Kubernetes consulting & platform engineering
We help teams run real workloads on Kubernetes: stateful products, deployed many times a day, with the observability to see what's happening when something breaks. We engineer these deployments end to end, with Helm charts as code, autoscaling and safe releases.
Kubernetes that works the day after you launch
Standing up a cluster is the easy part. Teams get stuck on running a stateful product on it reliably, recovering it after a failure and shipping to it safely many times a day. We focus on day-to-day operations: reproducible environments, safe releases and signals you can act on.
- Cluster architecture: managed control plane, node pools, networking
- Infrastructure as code, so environments are reproducible
- Stateful workloads: managed Postgres, Redis and persistent storage
- Safe deployment strategies: blue-green and progressive rollout
- Observability: metrics, logs and traces wired in from day one
- Hardening: RBAC, network policy, secrets and resource limits
How we approach the platform
Everything is described as code, so the same definition stands up staging and production with no manual drift. We optimise for recoverability and clarity over cleverness.
- 1
Assess & plan
We review your workloads, constraints and team, then design a cluster topology that fits without over-engineering it.
- 2
Infrastructure as code
The cluster and its services described declaratively, so environments are reproducible and changes are reviewable.
- 3
Workloads & data
Stateful services done right: managed Postgres and Redis, persistent volumes, backups and sane resource limits.
- 4
Safe delivery
Blue-green or progressive releases so deploys are routine and reversible, with health checks gating each step.
- 5
Observe & harden
Metrics, logs, and traces in from day one; RBAC, network policy, and secrets locked down before you carry real traffic.
What you receive
A platform your team can operate with confidence: reproducible, observable and recoverable.
- A documented cluster architecture sized to your workloads
- Infrastructure as code that stands up staging and production identically
- Stateful services configured with backups and resource limits
- A blue-green or progressive deployment pipeline
- Dashboards and alerts for metrics, logs, and traces
- A hardening pass (RBAC, network policy, secrets) plus a runbook
The platform toolchain
We engineer Kubernetes deployments as code, with Helm charts, autoscaling, Postgres and Redis, blue-green releases, and metrics, logs and traces wired in from day one. Your product gets the same setup.
Kubernetes consulting questions
Do I actually need Kubernetes?
Not always. For a single small service, a managed platform-as-a-service is often simpler and cheaper. Kubernetes earns its keep when you're running several services, need reproducible environments across staging and production, deploy frequently, or want portability across clouds. We'll tell you whether it fits your stage. Adopting it too early is a common and expensive mistake.
Can you run stateful workloads like databases on it?
Yes. That's exactly the hard case we focus on. We typically use managed Postgres and Redis where they're available, with persistent volumes, backups and tested recovery for anything that has to live in the cluster. Stateless services are easy; we make the stateful parts reliable too.
How do you make deployments safe?
We use blue-green or progressive rollouts gated by health checks, so a bad release is caught and rolled back before it reaches all your users. Because the whole platform is described as code, every change is reviewable and reversible, with no manual drift between environments.
Will my team be able to run it after you leave?
That's the point. Everything is in code and documented, we wire in the observability your team needs to see what's happening, and we hand over a runbook for the routine operations and the failure cases. We can stay on for support, but you won't be locked into us.