How to Use IronWord on AWS Lambda

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This article provides a comprehensive guide to setting up an AWS Lambda function using IronWord. You will learn how to configure IronWord to create and manipulate Word documents within an AWS Lambda environment.

Installation

Since this example will read/write Word documents to an S3 bucket, the AWSSDK.S3 NuGet package is required.

Using IronWord ZIP Package on AWS Lambda

When using the IronWord ZIP package, it’s important to set a temporary deployment path because AWS Lambda has a read-only filesystem except for the /tmp/ folder. You must configure IronWord to use this folder for its runtime files:

var awsTmpPath = @"/tmp/";
IronSoftware.Word.Installation.DeploymentPath = awsTmpPath;
var awsTmpPath = @"/tmp/";
IronSoftware.Word.Installation.DeploymentPath = awsTmpPath;
Dim awsTmpPath = "/tmp/"
IronSoftware.Word.Installation.DeploymentPath = awsTmpPath
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Integrating IronWord with AWS

Create an AWS Lambda Project

Use Visual Studio to create a containerized AWS Lambda project:

  1. Install the AWS Toolkit for Visual Studio
  2. Select AWS Lambda Project (.NET Core - C#)
  3. Choose the .NET 8 (Container Image) blueprint and finish the setup
  4. Select container image as the deployment type

Add Package Dependencies

Add IronWord and AWSSDK.S3 packages to your project via NuGet. The IronWord library works smoothly on AWS Lambda with the correct setup. Run the following command to install IronWord to your AWS project seamlessly:

Install-Package IronWord

Update your project's Dockerfile to use the .NET 8 Lambda base image and copy your build artifacts:

FROM public.ecr.aws/lambda/dotnet:8

RUN dnf update -y

WORKDIR /var/task

COPY "bin/Release/lambda-publish"  .

Modify the FunctionHandler Code

Below is an example Lambda function that creates a simple Word document, saves it as a .docx file, and uploads it to an S3 bucket.

using Amazon.Lambda.Core;
using Amazon.S3;
using Amazon.S3.Model;
using IronWord;
using IronWord.Models;
using System.Text;

// Assembly attribute to enable the Lambda function's JSON input to be converted into a .NET class.
[assembly: LambdaSerializer(typeof(Amazon.Lambda.Serialization.SystemTextJson.DefaultLambdaJsonSerializer))]

namespace IronWordAwsLambda;

public class Function
{
    private static readonly IAmazonS3 _s3Client = new AmazonS3Client(Amazon.RegionEndpoint.APSoutheast1);

    public async Task FunctionHandler(ILambdaContext context)
    {
        var awsTmpPath = @"/tmp/";
        License.LicenseKey = "YOUR-LICENSE-KEY"; // Replace if you have one

        string filename = Guid.NewGuid() + ".docx";
        string localPath = Path.Combine(awsTmpPath, filename);
        string bucketName = "your-s3-bucket-name";
        string objectKey = $"IronWordAwsLambda/{filename}";

        try
        {
            // Create Word Document
            var doc = new WordDocument();
            Paragraph paragraph = new Paragraph(new TextContent("Hello from IronWord on AWS Lambda!"));
            doc.AddParagraph(paragraph);
            doc.SaveAs(localPath);

            context.Logger.LogLine("Word document created.");

            // Upload to S3
            byte[] fileBytes = await File.ReadAllBytesAsync(localPath);
            await UploadToS3Async(bucketName, objectKey, fileBytes);

            context.Logger.LogLine($"Document uploaded to S3: {bucketName}/{objectKey}");
        }
        catch (Exception ex)
        {
            context.Logger.LogLine($"[ERROR] {ex.Message}");
        }
    }

    private async Task UploadToS3Async(string bucketName, string objectKey, byte[] fileBytes)
    {
        using var stream = new MemoryStream(fileBytes);
        var request = new PutObjectRequest
        {
            BucketName = bucketName,
            Key = objectKey,
            InputStream = stream,
            ContentType = "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
        };
        await _s3Client.PutObjectAsync(request);
    }
}
using Amazon.Lambda.Core;
using Amazon.S3;
using Amazon.S3.Model;
using IronWord;
using IronWord.Models;
using System.Text;

