18 лютого 2026 р.
Moving from VM-heavy OpenStack estates to Kubernetes can reduce operational friction, but only if the cost model is built before migration work starts. Too many teams begin with cluster design, then discover three months later that network egress, storage IOPS, and duplicated environments have quietly increased the bill.
This guide gives cloud buyers and platform operators a practical model you can run in a spreadsheet in one afternoon. It is deliberately simple: estimate baseline, map what changes with containers, and make three policy decisions early. If you already run workloads on OneCloudPlanet, this is the quickest way to separate real savings from wishful thinking.
1) Start with a clean baseline (last 90 days, not one invoice)
Use 90 days of cost and utilization data from your current OpenStack workloads. One month is often noisy because of releases, load tests, or seasonal traffic.
Track five lines only:
- Compute (vCPU/RAM for application VMs)
- Storage (capacity + performance tier)
- Network traffic (especially north-south egress)
- Backup/snapshots
- Operations overhead (on-call and routine administration time)
Practical example: one retail team we supported had stable compute spend, but their “hidden” cost was storage overprovisioning for databases. Their first migration assumption (“Kubernetes will cut costs by 30%”) was wrong; storage policy changes produced most savings, not the orchestrator itself.
2) Model the container reality, not a perfect architecture diagram
In early planning, teams often underestimate Kubernetes overhead. Add these items explicitly:
- Control plane and platform add-ons (ingress, monitoring, logging)
- Headroom for autoscaling and failure tolerance
- Persistent volumes for stateful services
- Inter-service traffic amplification from microservice calls
Use two scenarios: conservative (20–30% overhead) and optimized (10–15% overhead after tuning). This avoids board-level surprises and gives procurement a realistic range instead of a single number.
If your team is still defining service boundaries, review your microservice assumptions first. This older OCP article is still useful for migration prep: microservice architecture best practices and challenges.
3) Decide three cost policies before any production cutover
Policy A: environment scheduling. Non-production namespaces should sleep outside office hours unless a team marks an active test window. This single policy usually delivers immediate savings.
Policy B: storage classes and retention. Define default classes and snapshot retention up front. Without this, teams choose premium tiers “temporarily” and never come back.
Policy C: ownership tags. Every namespace and major workload needs owner + environment + business service labels. If no owner exists, no budget conversation exists.
For teams already running Kubernetes, OCP’s practical orchestration overview is a good reference for platform responsibilities: Kubernetes orchestration in OneCloudPlanet cloud.
4) Build a phased migration budget (parallel run is the expensive phase)
The most expensive period is usually not “after migration.” It is the overlap period when VMs and clusters run together while data, traffic, and rollback options are maintained.
Use a three-phase budget:
- Phase 1 — Foundation (4–8 weeks): platform setup, observability, baseline controls.
- Phase 2 — Dual run (6–16 weeks): both platforms live, migration waves by service criticality.
- Phase 3 — Consolidation (4–6 weeks): retire unused VMs, rightsize cluster nodes, clean stale volumes.
Make “decommission completion” a formal KPI. Many projects miss savings simply because old resources stay powered on “just in case.”
5) Governance checklist for buyers and operators
Before approving a migration budget, confirm the team can answer these questions clearly:
- What is the current unit cost per customer-facing service?
- What is the expected unit cost after migration in conservative and optimized scenarios?
- Who owns monthly cost reviews and exception approvals?
- Which workloads stay on OpenStack VMs for technical or financial reasons?
- What is the rollback cost if one wave fails?
If any answer is vague, delay large cutovers and tighten the model first. Migration speed is less important than avoiding structural waste.
For broader IaaS planning context, this OCP post can help align stakeholders on service model basics: IaaS vs PaaS vs SaaS.
Bottom line: Kubernetes can improve delivery and resilience, but cost efficiency comes from policy discipline, not tooling alone. Teams that define ownership, storage rules, and overlap-phase controls early usually hit their financial targets within the first two quarters after migration.