AWS DevOps Blog

Tag: Amazon ECS Fargate

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. […]

Use Amazon ECS Fargate Spot with CircleCI to deploy and manage applications in a cost-effective way

This post is written by Pritam Pal, Sr EC2 Spot Specialist SA & Dan Kelly, Sr EC2 Spot GTM Specialist Customers are using Amazon Web Services (AWS) to build CI/CD pipelines and follow DevOps best practices in order to deliver products rapidly and reliably. AWS services simplify infrastructure provisioning and management, application code deployment, software […]

This diagram depicts the deployment architecture for Jenkins on AWS Fargate

Building a serverless Jenkins environment on AWS Fargate

Jenkins is a popular open-source automation server that enables developers around the world to reliably build, test, and deploy their software. Jenkins uses a controller-agent architecture in which the controller is responsible for serving the web UI, stores the configurations and related data on disk, and delegates the jobs to the worker agents that run […]

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.