Overview#
An operations manager at a financial intelligence unit needs to know whether her team's caseload is growing faster than their capacity to clear it, and whether the platform processing their transaction feeds is keeping pace. She needs that picture updated continuously, not in a weekly report. The Operational Analytics module tracks 500+ operational metrics across system performance, investigation throughput, and platform health, surfacing the numbers that matter to operations managers, service delivery leads, and infrastructure teams in real time.
When something drifts outside normal bounds, AI-powered anomaly detection flags it before it becomes visible to end users. Threshold alerts reach the right team through the right channel, and correlated alert grouping keeps the noise down so genuine incidents stand out.
Key Features#
- 500+ operational metrics covering system performance, investigation throughput, transaction processing, and platform health
- Real-time metric collection with sub-second data freshness for operational monitoring, so dashboards reflect what is happening now
- AI-powered anomaly detection that identifies unusual patterns and emerging issues before they cross threshold boundaries
- Threshold-based alerting with configurable rules, escalation paths, and notification channels suited to different team structures
- Custom operational dashboards for team-specific and function-specific monitoring views
- SLA tracking with automated monitoring of service level agreement compliance, including breach notifications with sufficient lead time to respond
- Predictive capacity planning that uses current growth trajectories to forecast resource needs before demand outstrips supply
- Time-series analysis enabling historical comparison and trend identification across all metric categories
- Metric categorisation spanning system performance, investigation metrics, API performance, queue depth, cache hit rates, and network metrics
- Dimensional metric tagging for flexible grouping, filtering, and drill-down analysis by team, system component, or data source
- Alert correlation that groups related alerts to reduce noise and surface root causes rather than symptoms
- Operational reporting with scheduled metric summaries and performance trend analysis for weekly briefings and management reviews
- Configurable data retention policies balancing analysis depth with storage cost
Use Cases#
- System Health Monitoring: Operations teams monitor platform health in real time, with anomaly detection alerting them to emerging issues before they affect analysts or investigators
- Investigation Performance Tracking: Management tracks caseload throughput, resolution times, and analyst productivity for resource allocation and capacity decisions
- SLA Compliance Monitoring: Service delivery teams ensure compliance with contractual service level agreements through continuous automated monitoring, with early warnings before breaches occur
- Capacity Planning: Infrastructure teams use predictive analytics to forecast resource requirements and plan scaling well ahead of demand peaks
Integration#
- Connects with system monitoring, alerting, and performance infrastructure for comprehensive data collection
- Compatible with executive dashboard and reporting systems for metric aggregation and presentation
- Supports real-time metric streaming through subscription-based data delivery mechanisms
- Role-based access controls for metric visibility and alert configuration
- Complete audit logging of alert acknowledgments and operational responses
- Multi-tenant isolation ensuring organisational metric data separation
Open Standards#
- GraphQL (June 2018 specification): All analytics queries, mutations, and live subscriptions are exposed through a typed GraphQL API, allowing clients to request exactly the metric fields they need.
- RFC 6455 (WebSocket Protocol): Real-time metric streaming and live dashboard updates are delivered over persistent WebSocket connections, with GraphQL subscriptions multiplexed over the same transport.
- IEEE 1366 (Guide for Electric Power Distribution Reliability Indices): Reliability metrics (SAIDI, SAIFI, CAIDI, ASAI) are calculated using IEEE 1366 formulae and compared against nationally benchmarked targets derived from EIA Form 861 data.
- RFC 7519 (JSON Web Tokens) with OAuth 2.0: Every analytics and reporting API operation requires a verified RS256 JWT issued by the platform's authorisation service; access tokens are resolved via JWKS endpoint before any query executes.
- ISO 8601 / RFC 3339 (Date and Time Formats): All metric timestamps, time-series window boundaries, and scheduled report timestamps are serialised and parsed in ISO 8601 / RFC 3339 format.
- RFC 4122 (UUID): Universally unique identifiers conforming to RFC 4122 are assigned to every monitor, report, analytics session, and alert, ensuring stable cross-system references.
- JSON (ECMA-404 / RFC 8259): All metric payloads, alert configurations, analytics templates, dimensional tags, and export data are serialised as JSON over both REST and GraphQL transports.
Last Reviewed: 2026-02-05 Last Updated: 2026-04-14