FinOps That Doesn’t Slow You Down

Signals You Might Need FinOps Help

• High bill, low elasticity; owners can’t explain this month’s spikes
• Tagging coverage < 70%; budgets exist but no one gets alerted
• Idle storage/IPs/DBs linger because “someone might use it”
• Commitments under-utilised; vendor options unclear
• No single rhythm across cloud, hosted, and on-prem spend

What We Do (Plain Terms)

1) Make spend visible

Clean tags, owners, budgets, anomaly alerts. Unit costs by product/env so teams see the slope and act.

2) Land quick wins

Rightsize hotspots, schedule-to-zero, kill idle/orphaned resources, set storage lifecycle. Savings in days, not quarters.

3) Put guardrails in the background

Policies that enforce themselves — tagging in CI/IaC, budget alerts to owners, exception approvals, showback.

4) Tune architecture & commitments

Fix costly patterns (egress, chatty services). Buy commitments where utilisation is predictable — with guardrails.

30 Days to Visible Savings

1. Days 1–5: Baseline run-rate, top 10 spenders, tag coverage; set budgets/alerts.
2. Days 6–10: Rightsize & schedule top 5 clusters/VMs; storage lifecycle; remove idle/orphans.
3. Days 11–20: Commitment plan (SP/RI/CUD) with utilisation guardrails and approvals.
4. Days 21–30: Dashboards live; showback/chargeback; monthly cost WBR started.

Operating Cadence (Monthly WBR)

• Run-rate vs budget → deltas → owners → dates
• Anomalies and spikes → RCA → playbook action
• Commitment coverage & utilisation → adjust plan
• Top 5 “next best moves” per team → closed next review

Purchasing & Commitments

We target predictable baseload with Savings Plans/RI/CUDs and leave headroom for change. Guardrails ensure utilisation is tracked and no one over-commits. Vendors are aligned to measurable outcomes, not vanity discounts.

Architecture Levers That Move Cost

• Compute: rightsizing, autoscale, spot/fleet, schedule-to-zero
• Storage: tiering, lifecycle, compression, snapshot hygiene
• Data transfer: placement, caching, peering, CDN; avoid accidental egress
• Patterns: queues/caches to flatten peaks; serverless where it wins

See Cloud foundations and Hosting for venue decisions when hyperscale isn’t the best fit.

Chargeback/Showback That Teams Respect

Owners see what they spend and why. Budgets are enforced in tooling, not email. We report unit costs that map to outcomes (per order/session/model run) and keep the backlog of cost moves short and closed.

Databricks: Quick Wins Without Slowing Delivery

• Right-size clusters & jobs; pools and autoscale with sensible bounds
• Photon where it helps; checkpointing & caching to cut recompute
• Job orchestration to avoid zombie runs; visibility of DBU burn by team

Deep dive: Databricks Cost — Quick Wins.