You’re called in. The system is misbehaving. It could be a key metric going crazy, or exceptions starting to fire. You’re troubleshooting, beating around the bush, just to realize that one of the team’s deployments was the one messing things up. Sounds familiar? If you’re practicing continuous deployment, you probably experience that several times a week, if not more. Users report that 50% of their outages are due to infrastructure and code changes, namely deployments.
In a single, monolithic repository, also known as a monorepo, you keep all your application and microservice code in the same source code repository (usually Git). Typically, teams split the code of various app components into subfolders and use Git workflow for new features or bug fixes. This approach is natural for most applications or systems developed using a monolithic architecture. Code in such a monorepo typically has a single build pipeline that produces the application executable.
This article will take you through setting up CI/CD integration for building, testing, and publishing libraries to Maven Central using Gradle. With jCenter shutting down, Maven Central is once again the primary destination for all Android and Java libraries. Library publishers will need to port their libraries over to Maven Central to keep their libraries available after jCenter shuts down. This article focuses on CI/CD integration.
At Cloudsmith, we believe that packaging should be at the centre of any modern build and deployment process. In fact, we think that Continuous Packaging is the glue that ties Continuous Integration and Continuous Deployment or Delivery together. So with that in mind, in this blog, we will take a walk through how easy it is to integrate Cloudsmith with a Semaphore CI workflow and push the artifacts and packages that you build to a private repository. TL:DR – It’s super easy.
Serverless computing, a model in which the provider manages the server, lets developers focus on writing dedicated pieces of application logic. Serverless computing has been adopted by many development teams because it auto-scales. Auto-scaling relieves developers of allocation management tasks, so they do not need to worry about the allocation of server resources or being charged for resources they are not consuming.
The Gradle Build Cache is designed to help you save time by reusing outputs produced by previous builds. It works by storing (locally or remotely) build outputs, and allowing builds to fetch these outputs from the cache when it determines that inputs have not changed. The build cache gives you the ability to avoid the redundant work and cost of regenerating time-consuming and expensive processes.
