Find issues faster than ever before. Anomify scans your metrics to find unexpected change.
Threshold rules are time consuming to maintain and prone to human error.
Many event detection products fail to deliver meaningful results because their algorithms lack the real-world context that a team brings.
Cultural differences make it hard for teams agree on a monitoring strategy. Does the person who instrumented the application also own alerts?
Train the ML brain with the knowledge siloed in your teams.
Unpick detection decisions.
Cut False Positive events by 75% while maintaining True Anomalies.
Anomify is always on, proactively learning your metrics normal behavior, identifying deviations and updating its machine learning brain.
Anomify uses a consensus method, combining forces from multiple analyses, to determine whether an event is suspicious. Analyses are weighted depending on the long term characteristics of the data.
When an anomaly is detected, correlation and related event analysis is applied to aid resolution.
Alerts are sent to your workflow in near real time enriched with contextual data. Jump directly into the dashboard to explore correlated events and carry out root cause analysis.
Anomify creates context through correlation, change detection and related event analysis.
Get alerts delivered to your workflow with supportive context so that anyone on the team can interpret the issue.
Anomify's infrastructure sits on top of our patented architecture for guaranteed uptime.
Access analysis and results programmatically.
Have a specific case you want to catch? You can bolt a custom algorithm or threshold onto the analysis pipeline.
Explore interactive real-time charts, check the health of your metrics or train the detection system.