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Kubernetes and Docker

Containers built small and reproducible, orchestrated only when the product needs it. Health checks, resource limits and rollbacks that work under pressure.

Containers solve a real problem: the same artefact runs on a laptop, in staging and in production. Kubernetes solves a different one, and not every product has it yet. We are happy to say when you do not need a cluster.

Images worth shipping

Multi-stage builds, a minimal base, no build toolchain in the runtime layer, no secrets baked in, and a tag that points at a commit rather than at latest. A small image is not vanity — it is a faster deploy and a smaller thing to patch when a CVE lands.

When orchestration earns its keep

Several services with different scaling profiles, rolling deploys with real health gates, jobs and cron work beside long-running processes, or a platform team that will still be here in two years. If your product is one API and one worker, a managed container runtime is less to own and we will recommend it.

The settings that matter under load

  • Liveness and readiness probes that check the thing that actually breaks
  • Requests and limits set from measurements, not from a template
  • Pod disruption budgets so a node drain does not take the service with it
  • Graceful shutdown, so in-flight work finishes before the container stops

Rollback is the feature

A deploy strategy is only as good as its reverse. We keep the previous release one command away and rehearse that path, because the middle of an incident is a bad time to read documentation.

What comes with it

Centralised logs, metrics and traces on day one. A cluster you cannot observe is a cluster you cannot debug.

Runs on AWS or Google Cloud, described in Terraform, deployed by CI/CD.

Ready to scope the next step?

Tell us what you want to build or fix. We reply with a plan, a rough budget and a start date. No slide deck first.