Kubernetes & Cloud Platform
GKE clusters on Google Cloud, designed to be boring to operate and sized to what you actually run.
The challenge
Sound familiar?
Many teams end up with a cluster nobody fully understands: workloads deployed by hand, node pools sized for a peak that never comes, databases running inside the cluster with no backups, and a monthly bill that keeps creeping up.
Or the opposite — everything still lives on a single VPS or shared host, and every release is a manual SSH session.
Our approach
What we do
- 01
Cluster design
We lay out GKE clusters with clear namespaces, node pools matched to workload profiles, Workload Identity instead of key files, and private access to managed services.
- 02
Helm charts for every service
Each application gets a chart with sane resource requests, health probes, a read-only root filesystem and non-root users, so every service is deployed the same way.
- 03
Managed data, not pets
Databases move to Cloud SQL with point-in-time recovery, media to Cloud Storage, and caches to dedicated instances — out of the cluster and backed up.
- 04
Cost review
We look at requests versus real usage, idle resources, egress and storage classes, and cut what is not pulling its weight.
What you get
- A documented GKE cluster with namespaces, node pools and network policy
- Helm charts for your services, kept in Git
- Managed PostgreSQL with private connectivity and point-in-time recovery
- Workload Identity for access to cloud services, no long-lived keys
- A written cost review with concrete changes applied
Technologies
Let’s talk about your project
A few lines about your situation are enough to start.