For Site Reliability Engineers
Hit your SLOs.
Without burning out.
SLO tracking, error budget management, and burn-rate alerts — all from the same platform you already use for observability.
The challenges every site reliability engineers team faces
And how aiAxonIQ solves them.
SLO blindness
You defined SLOs in a spreadsheet. No real-time tracking, no error budget visibility, no early warning before burn-down.
Live SLO tracking with multi-window burn-rate alerts. Know exactly where your error budget stands at any moment.
Learn about SLOs & Error BudgetsIncident timeline chaos
Reconstructing what happened takes longer than the incident itself. Slack messages, Grafana screenshots, manual timelines.
AI incident summaries assemble the likely root cause from correlated logs, traces, and metric anomalies.
Learn about AI InsightsHigh on-call load
Too many alerts, too many false positives. On-call is unsustainable and engineers are leaving.
Anomaly rules, cooldown windows, and label-based silences cut false positives — so a page means something.
Learn about AlertingHow it works in practice
Your improved workflow, step by step.
Platform modules used
Everything site reliability engineers teams need, in one place.
Why it works
Reliability you can put a number on
Availability, latency, error-rate, and custom-query SLOs are computed straight from your traces and metrics. Multi-window burn-rate alerts catch fast and slow burns before the budget is gone, and AI can author SLOs from plain English or propose them from seven days of measured evidence.