Proactive Monitoring

Identify user experience issues before they occur

Track and alert on global API endpoint response times, HTTP status codes, and SLOs like error budgets and burn rate
Create automated browser tests without a query language to ensure user actions execute accurately across devices and locations
Proactively monitor recurring checks for UI changes and new elements using self maintaining browser tests

Utilize machine learning based alerts for proactive monitoring

Algorithmically discover seasonal trends and only alert on behavior outside of historical patterns with anomaly detection
Use tags to detect outliers, like specific hosts or availability zones, that are behaving unusually compared to their established group
Proactively monitor and predict metric behavior and get notified when a machine learning projected threshold is breached with forecasting

Proactively monitor the “unknown unknowns” in your systems

Automatically surface anomalous behavior without manually setting up and configuring alerts with the Watchdog auto-detection engine
Detect application and infrastructure issues with proactive monitoring of hits, error rates, latency or metrics from turnkey integrations
Evaluate curated issue summaries, detailed performance information, and automatically search for irregularities in related metrics with Metric Correlations