bigquery-query-cost-watch

Operator control plane for BigQuery query-cost posture, bytes-scanned spikes, slot pressure, attribution drift, telemetry gaps, and optimization sequencing.

Production status

Aspect	Status
Deploy	Static prerender -> https://bigquery.kineticgain.com/
Data posture	Synthetic INFORMATION_SCHEMA and billing-export samples only; no project identifiers, dataset IDs, or live query logs are committed

Why this matters

• BigQuery spend gets dangerous when scan spikes, partition misses, slot contention, and unlabeled workloads stay trapped in raw exports instead of one operator-readable surface.
• Recruiters looking for BigQuery / FinOps / data platform / optimization proof should see a real operator dashboard, not a keyword page.
• This repo turns BigQuery usage and optimization drift into a control plane for scan containment, reservation hygiene, attribution trust, telemetry continuity, and workload-rightsizing posture.

Why this matters (KG Embedded tie-back)

This repo demonstrates the query-cost and optimization-control-plane primitive for Kinetic Gain Embedded: workload snapshots, bytes-scanned evidence, attribution hygiene, and remediation packets in one operator surface. Kinetic Gain Embedded extends this pattern into productized in-app dashboards where platform, FinOps, and analytics teams need evidence-rich cost governance without exposing raw admin consoles or live warehouse credentials.

What it shows

• query-lane visibility for scan efficiency, slot governance, attribution hygiene, and telemetry freshness
• cost-risks detection for bytes-scanned spikes, partition misses, reservation drift, stale snapshots, and export gaps
• optimization-posture packets that tie owner, blocker, timing, and completeness together
• offline-safe analysis of captured BigQuery usage exports
• recruiter-facing BigQuery / FinOps / data-platform proof that complements the Microsoft, AWS, GCP, and reporting lanes

Product depth

This is not a billing-console screenshot. It is a buyer- and operator-readable FinOps surface for teams that need to explain why warehouse spend changed, which workloads caused it, and what can be optimized without breaking analytics delivery.

• Buyer value: gives data-platform, FinOps, analytics engineering, and finance leaders a compact answer to "where are query costs leaking, who owns the workload, and what can we save before the next forecast or chargeback review?"
• Technical proof: parses synthetic BigQuery workload snapshots, reservation signals, labels, export freshness, and query-risk observations into routes, JSON APIs, CLI output, screenshots, and optimization packets.
• GTM story: positions Kinetic Gain as the layer between raw warehouse telemetry and executive decisions about margin leakage, data-platform efficiency, owner accountability, and analytics reliability.

What these repos have in common

The BigQuery cost surface follows the same Kinetic Gain pattern used across cloud, identity, revenue, and regulated-infrastructure repos:

• a risk signal that turns raw platform telemetry into a readable operating weakness
• an owner context that keeps spend, workload, or control accountability attached to a role
• an evidence packet that can support audit, diligence, board, or operating-review conversations
• a next action that converts "we should optimize" into a concrete containment or remediation path

Operating workflow

1. Export or model BigQuery job, reservation, label, and billing-export snapshots.
2. Run the analyzer locally or in CI against captured JSON payloads.
3. Review query lanes, cost risks, and optimization posture before forecast, chargeback, or migration decisions.
4. Use the static site and JSON endpoints as a buyer-readable artifact for FinOps review, data-platform governance, or portfolio diligence.

Routes

• /
• /query-lane
• /cost-risks
• /optimization-posture
• /verification
• /docs

API

• /api/dashboard/summary
• /api/query-lane
• /api/cost-risks
• /api/optimization-posture
• /api/verification
• /api/sample

Screenshots

CLI

npx bigquery-query-cost-watch fixtures/bigquery-query-hotspots.json `
  --format markdown `
  --fail-on-high

Validation

• npm run verify
• npm run prerender
• npm run render:assets

Local development

cd bigquery-query-cost-watch
npm install
npm run dev

Then open:

• http://127.0.0.1:5524/
• http://127.0.0.1:5524/query-lane
• http://127.0.0.1:5524/cost-risks
• http://127.0.0.1:5524/optimization-posture

Packaging

Item	Value
License	AGPL-3.0-or-later
CNAME	bigquery.kineticgain.com
Live site	https://bigquery.kineticgain.com/
Deploy	Static prerender -> GitHub Pages

Docs

• docs/KINETIC_GAIN_EMBEDDED.md

Related

• gcp-billing-anomaly-router — GCP cost anomaly routing lane
• regulatory-reporting-mart — reporting and warehouse proof
• snowflake-cost-governance-studio — warehouse cost governance on Snowflake

Part of the Kinetic Gain Suite

Operator surface in the Kinetic Gain Suite — a portfolio of buyer-readable control planes spanning security posture, compliance evidence, data-platform governance, FinOps, and operator workflows. See the suite index for related surfaces. Apex: kineticgain.com.