Production Kubernetes architecture, managed cluster deployment (EKS, AKS, GKE), monitoring with Prometheus and Grafana, and GitOps workflows with ArgoCD and Helm. FreedomDev has 20+ years of infrastructure experience in Zeeland, Michigan. We help teams that need Kubernetes done right — and we tell you when you do not need it at all.
Kubernetes won. The CNCF 2023 survey reported 96% of organizations are either using or evaluating Kubernetes, up from 83% in 2020. It is the operating system for modern infrastructure — the abstraction layer that lets you deploy, scale, and manage containerized workloads across any cloud provider or on-premises data center without rewriting your deployment tooling every time you change hosts. If you are running more than a handful of Docker containers in production, you are either already on Kubernetes or spending engineering time solving problems Kubernetes already solved.
But Kubernetes is not a product you install and forget. It is a platform you build on. A production-grade cluster requires decisions about networking (Calico vs Cilium vs the cloud provider CNI), ingress (nginx Ingress Controller vs AWS ALB Ingress vs Istio Gateway), secrets management (Kubernetes Secrets with SOPS encryption vs HashiCorp Vault vs AWS Secrets Manager), storage (EBS CSI driver, EFS for shared volumes, or Longhorn for on-prem), observability (Prometheus, Grafana, Loki for logs, Jaeger or Tempo for traces), and deployment strategy (Helm charts, Kustomize overlays, ArgoCD for GitOps, or Flux). Each decision has downstream consequences, and the wrong combination creates operational debt that compounds every time you deploy.
The managed Kubernetes market reflects this complexity. AWS EKS holds approximately 42% market share among managed Kubernetes services, with Azure AKS at roughly 29% and Google GKE at around 22%. Each provider handles the control plane differently, charges differently (EKS charges $0.10/hour for the control plane; GKE Autopilot bundles it into pod pricing; AKS makes the control plane free but charges for uptime SLA), and integrates differently with their native services. Choosing a managed provider is not just a Kubernetes decision — it is a cloud platform commitment that affects your networking, IAM, storage, and billing for years.
FreedomDev architects and deploys production Kubernetes clusters for companies that need containers orchestrated correctly from day one — not after a production incident teaches them what they skipped. We handle cluster architecture, namespace strategy, resource requests and limits, network policies, RBAC, Helm chart development, CI/CD pipeline integration, and ongoing monitoring. We also do the thing most Kubernetes consultants will not: tell you when Kubernetes is overkill for your workload and recommend a simpler alternative.
Production cluster design from the ground up: control plane sizing, node pool strategy (spot instances for batch, on-demand for stateful workloads), namespace isolation per environment and team, resource requests and limits tuned to actual workload profiles, Pod Disruption Budgets for safe node drains, and network policies using Calico or Cilium to enforce zero-trust pod-to-pod communication. We deploy on EKS, AKS, GKE, or bare-metal (k3s/RKE2 for edge and on-prem). Every cluster ships with Terraform IaC so your infrastructure is version-controlled, reviewable, and reproducible.
AWS EKS if you are already deep in AWS (VPC integration, IAM roles for service accounts, ALB Ingress Controller, EBS/EFS storage classes). Azure AKS if you run Dynamics 365, Azure AD, or Azure DevOps (free control plane, integrated Azure Monitor, Azure AD pod identity). Google GKE if you want the most opinionated and automated experience (Autopilot mode, native Istio service mesh, integrated Cloud Run for serverless). We evaluate your existing cloud footprint, IAM model, networking requirements, and budget to recommend the right provider — then deploy with Terraform modules and Helm charts so you are not locked into a single consultant's kubectl history.
Helm charts structured for real teams: parameterized values files per environment (dev, staging, production), dependency management for sub-charts, pre/post-install hooks for database migrations, and semantic versioning pushed to a private chart registry (Harbor, ECR, or ChartMuseum). For GitOps, we deploy ArgoCD with Application Sets that auto-sync from your Git repository — every deployment is a Git commit, every rollback is a git revert, and your cluster state is always auditable. We configure progressive delivery with Argo Rollouts for canary and blue-green deployments that promote automatically based on Prometheus metrics.
