Take back control of your infrastructure.
The OpenMetal team is standing by to assist you with scoping out a fixed-cost model based infrastructure plan to fit your needs, budgets and timelines.
Modern FinOps isn’t just about shaving costs—it’s about giving Finance, Product, and Engineering the same truth about spend, performance, and risk so they can make better decisions faster. That alignment gets dramatically easier when the infrastructure itself is predictable.
OpenMetal’s Hosted Private Cloud—powered by OpenStack and Ceph on dedicated hardware—uses flat, transparent pricing: fixed monthly line items for compute, storage, and networking, with fair 95th-percentile egress above generous included allotments and private east-west traffic included. Because the platform is private by design (customer-specific VLANs with VXLAN support) and not metered per micro-resource, FinOps teams can forecast spend with far greater accuracy while still retaining cloud-like agility.
This article outlines a practical, 30–60–90-day playbook for embedding FinOps on a predictable, flat-rate base. You’ll see what cost-visibility dashboards to build, how to allocate costs by business unit, governance you can enforce without slowing engineers, tagging strategies that actually stick, and real-time alerts that keep budgets intact. We’ll frame each section with what matters most to CFOs, CTOs, and FinOps practitioners.
Why predictable beats purely variable
CFO lens. Variable, usage-metered cloud bills make forecasting hard. You’re modeling not only demand but also the billing behavior of dozens of vendor services. With OpenMetal’s fixed line items (e.g., “3× Cloud Core nodes,” “2× NVMe storage tiers,” “10G commit + 95th egress”), Finance can plan quarterly and annual OpEx with a tighter confidence interval, then model upside with clear step-functions (add a node, add a GPU server, expand storage by X TB).
CTO lens. Predictable infrastructure doesn’t mean static. You still scale—just in coarse, intentional increments (servers, storage tiers, network commits) aligned to capacity and SLOs. That forces better architectural discipline while maintaining speed.
FinOps lens. Forecasts move from fragile regressions to simple unit economics: cost per environment per month, cost per workload per month, marginal cost of a new customer, egress cost under 95th percentile scenarios. Fewer levers, clearer models.
Foundation: the cost objects you’ll track
On OpenMetal, your primary cost objects are:
Compute line items
Dedicated servers or Cloud Core nodes with known CPU, RAM, and local NVMe.Storage tiers
Ceph-backed volumes and object storage by tier (e.g., NVMe-optimized vs HDD/erasure-coded).Networking
Public egress with 95th-percentile pricing beyond included levels; private VLAN/VXLAN traffic included.Add-ons
GPU servers/clusters, additional IPs, backup/replication services, professional services.
These become your “chart of accounts for infrastructure,” the backbone for dashboards, allocation, and governance.
Dashboards that Finance and Engineering should build
Build three layers of dashboards (your BI of choice or Grafana/Looker + data from OpenStack, Ceph, and billing exports):
1) Executive rollup (monthly/quarterly)
- Total infrastructure run-rate (vs budget)
- Capacity headroom: CPU, RAM, storage utilization vs thresholds (e.g., 70% target, 80% yellow, 90% red)
- Egress at 95th percentile: included vs actual, projected overage
- Cost per revenue dollar (or per active customer)—high-level unit economics
- Top 5 cost centers & trend (BU, product, or environment)
CFO takeaway: “Are we on budget? What step-function investments are coming next quarter?”
2) Allocation & efficiency (weekly)
- Cost by business unit, environment, product, and region
- Idle capacity ratio (allocated but unused vCPU/RAM/storage)
- Right-size index: instances with low utilization for N days
- Storage tiering report: % of hot vs warm/cold data, candidates for cheaper tiers
- Egress profile: who drives bursts near 95th peaks
FinOps takeaway: “Where are reallocations or optimizations worth doing this sprint?”
3) Engineering & operations (daily)
- Workload health vs cost: SLO breach risk at current capacity
- Top noisy workloads: spike patterns that push 95th percentile
- GPU utilization: by project; idle GPUs flagged within 24 hours
- Volume efficiency: snapshot sprawl, unattached volumes
CTO takeaway: “What can teams clean up now without risk?”
Tip: Use OpenStack metadata (Nova flavors, Cinder volume attributes, Neutron ports) and Ceph metrics to feed dashboards. Tag resources (see below) so cost rollups are automatic.
