Category: Technical How-to

Computing at-scale solutions is required in many industries and domains. Cloud computing provides elastic on-demand access to large amounts of computing resources and enables economically efficient and technically flexible solutions naturally suited for computing at scale. Batch processing is a requirement for many scale-out computing solutions. Customers use batch processing as a non-interactive way of […]

Have you been tasked with identifying which Amazon Machine Images (AMI) are in use in your organization and how they are being billed? Have you researched several solutions but find that you can’t get the exact data you need or that you don’t have access to the payer-level billing data? Then this solution is for […]

In part 2 of this blog post series, we show how to set up a project in Amazon CodeCatalyst and collaborate on the coding, building, testing, and deployment of .NET serverless applications in your AWS environments. Consider reviewing the first post, which introduced CodeCatalyst. It explains the compute fleet options that are available for your […]

In this blog post, the first in a series of posts about using .NET with Amazon CodeCatalyst, we will guide you through building and deploying a .NET 6.0 ASP.NET Core web API to Amazon Elastic Container Service (Amazon ECS) using the ASP.NET Core web API project blueprint included with CodeCatalyst and the AWS .NET deployment […]

Amazon Web Services (AWS) recently introduced a new workflow template that improves the experience of importing your on-premises virtual machine (VM) images using the AWS Migration Hub Orchestrator console. Previously, when importing Windows Server or Linux VM images using the VM Import/Export service, customers could only use the AWS Command Line Interface (AWS CLI) or […]

Introduction In this blog post, we will walk through how to automate the creation of an Azure DevOps release pipeline that deploys containerized applications to AWS. This solution will save you time and effort if you’re using Azure DevOps for version control or CI/CD and if you’re modernizing your applications using containers. We will use […]

Thermo Fisher team designed a solution to pull business context data from Microsoft SharePoint and enrich data pipeline hosted on AWS to build sales and inventory BI reports.

In this blog post, I will share results for Babelfish for Aurora PostgreSQL performance testing using the HammerDB database benchmarking tool. Based upon the results of testing various Aurora for PostgreSQL clusters hosting Babelfish, I will also provide recommendations on the optimal instance selection from the price-performance viewpoint. This blog post concludes with a summary […]

In this blog post, I will provide details on how to set up Babelfish for Aurora PostgreSQL for performance analysis using the HammerDB performance tool. 1.   Introduction Whether it’s a component of migrating to AWS or optimizing workloads already on AWS, customers are looking at the options to modernize their SQL Server workloads. An attractive […]

CDK offers a high-level abstraction to define AWS resources using modern programming languages. Among its components, it provides aws-s3-assets, which is a high level construct that abstracts packaging AWS Lambda functions. The default behavior of this construct is to zip all the content into a folder and upload it to an Amazon Simple Storage Service (Amazon S3) bucket. That works great for Lambda runtimes like Python or Node.js, which do not require code compilation, but for .NET, Java, or Go, which requires code compilation, you’ll need extra steps to restore external dependencies, compile the code, and publish the binary. This post will explore how to streamline building, packaging, and publishing .NET Lambda functions using AWS CDK.