Cluster Architecture and Design
Node pool design, networking configuration (CNI selection, network policies, ingress architecture), storage class design, and RBAC framework. Designed for production requirements, not for ease of initial setup.
CLOUD CONSULTING · KUBERNETES
Kubernetes Consulting for Enterprises That Need Container Orchestration Built for Production, Not Just Deployment
Kubernetes is straightforward to install. Running it reliably in production — with the right security configuration, autoscaling, observability, and operational procedures — requires a different level of design. DAM Networks builds Kubernetes environments for production workloads from the outset.
THE PROBLEM
Kubernetes clusters that work in staging become operational liabilities in production when the architecture was not designed for the difference.
Kubernetes adoption in enterprise engineering teams typically starts with a development team that needs faster deployment cycles. A cluster is stood up, applications are containerised, and workloads deploy more quickly than they did before. The cluster goes to production. Within 90 days, the operations team is dealing with node instability, resource contention between workloads, networking issues that only appear under production traffic, and security configurations that were adequate for a development environment but not for a system processing live customer data.
The gap between a Kubernetes cluster that works and one that operates reliably at production load is almost entirely in the initial architecture decisions. RBAC configuration that was simplified for developer convenience becomes a security risk when production service accounts inherit the same permissions. Node pool configuration optimised for development workloads cannot handle the resource patterns of a production database workload running alongside a CPU-intensive processing job. Autoscaling that works at low traffic volumes does not scale quickly enough when production traffic spikes.
DAM Networks designs Kubernetes environments for the production use case from the first cluster node. The development experience is not compromised — but the security, availability, and operational requirements of production workloads are built into the architecture before any workload is deployed.
CAPABILITIES
What DAM delivers across Kubernetes engagements
Security Hardening
Pod security standards, network policy enforcement, secret management with external secret stores, image scanning in the CI pipeline, and admission controller configuration for policy enforcement at deploy time.
Observability and Monitoring
Prometheus and Grafana stack deployment, custom metrics for application SLIs, alerting rules calibrated to production behaviour, and log aggregation architecture. Cluster health is visible before an incident, not only during one.
Managed Kubernetes Operations
Ongoing cluster management covering version upgrades, node pool rotation, certificate rotation, incident response, and capacity planning. Available for EKS, AKS, GKE, and self-managed clusters.
DAM APPROACH
Kubernetes architecture begins with the production requirements — security, availability, and operational overhead — before any cluster is provisioned.
DAM starts every Kubernetes engagement with a requirements session covering the workloads that will run on the cluster, their resource profiles, their isolation requirements, their data classification, and the operational team that will manage the environment day-to-day. The cluster architecture follows from those requirements — node pool composition, namespace structure, network policy design, and RBAC model are all derived from what the workloads need and what the operations team can sustainably manage.
For existing clusters, DAM conducts a configuration audit before any changes are made. The audit covers security posture, resource configuration, networking, and observability against a production-readiness checklist. The findings are prioritised by risk level and remediated in order — critical security issues first, then availability risks, then operational inefficiencies.
Managed operations includes cluster version upgrade management, which is where many enterprises accumulate technical debt. Kubernetes releases a new minor version every four months. Clusters that fall more than two versions behind lose access to security patches. DAM's upgrade process keeps clusters current with tested upgrade paths that do not require workload downtime — node pool rotation rather than in-place upgrades for production environments.
RELATED SERVICES
Services that work alongside Kubernetes Consulting
WORK WITH DAM NETWORKS
If the Kubernetes environment is creating more operational overhead than it is removing, the architecture needs to be reviewed before the next incident.
DAM Networks designs and manages Kubernetes environments for enterprise engineering teams on EKS, AKS, GKE, and self-managed clusters. Engagements begin with the production requirements — not the development team's current setup.
FREQUENTLY ASKED QUESTIONS
Questions about Kubernetes architecture and operations
For enterprise organisations, managed Kubernetes services are almost always the right choice. EKS, GKE, and AKS handle control plane management, including upgrades, availability, and scaling — removing the most operationally demanding part of running Kubernetes. The cost of a managed control plane is small relative to the engineering time required to manage one. Self-managed clusters are appropriate for organisations with specific compliance requirements that prevent use of managed services, or those with Kubernetes expertise on staff who need control over the control plane configuration.
Resource requests should reflect the typical sustained consumption of the workload under normal production load. Limits should be set at the maximum acceptable consumption before the workload is terminated and restarted. Both values require measurement from a production-representative load test — setting them from intuition or defaults produces either over-provisioned clusters (requests too high) or workloads that are terminated under normal peak traffic (limits too low). VPA (Vertical Pod Autoscaler) in recommendation mode is a useful way to gather request data from a running workload before hardcoding values.
Overly permissive RBAC is the most common and consequential security issue in enterprise Kubernetes clusters. Service accounts with cluster-admin binding, pods running as root without a read-only root filesystem, and absence of network policies allowing unrestricted east-west traffic between namespaces are the three configurations that appear most frequently in cluster audits. Each one represents a significant blast radius if a workload is compromised. Fixing them requires deliberate RBAC redesign, not a quick patch — which is why they accumulate unaddressed in clusters that were not designed with security requirements from the start.