AI-Powered
Alerting
Eliminate alert fatigue with AI that groups related alerts, learns your normal, routes to the right team, and tracks SLO burn rates — so you only get paged when it truly matters.
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Alerts That Work With You, Not Against You
Six capabilities that turn alert chaos into signal clarity — reducing pages by 94% while improving response times.
AI Alert Grouping
Related alerts from the same incident are automatically grouped into a single notification. Stop getting paged 50 times for one event.
Anomaly-Based Alerts
Dynamic thresholds that learn seasonality and traffic patterns. No more false alarms from Black Friday traffic spikes.
Alert Routing
Route alerts to the right team based on service ownership, severity, time of day, and custom routing rules — all in a visual builder.
Escalation Policies
Multi-level escalation chains with configurable timeouts. If the first responder doesn't acknowledge, it automatically escalates.
Noise Reduction
Machine learning identifies recurring noisy alerts and progressively suppresses them while logging for audit purposes.
SLO Tracking
Define error budgets and get burn-rate alerts before you breach SLOs. Multi-window, multi-burn-rate alerting out of the box.
Alert Anywhere
Drop-in integrations with the tools your team already uses.
Frequently Asked Questions
How does AI alert grouping reduce noise?
When multiple alerts fire for the same underlying incident — for example 47 disk I/O alerts across a Kubernetes cluster — the AI correlates them by time, affected services, and signal type, then groups them into a single incident notification. You receive one actionable page instead of dozens of duplicates, with the full list of contributing signals available in the incident detail.
What is anomaly-based alerting and how is it different from threshold alerting?
Traditional threshold alerts fire when a value crosses a fixed number you configure manually. Anomaly-based alerts fire when a metric behaves unusually relative to its own historical pattern — accounting for daily cycles, weekly seasonality, and recent deployment changes. This means you get alerted during genuine incidents and not during predictable traffic spikes like a Monday morning surge.
How do SLO burn-rate alerts work?
You define an SLO with an error budget — for example 99.9% availability over 30 days. TigerOps calculates how fast that budget is being consumed right now and alerts you when the burn rate indicates the budget will be exhausted before the end of the window. This gives you early warning with time to act rather than alerting only after the SLO has already been breached.
Can I route alerts to different teams based on the affected service?
Yes. The visual routing builder lets you define rules based on service name, alert severity, time of day, and any custom label on the alert. Each routing rule maps to a destination such as a PagerDuty service, Slack channel, or email group. A single alert can fan out to multiple destinations if multiple routing rules match.
How does the escalation policy work when no one acknowledges an alert?
Each escalation policy defines a chain of responders with configurable timeout windows. If the primary on-call does not acknowledge within the timeout, the alert automatically escalates to the secondary, then the team lead, and so on. You can define separate escalation chains per service tier to match your actual on-call rotation structure.
Get Paged Less. Fix Things Faster.
Set up intelligent alerting with AI noise reduction, SLO tracking, and automatic routing in under 10 minutes.
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