Kubernetes has brought predictable deployment and scaling, but in most mid-market shops the storage side is still a mess of YAML, manual ops, and hidden costs. Teams push StorageClass and PVC manifests into Git, but those YAML files are often a band-aid over deeper problems: inconsistent reclaim policies, overprovisioned volumes to avoid outages, ad hoc snapshot scripts, and little visibility into who controls data lifecycles. The result is rising infrastructure spend, risky refresh cycles, and compliance gaps that surface during audits.

Traditional SAN/NAS approaches — designed for LUNs and human ticketing — don’t map cleanly to cluster-native patterns. They leave operators stitching together CSI drivers, cron-based backups, and runbooks. That increases error rates from YAML drift and misapplied StorageClass parameters, and it forces conservative over-allocation that kills margins for MSPs and inflates CAPEX for customers.

The sensible response is a shift from storage-as-hardware to an intelligent data platform that understands Kubernetes semantics. Platforms like STORViX plug into CSI, enforce policy from the manifest layer, automate lifecycle tasks (snapshots, retention, tiering), and provide the cost and compliance controls you actually need. That doesn’t eliminate YAML — it makes YAML a single source of truth for intent, while removing the manual plumbing that creates risk and cost leakage.