AWS DevOps Blog

Tag: Amazon ECS

Blue/Green Deployments with Amazon ECS using Amazon CodeCatalyst

Amazon CodeCatalyst is a modern software development service that empowers teams to deliver software on AWS easily and quickly. Amazon CodeCatalyst provides one place where you can plan, code, and build, test, and deploy your container applications with continuous integration/continuous delivery (CI/CD) tools. In this post, we will walk-through how you can configure Blue/Green and […]

Blue/Green deployments using AWS CDK Pipelines and AWS CodeDeploy

Customers often ask for help with implementing Blue/Green deployments to Amazon Elastic Container Service (Amazon ECS) using AWS CodeDeploy. Their use cases usually involve cross-Region and cross-account deployment scenarios. These requirements are challenging enough on their own, but in addition to those, there are specific design decisions that need to be considered when using CodeDeploy. […]

Using Workflows to Build, Test, and Deploy with Amazon CodeCatalyst

Amazon CodeCatalyst workflows are continuous integration and continuous delivery (CI/CD) pipelines that enable you to easily build, test and deploy applications. CodeCatalyst was announced at re:Invent 2022 and is currently in preview. Introduction: I recently read The Unicorn Project, the follow-up to the bestselling title The Phoenix Project from Gene Kim. After a few years at Amazon, […]

Generate DevOps Guru Proactive Insights in ECS using Container Insights

Generating DevOps Guru Proactive Insights for Amazon ECS

Monitoring is fundamental to operating an application in production, since we can only operate what we can measure and alert on. As an application evolves, or the environment grows more complex, it becomes increasingly challenging to maintain monitoring thresholds for each component, and to validate that they’re still set to an effective value. We not […]

Build and deploy .NET web applications to ARM-powered AWS Graviton 2 Amazon ECS Clusters using AWS CDK

With .NET providing first-class support for ARM architecture, running .NET applications on an AWS Graviton processor provides you with more choices to help optimize performance and cost. We have already written about .NET 5 with Graviton benchmarks; in this post, we explore how C#/.NET developers can take advantages of Graviton processors and obtain this performance […]

Mainfrme DevOps On AWS Architecture Overview, Two types of pipelines, Project Pipeline and Regression Pipeline

Automate thousands of mainframe tests on AWS with the Micro Focus Enterprise Suite

We have seen mainframe customers often encounter scalability constraints, and they can’t support their development and test workforce to the scale required to support business requirements. These constraints can lead to delays, reduce product or feature releases, and make them unable to respond to market requirements. Furthermore, limits in capacity and scale often affect the quality of changes deployed, and are linked to unplanned or unexpected downtime in products or services.
The conventional approach to address these constraints is to scale up, meaning to increase MIPS/MSU capacity of the mainframe hardware available for development and testing. The cost of this approach, however, is excessively high, and to ensure time to market, you may reject this approach at the expense of quality and functionality. If you’re wrestling with these challenges, this post is written specifically for you.