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How to Build GDPR-Compliant AI Agent KPI Dashboards with Metrics and Logs

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Engineering guidance for gaming AI-agent admin dashboards recommends using pre-aggregated metrics for KPI charts and structured logs for incident investigation, rather than relying on a single storage system for both. Metrics suit recurring, bounded questions like p95 latency by release, while logs preserve the event-level detail needed to reconstruct why a specific game session behaved unexpectedly. Rollback safety is framed as a release requirement, meaning teams must retain the measurements that justified a change even after reverting it. For EU-based SaaS teams, the approach also addresses GDPR compliance by classifying data fields upfront — separating aggregate metrics from personally identifiable content — rather than applying privacy labels after implementation. A pre-release signal catalog defining each metric's name, unit, dimensions, freshness target, and rollback question is recommended to avoid the common mistake of adding charts simply because data is available.

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How to Build GDPR-Compliant AI Agent KPI Dashboards with Metrics and Logs · ShortSingh