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A large ecommerce company has deployed a foundation model (FM) to generate product descriptions. The company's engineering team monitors technical metrics such as token usage, latency, and error rates by using Amazon CloudWatch. The company's marketing team tracks business metrics such as conversion rates and revenue impact in its own systems. The company needs a unified observability solution that correlates technical performance with business outcomes. The solution must provide automatic alerts to stakeholders when operational metrics indicate degradation. The solution must provide comprehensive visibility across both technical and business metrics. Which solution will meet these requirements?
: Amazon CloudWatch provides the most integrated path for unifying technical and business metrics. By importing business metrics into CloudWatch (via custom metrics or metric streams), teams can build custom dashboards that provide a single pane of glass for both system health and conversion performance. Composite alarms allow stakeholders to be notified only when multiple conditions are met (e.g., high latency and dropping conversion rates), reducing alert fatigue. Applying anomaly detection to these metrics is essential for GenAI workloads because performance baselines can shift subtly; CloudWatch can automatically detect these deviations and trigger alerts through Amazon SNS. This solution provides comprehensive correlation and automated alerting with less operational complexity than managing external visualization servers (Option B) or multi-service analytics pipelines (Option C).
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