Kubernetes Consulting Services for US & EU Engineering Teams

It is rarely about the control plane (all three are conformant and stable) and almost always about what surrounds it. Pick EKS if your data plane already lives in AWS — VPC CNI, IRSA for IAM, ALB Ingress, Karpenter for autoscaling, and EBS CSI are first-class and integrate with the rest of the AWS estate. Pick GKE if you need the most opinionated experience: Autopilot removes node management entirely, Workload Identity is the cleanest service-account-to-IAM binding on the market, and the upgrade cadence is the most aggressive. Pick AKS if you are an enterprise on Entra ID and Azure Policy — the IAM and compliance story is the smoothest. For greenfield without an existing cloud bias we usually recommend GKE Autopilot. We do the eval as week one of every engagement and write up an ADR with concrete trade-offs scored against your workload.

We default to Argo CD for app delivery and Flux for cluster bootstrap, both with the App-of-Apps pattern. Cluster infrastructure (VPC, node groups, IAM, KMS keys, IRSA roles) is Terraform or Pulumi, stored in a separate repo with OPA/Conftest policy gates in CI. Application manifests live in Helm charts wrapped by Kustomize overlays per environment. Image promotion goes through a signed registry (Cosign + Sigstore) with a Renovate bot opening PRs against the GitOps repo. PR merged to main triggers Argo sync. Rollback is a git revert. We never let humans kubectl apply in production.

Six controls, non-negotiable. (1) Pod Security Standards set to restricted with Kyverno or OPA Gatekeeper enforcement. (2) Network policies default-deny with Cilium or Calico, traffic explicitly allowed per namespace. (3) IRSA on EKS or Workload Identity on GKE/AKS — never long-lived static credentials in secrets. (4) Image signing via Cosign with Kyverno verifyImages admission policy. (5) Runtime detection via Falco or Tetragon shipping to your SIEM. (6) Secrets via External Secrets Operator backed by AWS/GCP/Azure secret manager or HashiCorp Vault — no plaintext secrets in git, ever. We harden against CIS Kubernetes Benchmark v1.9 and provide the audit evidence pack for SOC 2 and ISO 27001.

Yes, and Kubernetes FinOps is most of where we save money on EKS and GKE clients. Standard play: install Kubecost or OpenCost for namespace-level chargeback, switch overprovisioned static node groups to Karpenter or GKE Autopilot, move stateless workloads to spot/preemptible with PodDisruptionBudgets and topology spread constraints, right-size requests and limits using Vertical Pod Autoscaler recommendations, and add HPA with custom metrics from KEDA rather than CPU-only. Typical first-quarter saving on a six-figure monthly EKS bill is 30 to 45 percent without touching reliability targets. We share the savings model with finance in a monthly written report.

Yes — this is most engagements that go past six months. A typical IDP stack: Backstage for the developer portal, Crossplane or Terraform-controller for self-service infrastructure claims, Argo CD for delivery, Argo Workflows for batch and ML, Tekton or GitHub Actions runners for CI, Istio or Linkerd for service mesh, Cilium Hubble for observability, OpenTelemetry collectors shipping to your APM. We do not invent abstractions — we glue best-of-breed CNCF projects into a paved road and document it in Backstage. Onboarding a new service drops from two weeks of YAML to a Backstage template + one PR.

Fixed-scope, all-in USD pricing across four engagement shapes. A Kubernetes audit (cluster, security and FinOps) runs from $700; a turnkey Kubernetes platform with GitOps, a security baseline and a Backstage internal developer platform from $1,800; managed Kubernetes and platform ops from $1,100 per month; and a senior CKA/CKS-certified platform engineer via staff augmentation from $100 per hour. You see the line-item budget at the end of discovery and sign off before any code is written. There is no recruitment markup, no tool surcharges, and cloud fees run on your own accounts, so you keep the cost lever.

Managed Kubernetes eliminates control plane operations: the cloud provider handles API server availability (99.95%+ SLA), etcd backups, Kubernetes version upgrades, and control plane security patching. EKS, GKE, and AKS all provide native cloud integration that reduces integration effort significantly. Self-hosted gives you full control over the control plane configuration, network topology, and hardware selection — important for air-gapped environments, specialized hardware (bare-metal GPU), or data sovereignty requirements where the control plane must remain on-premises. For most product companies under $50M ARR, managed Kubernetes is the right default and reaches production-ready state 4–6 weeks faster than self-hosted.

A production Kubernetes cluster on managed cloud with 3 availability zones, autoscaling node groups, and a staging environment typically runs $800–$2,500/month for small-to-medium workloads. Control plane costs are $72–$150/month on EKS/AKS; GKE offers one free Autopilot cluster per project. Beyond the cluster, costs include persistent storage, load balancers, monitoring (Prometheus/Grafana), and logging. Spot/preemptible instance strategies typically reduce compute costs by 40–70% for stateless workloads. We provide a cost estimate as part of our architecture assessment.

GitOps makes Git the single source of truth for cluster state: every configuration change goes through a pull request, gets reviewed, and the GitOps controller (ArgoCD or Flux) reconciles the cluster to match the declared state. ArgoCD provides a web UI and multi-cluster management that makes it easier for teams transitioning from manual deployments. Flux is lighter-weight, Kubernetes-native, and preferred for automated machine deployments without a UI dependency. We set up separate application repos (service code) and config repos (Kubernetes manifests/Helm values), configure sync policies with health checks, and implement promotion workflows from staging to production that require explicit approval.

Base64-encoded Kubernetes Secrets are not encrypted at rest by default. The three main approaches: HashiCorp Vault with the External Secrets Operator (best for fine-grained secret rotation and existing Vault deployments), Sealed Secrets (encrypts secrets with a cluster-specific key so encrypted manifests are safe to commit to Git — simplest GitOps-friendly option), and cloud provider secret managers via External Secrets Operator (best for cloud-native teams). We configure encryption at rest for the Kubernetes etcd datastore regardless of the secret management approach.

The kube-prometheus-stack Helm chart deploys Prometheus Operator, Alertmanager, Grafana, and pre-built Kubernetes dashboards in a single install. We configure service monitors for your application metrics, set up recording rules for commonly queried aggregations, and create alerting rules for CPU throttling, memory pressure, pod crash loops, and persistent volume pressure. Grafana dashboards cover cluster health, application performance (the RED method: Rate, Errors, Duration), and custom business metrics. We integrate Alertmanager with PagerDuty, OpsGenie, or Slack for production alerting.

Kubernetes disaster recovery has two components: cluster recovery and data recovery. For cluster recovery, we use Cluster API or infrastructure-as-code (Terraform/Pulumi) to define the cluster declaratively so it can be recreated in minutes. GitOps (ArgoCD/Flux) restores all application manifests automatically once the cluster is up. For data recovery, Velero backs up Kubernetes object manifests and persistent volume snapshots on a schedule, storing them in object storage with cross-region replication. RPO targets of 1 hour are achievable with hourly Velero snapshots; RTO targets of 30–60 minutes with pre-configured cluster-as-code and GitOps. We run quarterly DR drills to validate recovery time estimates.