![]() Drifting - same Dockerfile producing different images And if a second build is not enough, we can add another Docker build event on production, just before deployment, which is not uncommon in scenarios where the build artefact is generated by an Ops team, after being vetted by the Dev team.Īnd now for the bitter truth about Docker images. ![]() In reality, the workflow where “developer A” tests on its laptop and directly pushes to production is quite rare, simply because mature teams at scale prefer continuous integration, generally linked to git push events on the shared repo. At its core, you could take a Docker image from the laptop, test it on the local on-prem cluster and finally deploy it on a CaaS somewhere in your favorite cloud provider, with the same build! While its simplicity of use won the heart of millions of developers all stack included, Docker pushed the barriers of C-level support with a powerful promise: build once, run everywhere. Heck, it has even turned into an action verb: “last sprint was all about dockerizing the stack”! “Just use a Docker image” says the container enthusiast! It generally goes very wrong very fast, one day you patch a minor version for an obscure library and the next day all hell breaks loose and a major overhaul is required, UNLESS… unless you pin every version down, monitor the build sequence for drifting, and implement a handful of other good practices, all of which we detail in this blog post! Docker will not fix your processĭocker fever has been going on for the past 7 years, how it has changed the IT ecosystem from the bottom up and why everyone and its grandmother is packaging software into containers. ![]() As anyone reading the 12factor manifesto, we want our projects to run in production the same way they’re running on our laptop, and we only accept minimal changes between environments: configuration values and persistent data at most.
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