1.txt, the value of the name variable in function code is Blob1.txt.

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Stream binding is actually the default in the standard Visual Studio Azure Functions template for blob-triggered functions, regardless of whether you're using the In-process or Isolated model.

This means that if you're creating a new blob-triggered function, you're likely using stream binding by default. In fact, the standard template uses stream binding for both Azure Functions models.

The blob trigger in Azure Functions internally uses queues, and there's a limit of 24 concurrent function invocations, which applies separately to each function that uses a blob trigger. This limit can impact performance if you're handling large numbers of blobs or very large blobs.

The Consumption plan also limits a function app to 1.5 GB of memory at max, shared among all functions within the Function App. If a blob-triggered function loads the entire blob into memory, the maximum memory used by that function just for blobs is 24 times the maximum blob size.

The connection property is a crucial part of Azure Blobs configuration, specifying how your app should connect to the service.

It can reference an application setting containing a connection string, which is a key piece of information for establishing a connection.

This connection string can be used to connect to Azure Blobs, making it a vital part of your app's configuration.

The configured value can be either an exact match for a single setting or a prefix match for multiple settings, defining an identity-based connection.

If there's an exact match for a single setting and a prefix match for other settings, the exact match is used.

Here are the ways the connection property can be configured:

If you're experiencing issues with your blob trigger Azure function, start by checking the storage account connection string. Make sure it's correct and properly configured.

A common mistake is setting the wrong storage account or container name, which can cause the function to fail.

Ensure the blob is in the correct container and has the correct name as specified in the function's configuration.

The function's timeout setting can also cause issues if it's set too low.

If you're using a premium storage account, be aware that it has a different pricing model than standard storage.

A timeout error can also occur if the function is waiting for a long time to process the blob.

Check the function's logs to see if there are any error messages indicating the issue.

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Now that you've set up a blob trigger Azure function, it's time to take it to the next level.

Automating tasks is where the magic happens, and you can start by working with blobs. This means you can store and retrieve data in a structured way, making it easier to manage your application's data.

You can automate resizing uploaded images using Event Grid, which is a great way to streamline your workflow. With Event Grid, you can trigger actions based on specific events, such as when a new image is uploaded.

Here are some next steps to consider: