2.13.1 Analytics — Platform Analytics — Usage and Performance

Platform Analytics provides a unified view of how the system is used and how it performs across tenants, modules, and time. Metrics are collected in a consistent, low-overhead manner and aggregated into queryable datasets suitable for dashboards, reports, and automated monitoring.

Metrics Collection Model

Analytics events are emitted by modules using a standardized schema. Collection is asynchronous to avoid impacting user-facing latency.

Collected dimensions typically include:

Tenant and organization identifiers

Module and feature identifiers

Event type and action

Timestamps and execution context

Example event emission:

event(new AnalyticsEvent([ 'tenant_id' => tenant('id'), 'module' => 'inbox', 'action' => 'message_sent', ]));

Aggregation and Storage

Raw events are aggregated into time-series and summary tables optimized for read-heavy workloads. Aggregation windows are deterministic and reproducible.

Aggregation supports:

Hourly and daily rollups

Per-tenant and cross-tenant views

Module-level and feature-level breakdowns

Example rollup job:

AnalyticsAggregator::daily()->run();

Usage Metrics

Usage metrics describe how features are consumed rather than how they perform.

Common usage indicators:

Active users per period

Messages sent and received

Content created or published

Automation executions

These metrics inform capacity planning, billing enforcement, and product decisions.

Performance Metrics

Performance metrics capture system behavior under load.

Tracked indicators:

Request latency

Queue processing time

Job failure rates

Resource utilization

Example latency capture:

$timer = microtime(true); $service->execute(); Analytics::latency('service.execute', microtime(true) - $timer);

Querying and Dashboards

Analytics data is exposed through read-optimized queries used by dashboards and exports. Queries are scoped and permission-aware.

Example query:

Analytics::query() ->forTenant(tenant('id')) ->where('module', 'notifications') ->sum('count');

Retention and Data Governance

Analytics retention follows tenant-level policies. Raw events may be expired earlier than aggregated data to balance insight depth and storage cost.

Retention guarantees:

Predictable expiration

No silent truncation

Audit-friendly aggregation

Security and Isolation

All analytics data is tenant-scoped by default. Cross-tenant analytics is restricted to authorized system roles only. Sensitive identifiers are hashed or omitted where not required.

Access to analytics APIs and dashboards is enforced through role-based permissions.