Services · BUILD
Kubernetes that your team can actually operate.
Cluster architecture, GitOps, multi-tenancy, observability, and on-call patterns — built so your platform doesn't depend on the engineer who set it up.
How we deliver this: AI handles the routine analysis (audits, IaC drafts, runbook scaffolds, alert triage). A senior engineer reviews every change before it touches your production. Consultancy speed at consultancy quality.
Read more →When you need this
A cluster nobody owns
When the platform team is one person and they're on PTO, ownership ambiguity becomes outage risk. We build operating models, not just clusters.
Endless YAML, drifting environments
Hand-edited manifests across dev, staging, and prod produce silent drift. GitOps with environment overlays makes drift visible and reversible.
Workload teams blocked by platform tickets
When every namespace, RBAC change, or ingress rule needs a platform ticket, velocity dies. Self-service guardrails let teams move without breaking things.
How it works
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Phase 01
Cluster design
Multi-cluster vs. multi-tenant trade-offs, networking model, ingress, service mesh decisions — documented before YAML is written.
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Phase 02
GitOps foundation
Argo CD or Flux, environment overlays via Kustomize or Helm, secrets management, and policy-as-code (OPA Gatekeeper or Kyverno).
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Phase 03
Workload onboarding
Templates, paved-path Helm charts, and a self-service portal so workload teams ship to Kubernetes without learning Kubernetes.
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Phase 04
Day-2 operations
Observability (Prometheus + Grafana + Loki + Tempo), auto-scaling (HPA, VPA, KEDA), runbooks, and a working on-call rotation.
What you get
- → Cluster architecture document with rationale for each decision
- → GitOps repo with environment overlays and policy-as-code
- → Paved-path workload templates for your most common service types
- → Observability stack with golden-signal dashboards
- → On-call runbook and escalation guide
What changes for you
Self-service for product teams
Workload teams ship to Kubernetes without raising platform tickets. Guardrails enforce limits without blocking velocity.
GitOps-native operations
Cluster state lives in git. Audit, rollback, and disaster recovery are git operations, not detective work.
Cost visibility per workload
OpenCost or Kubecost integrated with your tagging — workload teams see what their pods cost.
Sane upgrades
Cluster upgrades become a routine quarterly task, not a multi-week project. We document the rehearsal and the rollback.
Security baselines that hold up
Pod security, network policies, image scanning, and admission control come standard — not as a follow-on hardening sprint.
Less hero work
When the platform engineer who built it leaves, the documentation, dashboards, and runbooks remain — not a black box.
What clients say
"CloudWizz rebuilt our delivery pipeline in eight weeks. Deploys went from a Friday-night ritual to a non-event we ship four times a day."
Director of Engineering
Fintech, Series C · 2025-11
"They turned a CFO emergency into a board-ready story in 12 weeks. The dashboards alone changed how engineering thinks about cost."
VP Engineering
Series B SaaS · 2026-01
Frequently asked questions
EKS, AKS, GKE, or self-managed? +
Almost always managed (EKS/AKS/GKE) for production. Self-managed Kubernetes is only worth it for very specific edge or air-gapped cases. We'll discuss the trade-off in discovery.
Should we use a service mesh? +
Probably not on day one. Most teams overestimate the value and underestimate the operational cost of Istio/Linkerd. Start without; adopt when a real need emerges.
Argo CD or Flux? +
Both work. Argo CD has a stronger UI; Flux is more git-purist. We pick based on your team's preferences and existing tooling — not a religious answer.
How do you handle multi-tenancy? +
Namespace-per-team with RBAC and resource quotas, plus network policies, is the default. For stronger isolation we use vCluster or separate clusters — case-by-case.
Do you migrate from ECS / Nomad / VMs to Kubernetes? +
Yes. We've run ECS → EKS, ASGs → EKS, and Nomad → EKS migrations. Each is a wave-based plan with cutover runbooks per workload.
How do you handle stateful workloads? +
Operators where they exist (e.g. CloudNativePG, Strimzi). Otherwise managed cloud services accessed from inside the cluster — Kubernetes is great at stateless, less great at databases.
What's your stance on Helm vs. Kustomize? +
Both. Helm for off-the-shelf packages, Kustomize for environment overlays of your own services. Mixing them is fine.
Can you set up an internal developer platform on top? +
Yes — Backstage or Port for the portal layer, integrated with your CI/CD, repo, and observability. We scope this as a discrete project after Kubernetes basics are stable.
How do we control costs? +
Right-sized requests/limits, cluster autoscaler with appropriate node groups, Spot/preemptible for batch, scheduled scale-down for non-prod, and per-workload cost dashboards. Typical savings: 30–60% versus a stock setup.
How long until our team can operate this independently? +
8–12 weeks of pairing typically gets a team to autonomy on day-2 operations. Cluster upgrades and major changes are pair-reviewed for the first cycle.