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.
AWS Developer Tools is a set of services that include AWS CodeCommit, AWS CodePipeline, AWS CodeBuild, and AWS CodeDeploy. Together, these services help you securely store and maintain version control of your application’s source code and automatically build, test, and deploy your application to AWS or your on-premises environment. These services are designed to enable […]
How to Create an Automated Database Continuous Integration and Release Management Workflow with Datical and AWS
Editors note: This blog post is out of date. For an up-to-date blog post on how to implement CI/CD for your database you can try this post “Deploy, track, and roll back RDS database code changes using open source tools Liquibase and Jenkins.” Thank you to my colleague Erin McGill for reviewing and providing valuable feedback on this […]
By Balaji Iyer, Janisha Anand, and Frank Li Organizations that transform their applications to cloud-optimized architectures need a seamless, end-to-end continuous delivery and deployment workflow: from source code, to build, to deployment, to software delivery. Continuous delivery is a DevOps software development practice where code changes are automatically built, tested, and prepared for a release to production. The […]
(This post has been updated on October 1, 2018 to reflect the deprecation of GitHub services. You can learn more about this deprecation here. We now recommend setting up automatic deployments from GitHub using AWS CodePipeline and AWS CodeDeploy.) AWS CodeDeploy is a service that makes it easy to deploy application updates to Amazon EC2 […]
A good practice for maintaining highly available applications is to monitor the metrics that impact performance and service levels. AWS OpsWorks includes built-in integration with 14 Amazon CloudWatch metrics, including load, CPU and memory, but you may also want to monitor other metrics such as disk space utilization or application-level metrics such as error rates. […]