AlertDuty
A SaaS alert response platform that covers alert distribution, aggregation, escalation, suppression, storage, and handling across the full alert lifecycle to improve reliability and response efficiency.
A SaaS alert response platform that covers alert distribution, aggregation, escalation, suppression, storage, and handling across the full alert lifecycle to improve reliability and response efficiency.

Supports DingTalk, Feishu, WeCom, email, SMS, and Webhook channels with routing by team, service, and severity. Ensures critical alerts reach the right responders at the right time.
Automatically groups repetitive and related alerts to reduce alert storms and operator fatigue. Helps teams focus on root causes instead of processing duplicate notifications.
Escalates alerts based on timeout, impact level, or custom policy and links them to incident workflows and third-party systems. Improves response accountability for high-priority failures.
Suppresses low-value or expected alerts during known incidents, releases, and maintenance windows. Reduces invalid interruptions and keeps on-call attention on actionable issues.
Supports scheduled and temporary silence strategies by service, label, responsibility group, and time window. Makes alert behavior predictable, auditable, and easier to manage.
Stores full lifecycle alert data with search and analysis by source, label, status, and time dimension. Provides reliable evidence for postmortems, SLA analysis, and reliability governance.
Supports acknowledge, assign, collaborate, annotate, and close actions in a unified handling process. Helps teams standardize operations and reduce cross-shift coordination overhead.
Uses historical alerts, metrics context, and handling records to provide root-cause hints and response recommendations. Speeds up decision-making and improves mean time to recovery.
Choose the plan that best fits your operations and on-call maturity.
Deploy services quickly and experience an end-to-end AI + cloud native workflow from development to delivery to operations.