Kubernetes platforms your developers actually like
Kubernetes is a toolkit for building a platform, not a platform by itself. We design and run clusters on Amazon EKS and Google Kubernetes Engine where the desired state lives in Git, every deploy is a reviewed pull request, every pull request gets its own preview environment, and autoscaling, policy and secrets are handled by the platform instead of by tickets.
A platform, not just a cluster
Everything a team needs to ship and run services on Kubernetes, set up once and kept in Git.
Cluster Design
EKS or GKE built with Terraform: private control planes, node pools by workload type, network policies, workload identity, and separate clusters or namespaces per environment.
GitOps Delivery
Argo CD or Flux keeps each cluster in sync with Git. Deploy by merging, roll back by reverting, and see drift the moment someone edits a live object by hand.
Preview Environments
Every pull request gets a namespace with its own URL, seeded data and the services it needs, created automatically and removed on merge.
Progressive Delivery
Canary and blue-green releases with Argo Rollouts or Flagger, promoted or rolled back automatically on error rate and latency.
Autoscaling
Horizontal pod autoscaling on the right metrics, KEDA for queue depth and events, Karpenter or cluster autoscaler for nodes, Spot capacity where interruptions are safe.
Policy & Security
Pod security standards, Kyverno or OPA Gatekeeper policies, signed images, network policies, and RBAC mapped to your identity provider.
Secrets & Config
External Secrets pulling from AWS Secrets Manager, Google Secret Manager or Vault, so no secret is ever committed, plus configuration per environment in Helm or Kustomize.
Observability
Prometheus and Grafana, Loki for logs, Tempo or Jaeger for traces, all fed by OpenTelemetry, with dashboards and alerts per service and per team.
Developer Self-Service
Templates for a new service with its pipeline, dashboards and alerts included, and an internal developer portal such as Backstage when the number of teams calls for one.
When Kubernetes pays off, and when it does not
We would rather talk you out of a cluster than run one you do not need.
| Your situation | Our recommendation | Why |
|---|---|---|
| One app, one database, one team | Cloud Run or ECS on Fargate | Same containers, autoscaling and zero-downtime deploys, without upgrades and add-ons to maintain. |
| Five to fifteen services, one or two teams | Managed containers, or GKE Autopilot | Depends on how much the services share: networking, sidecars and policies tip it toward Kubernetes. |
| Many services, several teams deploying independently | Kubernetes with GitOps and self-service | A shared platform with guardrails costs less than every team reinventing deploys, secrets and monitoring. |
| GPUs, batch jobs, mixed workloads | Kubernetes with dedicated node pools | Scheduling, quotas and bin-packing across workload types are what Kubernetes does best. |
| The same platform on two clouds | EKS and GKE from shared Terraform and GitOps repositories | The cluster becomes the common layer; cloud-specific parts stay thin and documented. |
Running clusters after launch day
Creating a cluster takes an afternoon. Keeping it healthy for years is the real job.
Upgrades on schedule
Deprecated APIs checked ahead of time, staging first, node pools rolled with disruption budgets so services stay up.
Capacity & cost
Requests and limits tuned from real usage, bin-packing reviewed, per-namespace cost reports for each team.
Security hygiene
Image scanning, patched base images, policy reports reviewed, access audited against your identity provider.
Recovery drills
Cluster state and volumes backed up with Velero or cloud snapshots, and a full rebuild from Git rehearsed on a schedule.
Kubernetes questions, answered
What engineering leads ask before committing to a platform.
When is Kubernetes worth it, and when is it overkill?
It is worth it when you run many services, several teams deploy independently, workloads need custom scheduling, GPUs or sidecars, or you want one platform across clouds. It is overkill for a monolith and a database, or a few services one team owns: Cloud Run or ECS on Fargate do that with far less upkeep. We say which case you are in before anything gets built.
What is GitOps and why does it matter?
GitOps means the desired state of every cluster lives in a Git repository, and a controller such as Argo CD or Flux keeps the cluster matching it. Deploying is a reviewed pull request, rolling back is a revert, and any manual change made with kubectl is detected and undone. You always know what is running, who changed it and why.
EKS or GKE?
Usually whichever cloud the rest of your system is on. GKE has the smoother managed experience, with Autopilot taking over node management. EKS fits teams already deep in AWS and gains a lot from Karpenter for fast, cost-aware node provisioning. We build the same GitOps platform on either, so moving between them later is a contained project. See our AWS and Google Cloud pages for the rest of each stack.
How do you handle Kubernetes upgrades?
On a schedule, not under pressure. Managed control planes get a new minor version a few times a year, so we keep clusters within supported versions, check deprecated APIs before each upgrade, upgrade staging first, then roll node pools in production with disruption budgets so services stay up. Add-ons are versioned in Git with everything else.
Can you take over a cluster someone else set up?
Yes. We inventory what runs, export the live manifests into Git, import the cluster into Terraform, close obvious security gaps, and put a GitOps controller in charge. From then on every change is reviewed and reversible, and the cluster no longer depends on one person's memory.
How do you keep Kubernetes costs down?
Requests and limits set from real usage, not guesses, autoscaling at both the pod and the node level, Spot capacity for interruptible workloads, scaling preview environments and batch jobs to zero, and per-namespace cost reports so each team sees what it spends.
How long does a new service take to reach production?
If the answer is weeks and a pile of tickets, the platform is the bottleneck. Tell us how your teams ship today, and we'll show you what to fix first, with a fixed quote.
Get a fixed quote