Should I Use Docker During Development, Deployment, or Both?

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Asked By MapleOrbit42 On

I'm an informatics engineering student working on several projects independently, and I'm trying to understand where Docker fits into the workflow. Should I start using it while developing an application, use it only when deploying to a server, or use it for both development and deployment?

4 Answers

Answered By QuietHarbor7 On

Docker can be useful in both stages, but how much you rely on it depends on the project. Using the same container setup during development and deployment can make the environment more consistent and reduce surprises when moving the application to a server.

Answered By MellowComet51 On

A practical approach is to create development and CI containers from the same general setup, then use a production image for deployment. This gives developers and automated builds matching tools and versions. Docker is one option; standards-based runtimes such as Podman or containerd may also be suitable depending on your security and infrastructure requirements.

Answered By LimeCactus18 On

Containers were originally used mostly for deployment, but they are now common throughout the development process too. A team can develop, test, and run an application using the same container configuration, which helps avoid the classic “works on my machine” problem. This is especially helpful when different projects need different language or tool versions.

SilverPebble63 -

For a small project, Docker is not always necessary, but it becomes increasingly useful when you have multiple services, dependencies, or environments to keep consistent.

Answered By BrightWalrus29 On

A Docker image packages an application together with much of the user-space environment it needs to run. That means the application is less dependent on whether the host uses one Linux distribution or another. Dockerfiles also provide a repeatable way to build the environment, while shared image layers can reduce duplicated storage. The tradeoff is some additional complexity and resource usage.

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