Allocation by business unit: showback first, chargeback second
Step 1 — Define allocation keys.
Choose a primary dimension (Business Unit or Product) and secondary (Environment: Prod/Stage/Dev; Region; Project). Compute and storage are allocated by tagged ownership; shared networking can be split by traffic contribution or a simple fixed ratio.
Step 2 — Showback.
Run showback for two cycles before chargeback. Publish BU-level PDFs or Slack digests: “Your OpenMetal infra this month: $X; capacity use: Y%; trends and opportunities.”
Step 3 — Chargeback (if culture supports it).
Move to chargeback when showback is trusted. Finance books internal transfers; teams budget for infra like any other line item. Predictable pricing makes this painless—teams know the cost of adding a server or storage block in advance.
Allocation rules of thumb:
- Dedicated resources → 100% to owning BU.
- Shared clusters → split by tagged vCPU/RAM/volume GB usage.
- Networking egress overage → split by 95th-percentile contributors (by source IP/project).
Unattributed usage → roll into “Platform” cost center; make reducing it a KPI.
Spending governance that doesn’t block developers
Governance should be guardrails, not gates. Implement lightweight policies that map to OpenMetal’s step-function scaling.
Some policy pack examples below:
Capacity thresholds:
- Add compute when sustained CPU > 70% for 7 days or forecast shows breach in 2 weeks.
- Expand storage tier when 80% full for 10 days.
Egress watch:
- Alert when 95th-percentile projection reaches 85% of included allotment; review CDN, compression, regionalization.
GPU discipline:
- Idle GPU > 24 hours triggers reclaim review; > 72 hours requires VP Eng approval to keep.
Change control:
- Infra changes (new nodes, GPU adds, storage expansion) require PR-based approvals in IaC repos; audits stored for compliance.
Environment standards:
- Dev/Stage use smaller flavors; Prod uses hardened images and backup policies by default.
RACI clarity:
- Finance: budget owner, approves step-function increases above $X/month.
- CTO/Platform: capacity plan authority, sets SLOs and guardrails.
- FinOps: reporting, showback/chargeback, policy enforcement, forecasting.
- Product/BU Leads: accountable for their cost center, cleanup backlogs.
- SRE/Engineering: execute IaC changes, tagging, and hygiene.
Tagging strategy that actually gets adopted
Tags fail when they’re optional or too complex. Keep it small, mandatory, and enforced in pipelines.
Minimum required tags (apply to servers, volumes, networks, IPs, and images):
- bu (e.g., commerce, media, platform)
- product (canonical product or service name)
- env (prod, stage, dev, qa, sandbox)
- owner (team alias or Slack group)
- cost_center (Finance code if applicable)
- data_class (public, internal, confidential, regulated)
Optional but useful:
- rev_model (subscription, ads, transactional)
- sla_tier (gold, silver, bronze)
- retention_policy (30d, 90d, 365d)
Enforcement:
- IaC defaults: Terraform/Heat modules require these tags; missing tag = plan fails.
- Admission checks: CI pipeline lints YAML/TF for tag keys/values.
- Drift repair: Nightly job lists untagged or mis-tagged resources; tickets filed automatically.
- Golden images: Bake tags and logging agents into images to reduce human error.
Tag glossary & ownership: Document allowed values in a simple README; FinOps owns the glossary, Platform enforces.
Real-time alerts that matter (and ones that don’t)
Alert fatigue is real. Prioritize alerts that prevent budget misses or SLO risk:
- Capacity: CPU/RAM sustained > 75% or disk > 80% for N hours (per cluster and per BU)
- GPU idle: > 24h idle with cost center = non-R&D
- 95th egress projection: > 85% of included allotment mid-cycle
- Unattached volumes / zombie IPs: existence > 48h outside maintenance windows
- Backup gap: any Prod volume missing snapshot policy
Send to the right place: BU-specific Slack channels for BU alerts; a shared #finops-infra channel for platform-wide signals; PagerDuty or equivalent for capacity/SLO risks. Include remediation links (runbooks, IaC PR templates) in the alert payload.
30–60–90-day FinOps rollout on OpenMetal
Days 1–30: Baseline & visibility
- Inventory & map: Export OpenStack/Ceph inventory; map each resource to a BU/product with a temporary heuristic (owner email, project name).
- Implement minimal tags in Terraform modules; block new resources without tags.
