Containers solve the packaging problem. Kubernetes solves the operations problem. Getting both right takes more than documentation.

Container adoption in DACH enterprises is no longer early-stage. Most engineering teams have Docker in their workflow and at least one Kubernetes cluster running somewhere. The harder question is whether those clusters are actually being operated well: whether deployments are reliable, resource utilization is defensible, security posture is governed, and the on-call burden on engineers is sustainable. For most teams, the honest answer is no to at least one of those.

Gradion works with teams that have adopted containers and Kubernetes but have not yet operationalized them. That gap looks different in each organization: clusters provisioned manually and never documented with IaC, Helm charts copied from the internet and never reviewed, resource limits unset and nodes that OOM-kill workloads under load, ingress rules accumulating without a governance model. We come in, assess the actual state, and build the operational foundation that turns your Kubernetes investment from a liability into an asset.

We have delivered this for platforms running 99.99% uptime and 50+ daily deployments. The work is engineering, not theory.

WHAT WE DELIVER

Container Strategy and Image Standards

We design your container build standards: base image selection, multi-stage build patterns, image scanning integration, tagging conventions, and registry governance. This is not aesthetic. Bloated images, unscanned base layers, and mutable tags are the vectors for the majority of container-related incidents. We enforce standards in the pipeline, not as guidelines in a wiki that no one reads.

Kubernetes Cluster Management

We provision and harden clusters on AWS EKS, Azure AKS, Google GKE, or on-premises environments. Cluster provisioning is done with Terraform or Pulumi, so every node group, networking decision, and IAM binding is version-controlled and reproducible. We configure namespace isolation, RBAC policies, network policies, pod security standards, and admission controllers to match your compliance requirements. Resource requests and limits are set based on profiling, not guessing. Horizontal and vertical autoscaling is configured with meaningful thresholds.

Helm Charts and Release Management

We design Helm chart structures that work across environments without becoming unmaintainable. Values hierarchies, environment-specific overrides, and chart versioning are defined explicitly. We migrate teams off kubectl apply workflows and onto repeatable, auditable release processes. Where chart complexity grows, we evaluate Kustomize overlays or Helmfile as alternatives, choosing based on your team's operational model rather than tool preference.

Service Mesh and Observability

For teams running microservice architectures, we implement service mesh layers using Istio or Linkerd where traffic management, mutual TLS, and distributed tracing are requirements. We instrument clusters with Prometheus and Grafana for metrics, Loki or the ELK stack for log aggregation, and Jaeger or Tempo for tracing. Dashboards are built around the four golden signals: latency, traffic, errors, and saturation. Alerting is configured to page on symptoms, not on infrastructure noise.

GitOps-Based Deployment

We implement GitOps delivery using ArgoCD or Flux, giving your cluster a declarative, pull-based deployment model. Application state is always reconcilable from Git. Drift is detected and corrected automatically. Rollbacks are git reverts, not emergency kubectl commands under pressure. Multi-cluster deployments, progressive delivery with canary releases, and application set templating are configured where your architecture requires them.

Platform Engineering and Developer Enablement

Operations teams should not be the bottleneck for deployment. We build internal developer platforms that give product teams self-service access to environments, deployment pipelines, and observability tooling within defined guardrails. This reduces the cognitive load on platform engineers and accelerates product delivery without sacrificing operational control. Templates, golden paths, and backstage-style portals are built to match your team structure and delivery cadence.

Proof in Production

HomeToGo, the world’s largest short-term rental marketplace, operates one of the most demanding Kubernetes environments in the European consumer internet market. Gradion built and runs the container platform sustaining 50+ production deployments per day, 99.99% uptime, and 100+ concurrent A/B tests running simultaneously in production. Deployments trigger on merge, traffic shifts progressively, rollbacks are git reverts. The system has run in continuous delivery through sustained platform growth without reliability degradation.

Vietnam’s largest coffee chain - migrated from Docker-based virtual machine deployments to a full Kubernetes cluster architecture. Manual container coordination across VMs was replaced with automated deployment pipelines, eliminating the release risk and operational overhead that came with managing containers at scale outside an orchestration layer.

Technology Stack

Docker, containerd, Kubernetes (EKS, AKS, GKE, on-premises), Helm, Kustomize, ArgoCD, Flux, Istio, Linkerd, Terraform, Pulumi, Prometheus, Grafana, Loki, Jaeger, Tempo, Trivy, Falco, OPA/Gatekeeper

CTA

Share your cluster setup and your biggest operational pain point. We will assess it and come back with a scoped engagement.