AWS DevOps Blog

Tag: How-to

Leveraging Amazon Q Developer for Efficient Code Debugging and Maintenance

In this post, we guide you through five common components of efficient code debugging. We also show you how Amazon Q Developer can significantly reduce the time and effort required to manually identify and fix errors across numerous lines of code. With Amazon Q Developer on your side, you can focus on other aspects of […]

AWS announces workspace context awareness for Amazon Q Developer chat

Today, Amazon Web Services (AWS) announced the release of workspace context awareness in Amazon Q Developer chat. By including @workspace in your prompt, Amazon Q Developer will automatically ingest and index all code files, configurations, and project structure, giving the chat comprehensive context across your entire application within the integrated development environment (IDE). Throughout the […]

Creating a User Activity Dashboard for Amazon CodeWhisperer

Maximizing the value from Enterprise Software tools requires an understanding of who and how users interact with those tools. As we have worked with builders rolling out Amazon CodeWhisperer to their enterprises, identifying usage patterns has been critical. This blog post is a result of that work, builds on Introducing Amazon CodeWhisperer Dashboard blog and […]

Getting started with Projen and AWS CDK

In the modern world of cloud computing, Infrastructure as Code (IaC) has become a vital practice for deploying and managing cloud resources. AWS Cloud Development Kit (AWS CDK) is a popular open-source framework that allows developers to define cloud resources using familiar programming languages. A related open source tool called Projen is a powerful project […]

Deploy container applications in a multicloud environment using Amazon CodeCatalyst

Deploy container applications in a multicloud environment using Amazon CodeCatalyst

In the previous post of this blog series, we saw how organizations can deploy workloads to virtual machines (VMs) in a hybrid and multicloud environment. This post shows how organizations can address the requirement of deploying containers, and containerized applications to hybrid and multicloud platforms using Amazon CodeCatalyst. CodeCatalyst is an integrated DevOps service which […]

10 ways to build applications faster with Amazon CodeWhisperer

Amazon CodeWhisperer is a powerful generative AI tool that gives me coding superpowers. Ever since I have incorporated CodeWhisperer into my workflow, I have become faster, smarter, and even more delighted when building applications. However, learning to use any generative AI tool effectively requires a beginner’s mindset and a willingness to embrace new ways of […]

Featured image for the "Build Next-Generation Microservices with .NET 5 and gRPC on AWS" blog post.

Build Next-Generation Microservices with .NET 5 and gRPC on AWS

Microservices commonly communicate with JSON over HTTP/1.1. These technologies are ubiquitous and human-readable, but they aren’t optimized for communication between dozens or hundreds of microservices. Next-generation Web technologies, including gRPC and HTTP/2, significantly improve communication speed and efficiency between microservices. AWS offers the most complete platform for builders implementing microservices — and the addition of HTTP/2 and gRPC support in Application Load Balancer (ALB) provides an end-to-end solution for next-generation microservices. ALBs can inspect and route gRPC calls, enabling features like health checks, access logs, and gRPC-specific metrics. This post demonstrates .NET microservices communicating with gRPC via Application Load Balancers.

Architecture diagram for the sample solution

Blue/Green deployment with AWS Developer tools on Amazon EC2 using Amazon EFS to host application source code

Many organizations building modern applications require a shared and persistent storage layer for hosting and deploying data-intensive enterprise applications, such as content management systems, media and entertainment, distributed applications like machine learning training, etc. These applications demand a centralized file share that scales to petabytes without disrupting running applications and remains concurrently accessible from potentially […]