Where Docker fits in a long-term product team.

The benefit most teams notice first is onboarding. A new specialist runs one command and has a working environment, instead of spending two days following a README written for a machine that no longer exists. On an engagement where people join over several years, that compounds.

Images rot quietly. A base image pinned three years ago carries three years of unpatched libraries, and a Dockerfile that installs whatever is latest builds differently every week. Both are avoidable with pinned versions and a regular rebuild, and both are common in estates without an owner.

What your dedicated team does with Docker.

Containerisation is the part of a stack that quietly stops being maintained. Base images drift out of support and build times creep up until developers stop waiting for them, because both are shared problems without an owner.

On an assigned team it sits with whoever owns the pipeline. When the same specialists also build the application, it's usually one dedicated development team, so there's one owner for the whole stack.

Common Docker use cases.

  • A working environment on day one New team members productive on day one, with no setup marathon.
  • Making the pipeline match production The same image tested and deployed, so a passing build means something about the thing that ships.
  • Reducing build time Layer caching and multi-stage builds applied to a pipeline where every commit currently costs twelve minutes.

Adding Docker skills to your team.

Containerisation is part of every dedicated cloud and DevOps team's work, because almost everything else in the pipeline depends on it.

Every Docker specialist we assign works remotely inside your tools as a dedicated member of your team, with the management on our side. It is how companies hire remote developers without opening an offshore office of their own.

Tell us what your roadmap needs Docker for.

A service delivery manager will reply with the specialists we'd suggest, the monthly capacity and what the first month looks like.

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