Squadcast pairs ML alert grouping with SLO-aware escalation.
Squadcast runs ML-based Intelligent Alert Grouping across observability sources to collapse related alerts into single incidents, layers AI-generated incident summaries on top, and uses Auto Pause Transient Alerts to suppress flapping ephemeral alerts. SLO dashboards link incident response back to reliability engineering: incidents that breach an SLO escalate faster than ones inside tolerance.
Who it's for. On-call teams of 5 to 30 engineers running multi-cloud infrastructure who want incident management tied to their observability stack. Scenario: 50 alerts fire across 10 services, Squadcast groups them into 2 incidents, identifies one as imminent SLO breach, and auto-escalates that one to senior SRE while routing the other to the regular on-call rotation.
Tradeoffs. Acquired by SolarWinds in 2025, which raises long-term independence questions. AI features are additive rather than core; the platform works without them and ML grouping is decent but less aggressive than PagerDuty AIOps. SLO dashboards require manual definition; no auto-discovery from observability data. Free tier is basic; AI features need Pro or Enterprise.
Compare: PagerDuty AIOps, incident.io, Opsgenie, Rootly
