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Kubernetes Setup & Management

A well-run Kubernetes cluster makes your engineers independent. A poorly configured one makes everything harder. The difference is almost entirely in the setup.

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The Problem

Kubernetes gets a reputation for being hard to operate because teams set it up wrong. Missing resource requests and limits lead to 40% over-provisioning. No pod disruption budgets mean rolling deploys kill availability. Security groups too permissive, RBAC too broad, no network policies.

The other common mistake is treating the initial cluster as temporary. Teams spin something up quickly, ship to production, and six months later nobody wants to touch it. Retrofitting Helm charts, proper namespaces, and GitOps onto an existing cluster running live traffic is painful. Getting it right from day one takes a few extra days. Fixing it later takes weeks.

Our Approach

01

Cluster design and sizing

We design your cluster architecture based on your workloads, expected traffic, and budget. Node types, autoscaling groups, spot instance strategy, and network topology.

02

Cluster provisioning with Terraform

We provision the cluster using Terraform so every piece of infrastructure is version-controlled and reproducible. EKS, GKE, or AKS - your choice based on where you are already running.

03

Application deployment setup

We set up Helm charts or Kustomize for your applications, configure namespaces and RBAC, set up GitOps with ArgoCD or Flux, and configure autoscaling (HPA and optionally KEDA).

04

Monitoring and alerting

We deploy Prometheus and Grafana for cluster metrics, configure PagerDuty or Opsgenie for alerts, and build dashboards your on-call engineers can actually use.

What You Get

  • Production Kubernetes cluster provisioned via Terraform
  • Staging cluster that mirrors production
  • Helm charts for all your services
  • GitOps setup with ArgoCD or Flux
  • Horizontal Pod Autoscaler configuration
  • Cluster monitoring with Prometheus and Grafana
  • RBAC policies and namespace structure
  • Runbook documentation and incident response guide

Tech Stack

AWS EKSGCP GKEAzure AKSTerraformHelmArgoCDPrometheusGrafanaKEDA

Real Example

35% cost reduction

Context: SaaS platform growing from 5 to 50 engineers, running Docker Compose in production.

Migrated to EKS in 6 weeks. Reduced cloud spend by 35% through proper resource limits and spot instances. Zero downtime during migration.

FAQ

For most startups under 5 services and 5 engineers, yes - K8s is likely overkill. The inflection point is when you need reliable autoscaling, zero-downtime deployments, or multiple teams deploying independently. If you are past that, it is the right tool.

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