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Rabbit for FinOps & Finance

Auto-optimize and attribute BigQuery spend

Rabbit models BigQuery commitments from real usage, raises coverage gradually inside the limits you set, catches anomalies before the monthly close, and maps every dollar back to the business. You approve the plan. Rabbit runs it.
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The challenge

BigQuery spend nobody can explain

Commitments get sized once and drift out of step with real usage. Anomalies show up at month-end close instead of the moment they happened. Chargeback and showback stall because labels are inconsistent across projects, so finance can't map BigQuery spend back to the teams that own it.

Sparkle icon for automation illustrationThe Solution

Planning, guardrails, and attribution as one system

Rabbit plans commitments from real usage, catches anomalies before the monthly close, and maps every dollar to the business. Automated purchases and caps run only inside the guardrails and approval paths you set.

platform capabilities

How Rabbit helps

Automated optimization, engineering guardrails, and drift visibility at scale

Govern

01

Plan commitments, enforce caps, and map every BigQuery dollar to the business.

Rabbit's Commitment Planner models slot and spend commitments from real usage. CUD Automation raises coverage gradually with weekly micro-purchases instead of one large lock-in. Hard spend caps by user, label, or query block runaway jobs before they run. Rabbit Labels turn project and GCP labels into finance-ready chargeback and showback views, without re-tagging every pipeline.
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Observe

02

Anomaly detection and attribution-ready cost views, not a surprise on the monthly bill.

Rabbit's forecast model flags spend spikes and linear drift near real-time, with sensitivity you can tune as your team learns what matters. Weekly and monthly digest emails keep finance aligned without logging into a dashboard, and cost insights drill from account rollups down to the query, project, or label behind a movement.
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Automate

03

Reservation and pricing automation, measurable savings.

Rabbit's Reservation Optimizer and the Job-level Pricing Model Optimizer keep every workload on the right pricing model automatically, so the usage data feeding your commitment plans and attribution views stays clean and current, not stale from manual reviews.
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Customer stories

Savings finance can plan around

Rightsized commitments commonly deliver 20-50% savings, depending on starting coverage and usage patterns.

How Lufthansa Group Cut BigQuery Costs by 50% with Rabbit

"Rabbit helped us to reduce the BigQuery costs by 50%, which is great because BigQuery cost is one of our biggest cost drivers in the project."

— Kunal Walia, Principal Solution Architect, Lufthansa Group

Lufthansa Group logo

52% less BigQuery spend. Reservations and autoscaler tuned together.

Lufthansa Group cut their BigQuery costs in half with Rabbit's Reservation Planner and automated autoscaler optimization.

52%

BigQuery spend reduction

30%

savings from autoscaler automation

32%

reservation planning savings

Read the case study

See where your BigQuery commitments and spend need attention

Start with a metadata-only assessment. See where commitments are misaligned, which anomalies are worth investigating, and how spend maps to your business.

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Calculate your savings

FAQ

Rabbit gives finance and platform teams shared controls: commitment planning from real usage, hard spend caps by user, label, or query, near real-time anomaly detection, and attribution through Rabbit Labels. Instead of reacting to the monthly bill, finance gets forecasts, guardrails, and chargeback-ready views throughout the month.

Rightsized commitments commonly deliver 20-50% savings, depending on current coverage and usage patterns. This is a projected range, not a guaranteed average. At Lufthansa Group, reservation planning alone cut BigQuery costs by 32%, reaching 52% total BigQuery savings once combined with automated slot tuning. Book a demo for a metadata-only assessment of your commitment fit.

Rabbit uses a forecasting model on 90 days of historical usage to build an expected-spend baseline, then flags spikes and linear drift as they happen, by project, service, account, or label. Alerts go out by email or Pub/Sub, with tunable sensitivity so your team can mark false positives.

Rabbit maps virtual labels from projects and existing GCP labels so spend rolls up to business units, teams, or any dimension finance needs. That gives you chargeback- and showback-ready cost allocation across projects without re-tagging every pipeline by hand, and it pairs with label-level anomaly alerts in Observe.

Not without your approval path. CUD Automation can raise coverage gradually through weekly micro-commitment purchases instead of one large lock-in, but you approve the automation path before Rabbit purchases anything. Commitment Planner recommendations come first; automated buying is opt-in.

Reservations don't natively forecast per-query cost the way on-demand bytes-scanned pricing does. Rabbit estimates slot-based query cost in advance, so daily, weekly, and monthly budgets by user or label, plus query-level thresholds, can warn or block a job before it runs, not after it shows up on the bill.

No. Rabbit is a BigQuery optimization platform with FinOps capabilities (commitment planning, spend caps, and attribution) alongside the feature sets described on the Automate, Observe, and Build pages. It is built for teams optimizing BigQuery specifically, not as a general multi-cloud FinOps category tool.

Yes. Rabbit is a Google Cloud Partner, listed on Google Cloud Marketplace. Finance can transact through your existing GCP vendor relationship instead of onboarding a new vendor: the cost appears as a single line item on your GCP bill and counts toward your committed Google Cloud spend.
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Get in touch to start saving

We help data teams cut BigQuery costs by 32% on average and see exactly where every slot hour goes.
The autonomous engine for BigQuery cost and performance
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