AlertOps groups alerts and recommends remediation using historical runbook context.
OpsIQ correlates incoming signals across 200+ sources using NLP and graph-based reasoning, deduplicates them into single incidents, and matches each incident against past resolutions to suggest a next step. The platform also runs the on-call rotation, escalation policy, and bi-directional ChatOps loop, so the entire incident path from signal to action lives in one tool.
Who it's for. Incident response teams of 5 to 30 on-call engineers running multi-cloud infrastructure with more than 50 alerting sources. A typical case: a node goes unhealthy, 40 alerts fire across Datadog, PagerDuty, and CloudWatch, and OpsIQ collapses them into one incident, names the node as the common cause, and suggests cordon-and-drain because that runbook resolved the last similar event.
Tradeoffs. Most of the 200 integrations are inbound webhooks. True bi-directional ChatOps remediation requires the paid tier. The AI suggestions are weak on greenfield deployments because they need a corpus of incident history to learn from. Free tier is generous for small teams but lacks SSO and audit logs.
Compare: PagerDuty AIOps, Squadcast, Opsgenie, FireHydrant
