Use Cases

Open Spanner is useful whenever your product needs a trusted record of usage: billing, limits, customer reporting, operations, audits, or internal analytics. The core pattern is the same across use cases:

Define a meter for the thing being measured.
Send usage events from trusted backend code.
Add dimensions for the fields you need to filter, group, export, or explain.
Query buckets, breakdowns, and events when you need totals or detail.

Common Patterns

API Request Metering

Track request volume by endpoint, method, status, and region.

AI Token Usage

Measure token consumption by model, provider, operation, and cache path.

Storage Usage

Report capacity usage by tier, region, and resource type.

Active Users

Meter seats, workspaces, or active user counts over time.

Background Jobs

Track async work by queue, status, and worker region.

Feature Usage

Understand which product features customers actually use.

Historical Backfill

Import older usage safely with stable idempotency keys.

In-Doc Examples

Each use-case guide includes the meter definition, usage payload, and the dimensions that matter for that scenario.

Use case	Example
API request metering	Create an API request meter and record request usage
Active users	Record active user activity or seat snapshots
AI token usage	Meter model/provider token consumption
Storage usage	Record storage capacity snapshots
Background jobs	Track queue throughput and job outcomes
Feature usage	Track product feature adoption
Historical backfill	Import historical events safely

For backend services that continuously emit usage over gRPC, start with stream-native examples:

Stream use case	What it records
Device telemetry	High-frequency device readings grouped by device, fleet, and region.
WebSocket sessions	Session duration or connection counts emitted as sessions open and close.
Queue consumer throughput	Message handling volume grouped by queue, outcome, and worker region.