Full observability stack: Prometheus for metrics collection (node-exporter, kube-state-metrics, custom ServiceMonitors for your application), Grafana dashboards for cluster health and application KPIs, Alertmanager with PagerDuty/Slack/OpsGenie routing, Loki for centralized log aggregation (replacing ELK stacks that cost 10x more to operate), and Jaeger or Grafana Tempo for distributed tracing across microservices. We configure Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA) driven by actual Prometheus metrics — not just CPU, but request latency, queue depth, or any custom metric your application exposes.
Pod Security Standards (Restricted profile) enforced at the namespace level. RBAC roles scoped to least privilege — developers get exec access in dev namespaces, read-only in production. Network policies that default-deny all ingress and egress, then whitelist only the traffic paths your architecture requires. Secrets encrypted at rest with KMS (AWS KMS, Azure Key Vault, GCP KMS), rotated automatically with External Secrets Operator pulling from Vault or cloud-native secret stores. Image scanning with Trivy in CI, admission controllers (Kyverno or OPA Gatekeeper) that block deployments with critical CVEs or running as root.
Kubernetes makes it easy to over-provision. Teams set CPU and memory requests based on worst-case guesses, then never revisit them. The result: clusters running at 15-25% actual utilization while you pay for 100% of the reserved capacity. We deploy Kubecost or OpenCost for real-time cost allocation by namespace, team, and workload. We analyze actual resource consumption with VPA recommendations, right-size requests and limits, implement cluster autoscaler with appropriate scale-down thresholds, and move batch workloads to spot/preemptible instances. Typical savings: 30-50% reduction in monthly cluster spend without affecting application performance.
Skip the recruiting headaches. Our experienced developers integrate with your team and deliver from day one.
We were managing 14 microservices across a mess of EC2 instances with Ansible and prayer. FreedomDev migrated us to EKS with ArgoCD and Helm in eight weeks. Deployments went from 45 minutes to under 3, rollbacks are instant, and our AWS bill dropped 40% from right-sizing alone. The monitoring stack they set up caught a memory leak in staging before it ever hit production.
A SaaS company running 12 services on a fleet of EC2 instances managed with Ansible playbooks and manual SSH deployments. Deployments take 45 minutes, require a specific engineer, and occasionally break other services due to shared dependencies. We containerize each service with multi-stage Docker builds, deploy an EKS cluster with Terraform, create Helm charts with per-environment values, set up ArgoCD for GitOps deployments triggered by PR merge, and configure HPA to auto-scale services independently based on request volume. Deployments drop from 45 minutes to 3 minutes. Any engineer can deploy. Rollbacks are a single ArgoCD click. Monthly infrastructure cost decreases 35% from right-sizing and spot instance node pools.
A B2B platform serving 200+ enterprise customers that need data isolation guarantees. Rather than running a separate cluster per tenant (which would cost $150K+/month in managed Kubernetes fees alone), we implement namespace-per-tenant isolation with network policies enforcing strict pod-to-pod boundaries, ResourceQuotas preventing any tenant from consuming more than their allocation, and RBAC that scopes tenant admin access to their own namespace. Separate node pools for high-security tenants who require dedicated compute. Istio service mesh for mTLS between all pods, ensuring traffic cannot be intercepted even within the cluster.
A manufacturer with ITAR or CMMC compliance requirements that prohibit certain workloads from running in public cloud. We deploy RKE2 (Rancher's FIPS-validated Kubernetes distribution) on bare-metal servers in their data center, with Longhorn for distributed block storage, MetalLB for bare-metal load balancing, and Rancher for multi-cluster management. Monitoring runs entirely on-prem with Prometheus, Grafana, and Loki — no telemetry leaves the facility. GitOps via ArgoCD pointed at an internal GitLab instance. The team gets the same deployment workflows as a cloud-native shop without violating compliance boundaries.
A development team running Jenkins on a single overloaded VM. Build queues are 30+ minutes during peak development hours. We migrate to Kubernetes-native CI: GitHub Actions or GitLab CI for orchestration, with build agents running as ephemeral Kubernetes pods that scale dynamically with demand. Container images built with Kaniko (no Docker-in-Docker security issues), scanned with Trivy, pushed to ECR or Harbor, and deployed via ArgoCD Application Sets that watch the chart repository. Developers push code, CI builds and scans the image, ArgoCD detects the new chart version and syncs to the staging cluster. Promotion to production requires a PR approval that ArgoCD picks up automatically.