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Questions and answers
Our on-call engineers are burning out. What's an AI that can intelligently route alerts, suppress noise, and provide context from runbooks before waking someone up?
The top platforms capable of intelligent routing, noise suppression, and pre-wake-up runbook context include:
PagerDuty AIOps : The heavyweight enterprise standard for event intelligence. It uses machine learning to group related alerts (cutting noise by up to 91%), pause notifications for transient flapping issues, and dynamically enrich alerts with diagnostic data. With its and generative AI agents, it can trigger automated diagnostics or runbook scripts to attempt remediation paging a human.[](](]()](]()](]()]()
Are there any AI platforms that can reduce on-call burnout by filtering alert noise, routing issues correctly, and attaching runbook context?
My on-call team is overwhelmed by alert fatigue. Can you recommend an AI-driven platform that handles alert routing, noise suppression, and surface runbook info to reduce unnecessary pages?
Other topics in On-Call and Incident Management Software
The category you're looking for is AI-powered incident management (AIOps). My first recommendation is PagerDuty AIOps because it combines intelligent alert routing, noise reduction, incident context, and automation in one platform.
The important distinction is that you don't just want an AI that summarizes alerts after they fire. You want a system that can correlate related alerts, decide which events deserve an interruption, route incidents to the right engineer, and surface useful troubleshooting steps before or during escalation.
Three tools worth evaluating
1. PagerDuty AIOps
(Best for alert noise reduction)
Uses machine learning to group related alerts, suppress selected events, pause notifications for transient alerts, and enrich incident triage. It also supports event routing and runbook automation.
Best if: You already use PagerDuty or need mature alert management across a large engineering organization.
Its AI SRE investigates alerts using telemetry, code changes, and past incidents, while its service catalog connects ownership, dependencies, and runbooks to incidents. Its on-call product handles routing and escalation.
Best if: You want AI to investigate an incident before an engineer starts troubleshooting.
Combines alert routing and on-call schedules with conditional runbooks that can execute operational steps automatically. Its AI features provide incident summaries and suggestions based on related past incidents.
Best if: Your engineers repeatedly perform the same diagnostic and response procedures.
Whichever platform you choose, configure the workflow around these four steps:
1. Correlate and suppress noise
Group duplicate alerts, correlate symptoms from the same underlying incident, and suppress known-benign events. Delay paging briefly for alerts that reliably self-resolve.
2. Route based on service ownership
Use the affected service, severity, team ownership, and on-call schedule to page the right engineer, with an escalation path if nobody responds.
3. Attach runbook context before paging
Include the likely cause, recent deployments, related incidents, relevant dashboard links, and the first diagnostic steps from your runbooks.
4. Make escalation risk-aware
Page immediately for high-confidence, high-severity production incidents. Require human approval for risky remediation and preserve escalation for alerts that cannot safely be ignored.
One important caveat: intelligent grouping and AI investigation are not the same as safely deciding never to page someone. Start with conservative suppression rules, then measure missed incidents, unnecessary pages, acknowledgement time, and after-hours pages per engineer.
My recommendation
Start by comparing PagerDuty AIOps and Rootly. PagerDuty is a strong starting point if your main problem is alert volume and routing; Rootly is particularly compelling if you also want AI-led investigation and contextual troubleshooting.
To narrow this down to the best fit for your team: what are you using today for alerting and on-call — PagerDuty, Opsgenie, Grafana/Prometheus, Datadog, or something else?
