Kubernetes in Production: Lessons from Enterprise Deployments

The Gap Between Demo and Production

Kubernetes has won the container orchestration battle. The CNCF's annual survey shows adoption rates well above 80% among organizations with more than 500 employees. But adoption and production readiness are very different things.

We regularly see enterprises that got Kubernetes running in a few weeks but then spent months dealing with the hard parts: security hardening, multi-tenancy, observability, cost management, and the organizational changes that come with operating a distributed platform.

Here are the lessons that keep coming up.

1. Managed vs. Self-Managed Is Not a Close Call

Unless you have a specific regulatory or technical requirement that forces self-managed clusters, use a managed Kubernetes service. EKS, AKS, and GKE handle the control plane, upgrades, and availability so your team can focus on the workloads running on top.

The argument for self-managed usually boils down to "we want more control." In practice, that control means your team is now responsible for etcd backups, API server availability, certificate rotation, and version upgrades across every cluster. Very few enterprises have the Kubernetes depth on their team to do this well.

The lesson: Default to managed. Self-manage only when you have a documented requirement that managed services can't satisfy.

2. Multi-Tenancy Needs Deliberate Design

Running multiple teams or applications on shared clusters is where most of the complexity lives. Without clear boundaries, one team's resource-hungry job can starve another team's production service.

Namespaces alone are not sufficient isolation. You need resource quotas to prevent any single namespace from consuming the entire cluster. You need network policies to control pod-to-pod communication. And you need RBAC configured so that teams can manage their own workloads without accidentally touching someone else's.

The lesson: Design your multi-tenancy model early. Retrofitting isolation into a cluster that's already running production workloads is painful and risky.

3. Security Is Not Optional (and the Defaults Are Permissive)

Out of the box, Kubernetes is designed for developer convenience, not security. Pods run as root by default. There are no network policies restricting traffic. Service accounts have broad permissions.

The NSA and CISA published a Kubernetes Hardening Guide that should be required reading for any team operating clusters in production. Key areas to address:

• Pod security standards. Enforce restricted or baseline profiles to prevent containers from running as root or escalating privileges.
• Network policies. Default-deny all traffic, then explicitly allow only what's needed. Treat your cluster network like a production network, not a trusted zone.
• RBAC. Follow least privilege. Audit who has cluster-admin access and reduce it aggressively. Most developers need namespace-scoped permissions, not cluster-wide access.
• Image security. Only allow images from trusted registries. Scan for vulnerabilities before deployment. Sign images and verify signatures at admission.

The lesson: Treat security hardening as a prerequisite for production, not something you'll get to later.

4. Observability Requires Its Own Strategy

"We'll figure out monitoring later" is one of the most common mistakes. When something goes wrong in production and you don't have metrics, logs, and traces in place, debugging becomes guesswork.

A solid Kubernetes observability stack covers three pillars:

Metrics. Prometheus plus Grafana is the de facto standard. Monitor cluster health, node resource utilization, pod-level metrics, and application-specific indicators.

Logs. Centralize logs from all pods into a system like Elasticsearch, Loki, or your cloud provider's log service. Make sure logs include enough context (namespace, pod name, container) to be useful during incident response.

Traces. For microservices architectures, distributed tracing through tools like Jaeger or Tempo is essential for understanding request flows across services.

The lesson: Deploy your observability stack before you deploy production workloads. You'll need it sooner than you think.

5. The Organizational Shift Is the Hardest Part

Kubernetes changes how teams work. Developers need to understand pod lifecycles, health checks, and resource requests. Operations teams need to think about cluster capacity planning and upgrade strategies. Someone needs to own the platform.

The most successful enterprise Kubernetes deployments we've seen share a common pattern: a dedicated platform team that owns the clusters and provides a paved road for application teams. The platform team handles upgrades, security policies, and shared infrastructure. Application teams deploy through standardized pipelines and Helm charts without needing to understand the underlying cluster details.

The lesson: Invest in a platform team. Kubernetes without clear ownership becomes everyone's problem and nobody's priority.

Getting It Right

Kubernetes in production is not just a technology problem. It's an infrastructure, security, and organizational design problem. The enterprises that succeed are the ones that treat it as all three from the beginning, rather than solving each one reactively as issues emerge.

If you're early in your Kubernetes journey, focus on getting the foundations right: managed clusters, security hardening, observability, and clear team ownership. The applications can come later. The platform has to be solid first.