Top 5 hard-earned lessons from the experts on managing Kubernetes

1. Operational overhead catches teams off guard Resources for operational overhead: 2. Hidden corners : Security issues put clusters at risk Default settings Network policy and namespace isolation Containers and the images you run in them Resources for Kubernetes security: 3. Scaling challenges that stall growth and agility The cost of node scaling The right metrics for pod scaling Resources for scaling Kubernetes: 4. Talent acquisition: High talent costs and skill gaps in Kubernetes expertise Resources for talent acquisition: 5. Technical debt piling up faster than teams can manage Ongoing upgrades A shifting tooling landscape Resources for managing tech debt: Bonus lesson: Not every workload belongs on Kubernetes Resources for managing Kubernetes: Bonus lesson: Policy enforcement Resources for policy enforcement: Building reliable, secure, and efficient Kubernetes Posted on November 18, 2025 by Stevie Caldwell, Tech Lead at Fairwinds CNCF projects highlighted in this post Kubernetes has transformed how modern organizations deploy and operate scalable infrastructure, and the hype around automated cloud native orchestration has made its adoption nearly ubiquitous over the past 10+ years. Yet behind the scenes, most teams embarking on their Kubernetes journey quickly encounter operational complexity, configuration challenges, and costly maintenance that few vendors highlight. Drawing from years of real-world experience architecting, building, and maintaining Kubernetes, we recently hosted a webinar sharing five hard-earned lessons to help organizations get started using the container orchestration tool. In this post, we’ve paired each lesson with useful resources and examples of how to navigate managing Kubernetes at scale, whether supporting your own teams, deploying across multiple clusters, or evaluating managed Kubernetes offerings. The Kubernetes community knows that spinning up a cluster is straightforward, especially if you use a managed provider such as AKS , EKS , or GKE. But in reality, running a production environment means managing all the hidden add-ons : DNS controllers, networking, storage, monitoring, logging, secrets, security, and more. Supporting internal users (dev teams, ops, and data scientists) adds significant overhead for any company running Kubernetes.