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Alerting

As explained in Machine Learning Platform Engineering

Alerting is the process of generating and delivering notifications when monitored application, system, or infrastructure conditions require attention.

Alerting generates and delivers notifications when monitored applications, systems, or infrastructure show failures, degradation, security events, or other conditions requiring intervention. It turns monitoring data into proactive incident management: responsible teams can act before faults cause extended downtime or user impact. section 11.1 section 11.1.4

A production alerting setup typically combines:

  • Prometheus alert rules expressed as PromQL conditions over monitored metrics. section 11.1.4
  • Service-availability checks using the up metric, plus absent when the target or metric disappears entirely. section 11.1.4
  • Alertmanager routing that groups alerts and sends them through configured channels such as email, Slack, or PagerDuty. section 11.1.4

Detecting a missing deployment

A BentoML deployment can trigger ServiceDown when up equals 0 and MissingUpMetric when absent(up{...}) equals 1. Requiring the condition for five minutes and assigning critical severity reduces transient noise while preserving urgent notification. Alertmanager can group alerts by alertname and job, then route them to Gmail with resolved notifications enabled.

How Machine Learning Platform Engineering covers it

How deep it goes
Builds rules, durations, labels, annotations, routing, grouping, and email delivery, but does not detail notification channels beyond configuration examples.
Examples
Uses BentoML uptime rules, absent-metric detection, Gmail routing, grouped notifications, and budget alerts for production LLM costs.
What it assumes
Assumes monitored metrics and logs, while defining uptime checks, absent-metric detection, alert rules, and notification routing.
What you can do after
Operate/configure Prometheus and Alertmanager to detect service failures and route grouped notifications to email.
How it connects
Connects monitoring, metrics, logging, Prometheus, Alertmanager, observability, data drift monitoring, and incident management.

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This explainer was generated by Manning's knowledge graph from the text of Machine Learning Platform Engineering. The section links point to the parts of the book it draws on.