// Assembly attribute to enable the Lambda function's JSON input to be converted into a .NET class.
[assembly: LambdaSerializer(typeof(Amazon.Lambda.Serialization.SystemTextJson.DefaultLambdaJsonSerializer))]

namespace IronWordAwsLambda;

public class Function
{
    private static readonly IAmazonS3 _s3Client = new AmazonS3Client(Amazon.RegionEndpoint.APSoutheast1);

    public async Task FunctionHandler(ILambdaContext context)
    {
        var awsTmpPath = @"/tmp/";
        License.LicenseKey = "YOUR-LICENSE-KEY"; // Replace if you have one

        string filename = Guid.NewGuid() + ".docx";
        string localPath = Path.Combine(awsTmpPath, filename);
        string bucketName = "your-s3-bucket-name";
        string objectKey = $"IronWordAwsLambda/{filename}";

        try
        {
            // Create Word Document
            var doc = new WordDocument();
            Paragraph paragraph = new Paragraph(new TextContent("Hello from IronWord on AWS Lambda!"));
            doc.AddParagraph(paragraph);
            doc.SaveAs(localPath);

            context.Logger.LogLine("Word document created.");

            // Upload to S3
            byte[] fileBytes = await File.ReadAllBytesAsync(localPath);
            await UploadToS3Async(bucketName, objectKey, fileBytes);

            context.Logger.LogLine($"Document uploaded to S3: {bucketName}/{objectKey}");
        }
        catch (Exception ex)
        {
            context.Logger.LogLine($"[ERROR] {ex.Message}");
        }
    }

    private async Task UploadToS3Async(string bucketName, string objectKey, byte[] fileBytes)
    {
        using var stream = new MemoryStream(fileBytes);
        var request = new PutObjectRequest
        {
            BucketName = bucketName,
            Key = objectKey,
            InputStream = stream,
            ContentType = "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
        };
        await _s3Client.PutObjectAsync(request);
    }
}
Imports Amazon.Lambda.Core
Imports Amazon.S3
Imports Amazon.S3.Model
Imports IronWord
Imports IronWord.Models
Imports System.Text

' Assembly attribute to enable the Lambda function's JSON input to be converted into a .NET class.
<Assembly: LambdaSerializer(GetType(Amazon.Lambda.Serialization.SystemTextJson.DefaultLambdaJsonSerializer))>

Namespace IronWordAwsLambda

	Public Class [Function]
		Private Shared ReadOnly _s3Client As IAmazonS3 = New AmazonS3Client(Amazon.RegionEndpoint.APSoutheast1)

		Public Async Function FunctionHandler(ByVal context As ILambdaContext) As Task
			Dim awsTmpPath = "/tmp/"
			License.LicenseKey = "YOUR-LICENSE-KEY" ' Replace if you have one

			Dim filename As String = Guid.NewGuid().ToString() & ".docx"
			Dim localPath As String = Path.Combine(awsTmpPath, filename)
			Dim bucketName As String = "your-s3-bucket-name"
			Dim objectKey As String = $"IronWordAwsLambda/{filename}"

			Try
				' Create Word Document
				Dim doc = New WordDocument()
				Dim paragraph As New Paragraph(New TextContent("Hello from IronWord on AWS Lambda!"))
				doc.AddParagraph(paragraph)
				doc.SaveAs(localPath)

				context.Logger.LogLine("Word document created.")

