作者彙整: Peter Wayner

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When a team develops software together, the need for continuous integration (CI)—and often continuous delivery (CD) as well—is rarely debated. The central continuous integration server acts like a referee and a quality control manager by constantly building and rebuilding the software before testing and retesting it. The sooner the CI server finds problems, the sooner they can be fixed.

The real debate is whether to host the continuous integration process yourself or offload the work onto one of the many cloud-based CI/CD services that have blossomed. Letting someone else do the work is always attractive and the services can often be faster because they share a pool of powerful machines that can run the different tasks from the CI process in parallel.

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The cloud and continuous integration (CI) are a natural match. While the cloud frees us from the pain of installing and maintaining physical servers, continuous integration automates away much of the pain of building, testing, and deploying our code. I… 閱讀全文 →

The cloud and continuous integration (CI) are a natural match. While the cloud frees us from the pain of installing and maintaining physical servers, continuous integration automates away much of the pain of building, testing, and deploying our code. I… 閱讀全文 →

Long ago in the early days of the Internet, pointing your browser at a URL meant your machine would start up a conversation with one server, and only one—the one connected with that URL. That may still happen if you visit a personal blog, but today all of the major websites and most of the small ones are really constellations of servers, sometimes dozens, sometimes hundreds, and sometimes even thousands.

Node.js has always been a popular foundation for enabling this leap into the future. Perhaps it’s because Node.js exploded in popularity around the same time as the microservice paradigm. Perhaps it’s because Node.js fits well in Docker containers. Perhaps it’s just because JavaScript is everywhere. Now when we go to a website, our packets travel to Node.js stacks, triggering more calls to more Node.js servers, each delivering a portion of the data that fills our screens.

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