Site Reliability Engineering (SRE)
Service level objectives, error budgets and an on-call practice that does not burn out your team.
Read moreProduction Kubernetes with sane defaults, guardrails and documentation — or honest advice that you do not need it.
Kubernetes is an outstanding platform and a system that must itself be maintained. For a team running a handful of services, a managed container service is often the better answer. For teams running many services, or needing consistent deployment across environments, it earns its complexity quickly.
When it is the right call, we build clusters that are boring on purpose: managed control planes, GitOps deployment, sensible resource requests, working autoscaling, real secrets management, tested backups and runbooks written for the person on call at 2am.
EKS, AKS or GKE so your team operates workloads rather than the cluster itself.
The cluster state matches a Git repository, making every change traceable and reversible.
Resource limits, pod security, network policy and admission control configured before the first workload.
Dashboards, alerts and runbooks handed over, not a platform only we understand.
We check that Kubernetes is genuinely warranted, and say so when a simpler service would do.
Cluster, networking, ingress, secrets, storage and observability delivered as code.
Workloads migrated one at a time, each with resource limits, probes and dashboards.
Upgrade process, backup restores and incident runbooks proven with your team before handover.
Often not. If you run fewer than about five services and have no multi-environment consistency problem, a managed container runtime is usually cheaper to own.
On a schedule, in staging first, with a documented rollback. Upgrades left too long are how clusters become unsupportable.
Yes, through a managed support arrangement, or we can back up your team while they take it on.
Service level objectives, error budgets and an on-call practice that does not burn out your team.
Read moreEvery resource defined in code, reviewed in a pull request and applied by a pipeline.
Read moreService boundaries drawn around real business capabilities, and honest advice when a monolith is better.
Read moreWe will tell you what we would do, roughly what it costs, and whether it is worth doing yet.