Containers and Kubernetes

Kubernetes solves real problems, and it introduces its own. Plenty of teams adopt it and end up with a platform that needs a dedicated engineer to keep running - for a workload that would have been happier on ECS or Fargate.

We start by asking whether you need it.

Choosing the right runtime

If you run a handful of services, deploy on a schedule, and live entirely on AWS, ECS with Fargate is usually the better answer - less to operate, no control-plane cost, and native integration with everything else you use.

Kubernetes earns its complexity when you need portability across clouds, have enough services that scheduling matters, or want the operator ecosystem. We have written a detailed comparison if you are weighing it up.

Platforms teams can operate

Where Kubernetes is right, the goal is a cluster your team can run without us. Standardised Helm charts, GitOps delivery so cluster state is declared in Git and drift is visible, and a rollback that is a revert.

Autoscaling is configured against real traffic patterns rather than defaults, at both pod and node level. Node strategy accounts for cost - Spot for what tolerates interruption, Graviton where the workload supports it - which frequently halves the compute bill.

Hardened by default

Admission control enforces what may run before it runs: no privileged containers, no host network, resource limits required. RBAC and network policies are scoped tightly rather than granted broadly for convenience, and images are scanned in the registry with policy blocking known-exploitable vulnerabilities.

None of that is bolted on afterwards. It is how the platform is built, which is considerably cheaper than retrofitting it once workloads depend on the loose configuration.