AWS, AWS Certification

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Exploring Sensational AWS and .NET SDK in Visual Studio Code

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The AWS .NET SDK (Software Development Kit) is a collection of libraries, tools, and resources provided by Amazon Web Services (AWS) to help .NET developers build applications that interact with AWS services. The SDK enables developers to integrate AWS functionality seamlessly into their .NET applications, allowing them to leverage a wide range of cloud services offered by AWS. AWS provides tools and extensions for popular IDEs like Visual Studio, making it easier for developers to integrate AWS services seamlessly into their development workflow.

Installing and configuring AWS credentials in Visual Studio Code

To utilize the AWS SDK for .NET within Visual Studio Code, you can proceed as follows:

  1. Install Visual Studio Code: If you haven’t installed it, first install the Visual Studio Code from this URL:
  2. Install .NET SDK: Ensure that you have the .NET SDK installed on your machine. You can download it from
  3. Open a .NET Project:
    • Open Visual Studio Code
    • Configure AWS Credentials:
    • Before using any AWS services, you need to configure your AWS credentials. You can do this in various ways, but one common approach is to use the AWS Toolkit for Visual Studio. You can install the toolkit through the Visual Studio Code Extensions.
  1. Navigate to the Extensions view in Visual Studio Code by clicking on the Extensions icon located in the “Activity Bar” on the side pane of the window.

Search for “AWS Toolkit” in the Extensions view search box and install the “AWS Toolkit for Visual Studio Code” extension.

  • After installation, go to “aws” > “AWS Explorer.”

  1. Configure AWS Credentials:
    Before you can start using AWS services, you need to configure your AWS credentials.
  1. To add your AWS credentials (Access Key ID and Secret Access Key) as instructed, Press Ctrl+Shift+P to open the command palette within Visual Studio Code. Type “AWS: Create Credentials Profile” and choose it from the options.
    By following these steps, you’ll successfully configure your AWS credentials within Visual Studio Code.
  1. You will receive a confirmation as Connected to IAM credentials.
  1. Write Code Using AWS SDK:
    • Now that you have the AWS tool kit installed and credentials configured, you can start writing code to interact with AWS services in your .NET project and install the required NuGet packages

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Install AWS SDK NuGet Packages

  • The AWS SDK for .NET is distributed as NuGet packages. You can add these packages to your project using the Command-Line Interface (CLI).
    Here’s a simple example of using the AWS SDK for S3. By following these steps, you can integrate the AWS SDK for .NET into your Visual Studio code and start building applications that interact with AWS services.
  • Create a .NET project by executing the command below.

    dotnet new console --name demos3-dotnet-project

  • Navigate to the directory where you want to create your .NET project.

    cd demos3-dotnet-project

  • Run the following command to add the AWS SDK NuGet package, as shown below.

    dotnet add package AWSSDK.S3
    dotnet add package AWSSDK.SecurityToken
    dotnet add package AWSSDK.SSO
    dotnet add package AWSSDK.SSOOIDC

  • Now go to Visual Studio code and Open the Program.cs file in the demos3-dotnet-project folder. Go to the program.cs file and start writing code using the AWS SDK code to list and create a S3 Bucket.
  • Use the following command to run your .NET application; you will be able to list the buckets.

    dotnet run

  • Now, create a bucket by passing the argument as a Bucket Name, which should be globally unique. Run the following command to create a bucket.

    dot run BUCKET-NAME


Working with the AWS .NET SDK involves installing the SDK, configuring AWS credentials, selecting desired services, and writing code that interacts with those services. The SDK supports various AWS services, including Amazon S3, Amazon EC2, Amazon DynamoDB, AWS Lambda, and more.
Developers can test applications locally before deploying them to AWS environments such as Elastic Beanstalk, Lambda, or EC2 instances.

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