				' Upload to S3
				Dim fileBytes() As Byte = Await File.ReadAllBytesAsync(localPath)
				Await UploadToS3Async(bucketName, objectKey, fileBytes)

				context.Logger.LogLine($"Document uploaded to S3: {bucketName}/{objectKey}")
			Catch ex As Exception
				context.Logger.LogLine($"[ERROR] {ex.Message}")
			End Try
		End Function

		Private Async Function UploadToS3Async(ByVal bucketName As String, ByVal objectKey As String, ByVal fileBytes() As Byte) As Task
			Dim stream = New MemoryStream(fileBytes)
			Dim request = New PutObjectRequest With {
				.BucketName = bucketName,
				.Key = objectKey,
				.InputStream = stream,
				.ContentType = "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
			}
			Await _s3Client.PutObjectAsync(request)
		End Function
	End Class
End Namespace
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Increase Memory and Timeout

Since document processing can be memory-intensive, increase your Lambda function memory to at least 512 MB and timeout to 300 seconds in aws-lambda-tools-defaults.json:

{
  "function-memory-size": 512,
  "function-timeout": 300
}

If you encounter errors like Runtime exited with error: signal: killed, increase memory or optimize your code.

Publish

To publish your Lambda function:

  • Right-click your project in Visual Studio
  • Select Publish to AWS Lambda...
  • Follow the wizard and configure settings as needed

Try It Out!

Invoke the Lambda function through the AWS Lambda Console or Visual Studio. After execution, check your S3 bucket for the newly created Word document.

Preguntas Frecuentes

¿Qué es IronWord y cómo puede mejorar el procesamiento de documentos Word en AWS Lambda?

IronWord es una herramienta poderosa para procesar documentos Word, y cuando se integra con AWS Lambda, ofrece gestión de documentos escalable y eficiente, permitiéndole automatizar y simplificar las tareas de documentos Word.

¿Cómo integro IronWord con AWS Lambda?

Para integrar IronWord con AWS Lambda, necesita configurar el paquete de IronWord en su entorno de AWS Lambda, configurar los permisos necesarios y desplegar su código de función que utiliza las características de IronWord para el procesamiento de documentos.

¿Cuáles son los beneficios de usar IronWord en AWS Lambda?

El uso de IronWord en AWS Lambda le permite aprovechar la arquitectura sin servidor para el procesamiento de documentos Word, proporcionando escalabilidad, rentabilidad y una reducción en la gestión de infraestructura.

¿Puedo automatizar tareas de documentos Word usando IronWord en AWS Lambda?

Sí, puede automatizar varias tareas de documentos Word, como la creación, modificación y conversión utilizando IronWord en funciones de AWS Lambda.

¿Es posible manejar documentos Word grandes con IronWord en AWS Lambda?

IronWord está diseñado para manejar eficientemente documentos Word grandes, y cuando se usa con AWS Lambda, puede procesar documentos de manera escalable, dependiendo de su configuración de Lambda.

¿Qué tipo de operaciones en documentos Word puede realizar IronWord en AWS Lambda?

IronWord puede realizar una variedad de operaciones en documentos Word, incluyendo edición, formateo, extracción de texto y conversión de documentos a diferentes formatos, todo dentro de un entorno de AWS Lambda.

¿Existen requisitos previos para desplegar IronWord en AWS Lambda?

Antes de desplegar IronWord en AWS Lambda, asegúrese de tener una cuenta de AWS, familiaridad con la configuración de AWS Lambda y cualquier rol y permiso de IAM necesario configurado.

¿Cómo maneja IronWord las actualizaciones y el mantenimiento en AWS Lambda?

IronWord se actualiza regularmente para asegurar mejoras de compatibilidad y rendimiento. En un entorno de AWS Lambda, puede actualizar fácilmente su paquete de despliegue con la última versión de IronWord para mantener una funcionalidad óptima.

¿Qué soporte está disponible para usar IronWord con AWS Lambda?

Iron Software proporciona documentación y soporte para ayudar a los usuarios a integrar y usar IronWord en AWS Lambda, asegurando que pueda utilizar eficazmente sus capacidades para sus necesidades de procesamiento de documentos.

Kye Stuart
Escritor Técnico

Kye Stuart fusiona la pasión por la codificación y la habilidad para escribir en Iron Software. Educado en Yoobee College en despliegue de software, ahora transforma conceptos tecnológicos complejos en contenido educativo claro. Kye valora el aprendizaje continuo y acepta nuevos desafíos tecnológicos.

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