Customer Experience Monitoring
Real-Time Product Login Monitoring
Anodot’s patented machine learning monitors the functionality, performance, correctness, and speed of every login in real time, to ensure top availability of the gateway to your product or app.
360° product login monitoring
Guarantee the smooth running of the login systems that power your applications. Ensure reliability and consistency by monitoring your product login for anomalies in:
Prevent detrimental login malfunctions
An unexpected drop in product logins may indicate any number of issues with your login system and product functionality. Since login is the gateway to your product or app, problems with login systems adversely impact user experience and brand reputation and swiftly lead to significant revenue loss.
A lag in time to detection also makes it harder to figure out what happened and how to fix it, dramatically increasing time to resolution.
Connect your product
Anodot learns the normal behavior of every single login metric within minutes, and starts monitoring all incoming data in real-time. Simply use one of our built-in collectors to connect your product for immediate, complete coverage of all your login systems.
The alerts you need, right now
Anodot autonomously learns the normal behavior of every metric in your login data to distill billions of data events into the single, scored, spot-on alerts that you need to know about right now.
Leave alert storms, false positives and false negatives behind. Anodot notifies you about incidents immediately via email, Slack, PagerDuty or even Webhook.
Real-time, autonomous, adaptable coverage
Anodot’s AI-driven anomaly detection is completely autonomous. There’s no need to define what data to look for or when, no manual thresholds to set up or update.
With Anodot’s adaptive alert dashboard you can easily create advanced login monitors. Add events such as new version releases or seasonal occurrences for greater context when incidents happen.
Take your product monitoring to the next level
Fastest incident detection