A data scientist running ML training jobs on PAI that read from RDS gets comprehensive pipeline monitoring where PAI job failures and GPU bottlenecks trigger urgent Twilio SMS/WhatsApp alerts to on-call engineers, while RDS slow queries and ECS infrastructure metrics are bundled into structured Resend email incident reports for stakeholders — all orchestrated through EventBridge rules that route alerts by severity and audience.
A data scientist running ML training jobs on PAI that read from RDS gets comprehensive pipeline monitoring where PAI job failures and GPU bottlenecks trigger urgent Twilio SMS/WhatsApp alerts to on-call engineers, while RDS slow queries and ECS infrastructure metrics are bundled into structured Resend email incident reports for stakeholders — all orchestrated through EventBridge rules that route alerts by severity and audience.
See _combos/ml-pipeline-monitoring-with-eventbridge-alerts-7ab363.
See _combos/full-stack-observability-with-multi-channel-aler-7b61ca.
See _combos/ml-training-pipeline-end-to-end-monitoring-7e87d8.
See _combos/full-stack-monitoring-with-multi-channel-alert-o-8e321d.
Q: How are PAI training failures and GPU bottlenecks alerted to on-call engineers? A: PAI job failures and GPU bottlenecks trigger urgent Twilio SMS and WhatsApp alerts directly to on-call engineers. This ensures rapid notification for critical training interruptions.
Q: How are RDS slow queries reported to stakeholders during training? A: RDS slow queries are bundled into structured Resend email incident reports for stakeholders. These reports also include ECS infrastructure metrics for comprehensive visibility.
Q: How does EventBridge route ML pipeline alerts? A: EventBridge rules orchestrate and route all ML pipeline alerts by severity and target audience. This centralized routing ensures appropriate prioritization across engineering and stakeholder teams.