- Dashboards v1: Executive rollup + Allocation & efficiency pages; no more than 10 charts total.
- Showback pilot: Share with 2–3 BUs; gather feedback.
- Set policy thresholds (capacity, egress, GPU idle).
- Quick wins: Delete zombie volumes, right-size obvious outliers, move cold data to cheaper storage tier.
Days 31–60: Governance & optimization
- Automate alerts for thresholds; wire to Slack/Teams.
- Chargeback decision: If culture allows, prepare the process; if not, strengthen showback.
- Egress review: Identify burst drivers; consider CDN, batching, or path optimizations.
- GPU utilization SLO: Define target utilization and reclaim procedures.
- IaC controls: PR-based approvals with change tickets linked; add policy-as-code checks.
Days 61–90: Forecasting & continuous improvement
- Capacity plan: 6–12-month forecast by cluster and BU; align to growth scenarios.
- Budget integration: Finance books infra as fixed line items per BU; establish variance thresholds.
- KPI cadence: Monthly FinOps review with CFO/CTO/BU leads; publish a one-page brief.
- Tag hygiene: Achieve > 98% tag compliance; automate drift repair.
- Playbook library: Right-sizing, storage tiering, GPU scheduling, egress tuning.
Example KPIs to keep everyone honest
Financial
- Forecast accuracy (±%) vs actual by BU
- Cost per revenue dollar / per active customer
- Percent of spend on predictable line items vs variable
Operational
- Capacity headroom by cluster (target bands)
- Tag compliance rate (> 98%)
- Idle resource elimination cycle time (< 48h)
Engineering
- Right-size actions per sprint
- SLO adherence with no unplanned capacity adds
- GPU utilization target (e.g., > 70% rolling 7-day)
Governance templates you can copy
Right-size policy
- Scope: Non-prod first, prod after 2-week bake.
- Trigger: < 20% avg CPU and < 30% RAM over 14 days.
- Action: Downsize one flavor step; verify SLOs for 72 hours.
- Exception: Ticket with justification signed by BU owner.
Storage tiering policy
- Trigger: Volume read IOPS < X for 30 days; data class ≠ regulated.
- Action: Migrate to warm/cold tier during maintenance window.
- Rollback: If P95 latency exceeds Y for 48 hours, revert.
GPU policy
- Trigger: Idle > 24h; non-R&D cost centers.
- Action: Notify owner; reclaim at 72h unless exception approved.
Egress policy (95th)
- Trigger: Projected 95th > 85% of included allotment mid-cycle.
- Action: Review drivers; apply CDN/caching/compression; if justified, approve uplift.
“Predictable” doesn’t mean “unmanaged”
Flat-rate/predictable pricing reduces noise, but FinOps discipline is still essential. Here’s how to keep it sharp:
- Model step-function growth. Everyone knows the cost of adding a node or GPU. Tie those steps to revenue or customer milestones to create a clean ROI narrative.
- Use private networking aggressively. With private VLAN/VXLAN traffic included, architect chatty services to stay private. Reserve public egress for true edge cases and distribution.
- Codify everything. Terraform/Heat for infrastructure; PR approvals for changes; policy-as-code for guardrails.
- Prefer small, frequent cleanups. A 30-minute weekly “hygiene” slot per team beats quarterly fire-drills.
- Tell the story. FinOps is culture change—publish the one-pager monthly, celebrate BU wins, and keep dashboards human.
What this unlocks for CFOs, CTOs, and FinOps
- For CFOs: Budgets you can trust, with fewer surprise deltas. Unit economics tied to business reality. Clean chargeback if you want it.
- For CTOs: Capacity planning that supports SLOs without whiplash. Guardrails that don’t slow shipping. Clear justification when you do need to step up capacity.
- For FinOps teams: Simpler data pipelines, fewer billing anomalies, higher-signal alerts, and a tagging system that sticks. More time for optimization, less time chasing ghosts.
Final word
When the substrate is predictable, FinOps can focus on outcomes instead of detective work. OpenMetal’s flat, transparent pricing—paired with private-first networking and dedicated hardware—gives you the stable base to run real FinOps: shared truth, fast decisions, and spend that scales with intent. Put the dashboards, allocation rules, guardrails, tags, and alerts above into practice, and you’ll turn infrastructure from a cost center everyone tolerates into a planning tool everyone trusts.