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.
Cloud and delivery
Kubernetes only when it earns it.
Containers built small and reproducible, orchestrated only when the product needs it. Health checks, resource limits and rollbacks that work under pressure.
What you are buying
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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 as the product grows. If your product is one API and one worker, a managed container runtime is less to own and we will recommend it.
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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
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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.
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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.
Discuss the next step
Tell us what you want to build or improve. We reply with a plan, an indicative budget and a start date.