Technology
Kubernetes Development & Consulting Services — Production K8s Done Right
Production Kubernetes engineering — cluster design, GitOps, observability, CIS hardening, multi-tenancy, internal developer platforms, and the day-2 operations the demos skip.
What we build with Kubernetes
- Production cluster design on EKS, GKE, AKS, or self-managed (kubeadm, kops, k3s)
- GitOps with Argo CD or Flux, progressive delivery via Argo Rollouts
- Security: CIS benchmark, Pod Security Standards, OPA Gatekeeper / Kyverno policies, signed images with Cosign
- Observability with Prometheus, Grafana, Loki, Tempo, OpenTelemetry collector, and AWS / GCP / Azure native integrations
- Helm and Kustomize for application packaging — chosen per workload
- Operators and CRDs for platform-level abstractions
- Karpenter for fast, right-sized node autoscaling on Spot and On-Demand
- Service mesh (Istio, Linkerd, Cilium) when mTLS, traffic splitting, or cross-cluster routing justifies it
- Multi-tenancy: namespace per team, RBAC, quotas, network policies, and admission controllers
- Internal developer platforms with Backstage, custom portals, or scaffolded Helm charts
- Cluster upgrade automation across minor versions
- Cost optimization: Karpenter consolidation, Spot, Graviton / Ampere, and rightsizing
- Disaster recovery: Velero backups, cross-region replication, and failover runbooks
- Migration paths from ECS / VMs / self-managed K8s / Docker Swarm to managed Kubernetes
Why DiveScale
Built by engineers who ship Kubernetes in production
Kubernetes is powerful when used in earnest and a liability when half-adopted. DiveScale ships Kubernetes platforms that earn their complexity: GitOps from day one, security hardened against CIS, observable, and self-service for app teams. We have shipped K8s for healthcare, fintech, hospitality, veterinary, and SaaS clients in production.
We make Kubernetes choices honestly. Many small teams should be on ECS, Cloud Run, or Container Apps — not K8s. When the workload genuinely calls for it (multi-team, complex networking, ecosystem dependencies, Operators), we ship K8s with the operational discipline production demands.
Our default cluster shape: managed control plane (EKS / GKE / AKS), Karpenter for autoscaling, Argo CD for GitOps, OPA Gatekeeper or Kyverno for policy, Cosign for image signing, and a Prometheus / Grafana / Loki / Tempo stack for observability. Variations exist — but this shape works.
And we build the developer-experience layer. App teams should not write raw YAML for routine deploys. Backstage templates, scaffolded Helm charts, or custom portals make the platform a productivity multiplier instead of a tax. The platform team's job is to make the rest of engineering faster.
Day-2 operations is where teams accumulate pain. We design for it: cluster upgrades on a cadence, Velero backups with regular restore drills, security policy that evolves as new CVEs land, observability that catches noisy-neighbor before it becomes an incident, and runbooks for the failure modes we hope never to use.
We take over struggling K8s estates regularly. A 2-week audit against CIS benchmark and SRE best practice; quick security and stability wins shipped in the first month; a 3–6 month plan to bring the platform to production discipline. No big-bang replacements.
Kubernetes use cases we deliver
How we deliver
Our Kubernetes delivery process
- 01
Right-size the platform
Pressure-test whether K8s is actually the right answer. We say so honestly when it is not — ECS, Cloud Run, or Container Apps often win for smaller teams.
- 02
Cluster + IaC foundation
Cluster design, networking (VPC, CNI choice, network policies), IAM topology (IRSA on AWS, Workload Identity on GCP), and Terraform / CDK for everything.
- 03
GitOps from day one
Argo CD or Flux managing cluster state from Git. No kubectl on production clusters from laptops.
- 04
Harden security
CIS benchmark, Pod Security Standards, OPA / Kyverno policies, Cosign-signed images, and runtime threat detection.
- 05
Observability stack
Prometheus, Grafana, Loki, Tempo, OpenTelemetry — wired to SLOs that map to user-visible behavior, not just CPU and memory.
- 06
Developer self-service
Backstage, scaffolded charts, or custom portals. App teams onboard themselves; the platform team scales.
- 07
Operate or hand off
Ongoing platform engineering with on-call, or hand off with runbooks, IaC, and on-call playbooks your team can extend.
Related technologies
Docker
Production Docker engineering — small images, multi-stage builds, BuildKit caching, security scanning, and the operational discipline containers deserve.
Learn moreAmazon EKS
EKS cluster engineering — IAM Roles for Service Accounts, autoscaling with Karpenter, GitOps with Argo CD, and the observability stack production Kubernetes demands.
Learn moreGoogle Cloud
GCP architecture, GKE, Cloud Run, BigQuery, and Vertex AI — production engineering for organizations leveraging Google’s data and AI strengths.
Learn moreTerraform
Terraform engineering — module design, state strategy, multi-account governance, policy-as-code, drift detection, and CI-driven plan / apply for multi-cloud estates.
Learn moreKubernetes — Frequently Asked Questions
Often, no. Small teams running a handful of services usually do better with ECS, Cloud Run, or Container Apps. We use K8s when there is genuine reason — ecosystem, multi-tenancy, complex networking, Operator-driven abstractions — not as a default.
